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Digital finance research and developments around the World: a literature review

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• Published: 11 September 2023

Research on the influence of digital finance on the economic efficiency of energy industry in the background of artificial intelligence

• Qiao He 1 &
• Ying Xue 2  

Scientific Reports volume  13 , Article number:  14984 ( 2023 ) Cite this article

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• Environmental sciences
• Environmental social sciences
• Solid Earth sciences

China's economic growth has reached a new plateau. It is no longer appropriate to use the old economic growth model, which relied on labor, land resources, mineral resources, and other economic considerations. Under the background of artificial intelligence, high-quality economic development is an inevitable trend. A new financial paradigm called "digital finance" integrates financial services with information technologies. Digital financial technology is thought to be a crucial foundation for fostering high-quality and sustainable economic and social development since it may offer more economic entities reduced cost of capital and more realistic financial service skills than in traditional financial models. In the era of artificial intelligence, how to reasonably release the momentum of digital finance for China's sustained economic growth has become a hot topic of discussion at this stage. This paper studies the impact of digital finance on the economic efficiency of the energy industry in the context of artificial intelligence. Relevant metrics were also calculated. The findings revealed that: The benchmark regression result of digital finance on the efficiency of the green economy was 0.4685 before adding the main restrictions; the benchmark regression result of digital finance on the efficiency of the green economy was 0.2243 after adding the main constraints. As a result, data finance had a favorable impact on the effectiveness of the green economy.

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The coordinated growth of the real economy and the digital economy takes the conventional "reverse integration" path, with the financial sector serving as the first example of its transformation and development characteristics in the tertiary sector. Digital finance generally refers to the use of electronic information technology by traditional financial institutions and online businesses to carry out new financial services like payment, project investment, and equity financing. The limitations on time and space between product transactions and financial services have been eliminated by the quick development of digital finance. In the era of artificial intelligence, what is the role of the rise and application of digital finance in the critical period of innovation in promoting strategic planning. Whether it can fill the shortcomings of the traditional financial system and improve the efficiency of urban green economic development and the financial market department's strong support and promotion of innovation and manufacturing, and better support the economy of the energy industry, requires further review and debate. Digital financial technology can provide more accurate Market trend forecast and energy price forecast by processing large-scale data and applying advanced data analysis technology. This will help energy companies make more intelligent decisions, optimize resource allocation, reduce production and operating costs, and thus improve Economic efficiency. The application of digital financial technology can improve the Economic efficiency of the energy industry, improve the efficiency of resource utilization, reduce waste and promote the sustainable development of the energy industry.

Literature review

Numerous professionals and academics have always focused their research on strategies to increase the effectiveness of the urban green economy. In order to create a model that could be used for urban green economy planning, Liu T enhanced the conventional algorithm and merged the principle of machine learning algorithm. Efficiency indicators for the green economy were evaluated in terms of input, anticipated output, and unexpected production. Comparison and analysis were done on the green efficiency determined using the relaxation value calculation model. The study's findings demonstrated that the model could be used in the design phase of urban green planning and that it had specific effects 1 . China's green economic efficiency and green total factor productivity were assessed and examined by Gao X. Furthermore, the shortcomings of conventional clustering techniques in high-dimensional data clustering were highlighted by outlining the properties of high-dimensional data. A sampling and residual squared-based density peak clustering technique was put forth. The experimental comparison on the data set revealed that in terms of time complexity and clustering outcomes, the modified algorithm outperformed the delayed procedure call approach 2 . Sarcheshmeh M examined the performance of urban green space in terms of social and economic indices in the Mashhad metropolitan region. 15 social questions and 5 economic questions from the research questionnaire were tested and examined using the SPSS22 program. The findings demonstrated that there was no appreciable impact on the management effectiveness of the urban green space sector in the city of Mashhad. From the perspectives of citizens and managers, several features of the social index were rated as desirable 3 . In order to examine the dynamic changes in the economic effectiveness of urban land use in South Korea at the regional level and to determine whether it would be feasible to implement the green belt policy, Yongrok C used the ecological efficiency measurement model. In order to increase the economic benefits of urban land use and execute sustainable green space management, more performance-oriented policy solutions were advocated 4 . These studies do have some impact on increasing the effectiveness of urban green economy and urban planning, but digital finance has received far too little attention. The market for digital finance is quickly taking over with the pace of the new economic system. The city's long-term development would have an effect on how effective the urban green economy is.

There are more research on the direct or indirect effects of digital finance on economic growth than there are on the effect of digital finance on the effectiveness of urban green economies. Based on the database for the growth of digital financial inclusion and the China Family Panel Studies, Xie W investigated the relationship between coastal rural residents' entrepreneurship and the development of China Family Panel Studies (CFPS). The empirical findings indicated that a crucial factor in encouraging rural entrepreneurship was the thorough development of digital financial inclusion. The monetary capital index and the payment index both significantly boosted rural inhabitants' entrepreneurial activity. The study also discovered that the effects of digital financial inclusion on rural residents' entrepreneurship exhibited signs of geographical variation 5 . In the context of economic digitization and the development direction of contemporary financial technology legal supervision, Barykin S determined the function of digital finance in the financial system. By adding new features of digital assets, the digital financial cube might be expanded to match the level of openness of industrial firms in the future Industry 4.0 technological framework 6 . The long-term causal impacts of digital financial inclusion on economic growth in sub-Saharan Africa were investigated by Thaddeus K J. The study made use of quarterly data from 2011 to 2017 and a sample of 22 sub-Saharan African nations. The findings indicated a long-term causal link between digital financial inclusion and economic growth in sub-Saharan Africa, with the causal relationship running one way from economic growth to inclusion in the latter 7 . Rastogi S set out to investigate how unified payment interface affects financial inclusion, economic development, and financial literacy of the underprivileged in India. He discovered that financial literacy was being impacted. Financial stability and trust both served as partial moderators of the significant associations between digital financial inclusion and economic development as well as the significant link between financial literacy and financial inclusion. This fostered financial inclusion and economic growth for the underprivileged in addition to supporting financial literacy 8 . Lin Boqiang uses the non radial direction distance function to build green Economic efficiency indicators that can evaluate cities at prefecture level and above in China under the super efficiency framework, and further empirically studies the impact of economic agglomeration on green Economic efficiency. To solve the endogenous problem caused by reverse causality between economic agglomeration and green Economic efficiency 9 .

The perfect combination of digital technology and financial services has created a new financial service model. With the help of intelligent digital technology, digital finance can provide lower capital cost and faster service mode for the real economy, provide financial services with "high efficiency, convenience and sustainable commercial services" for the energy industry, and complete the unification of objectivity and precision of financial services. This paper discusses the influence of digital finance on the economic efficiency of the energy industry under the background of artificial intelligence, and aims to provide theoretical guidance for the improvement of the green economic efficiency in the energy industry.

The influence mechanism of digital finance on the economic efficiency of the energy industry

New energy technologies include solar power generation, water energy, wind energy, tidal energy, sea surface temperature difference energy, wave energy, firewood, peat soil, biochemical material energy conversion, geothermal energy, tar sand, etc. At this stage, it is generally recognized that new energy and renewable resources are based on the development trend of new technology application, and gradually change the development and utilization of renewable resources. The traditional fossil energy resources with environmental pollution problems and limited total amount should be replaced by new energy sources that will not be limited by the total amount and the utilization of the recycling system. The key development areas include solar power generation, tidal energy, hydrogen energy and wind energy.

The new energy industry is the exploration, development and utilization of new energy. It uses social methods to achieve effective utilization and popularization, including the whole process of scientific research, industrial utilization, production, manufacturing and operation. It is a high-tech that commercializes solar power generation, wind energy, bioenergy, etc. From the perspective of the characteristics of the industrial chain, the new energy industry is to replace the new industries with strategic status represented by fossil energy, and has extremely important obligations in replacing fossil energy, promoting economic growth, protecting the environment, and building a harmonious society; From the perspective of the whole industry chain, the new energy industry can be divided into energy supply, product research and development, investment and manufacturing, transportation and trading.

The Corona Virus Disease 2019 pandemic has had a major impact on the traditional financial services provided by financial institutions, but it has also accelerated the digital transformation of these services. According to the statistics and analysis of the China Asset Appraisal Association, during the epidemic period, the average service item replacement rate of online banking reached 96%. Despite the epidemic's considerable effects on small and micro businesses and traditional financial "long-tail clients", However, under the background of the intelligent era, the development speed of digital banking is enough to solve the problems of these groups. Through "zero contact" to provide them with low-cost, convenient and fast service projects, especially the contact-free loan has become an important means to help the sustainable development of the energy industry 10 .

The development of digital finance requires a complete institutional system, and the institutional system of digital finance is the financial ecosystem, which is composed of the main body of the ecosystem and the financial ecological environment. The close combination of the two can produce a regular financial ecosystem with internal logic and self-improvement. Judging from the current overall situation of China's financial institution management system, it has basically formed a large digital financial service ecological chain dominated by banking, Internet banking, non-bank finance, and large and medium-sized financial high-tech companies with electronic payment system, integrity management system, legal norms as infrastructure and institutional guarantee, which is dominated by the "one committee, one bank, two committees and one bureau" supervisory agency 11 , 12 . A schematic representation of the structure of the digital financial ecosystem is given in Fig.  1 .

Digital financial ecosystem.

At this point, a significant trend is the close integration of digital technology with finance. In the era of artificial intelligence, digital technology is playing a unique and important role in modern finance. The following points mostly highlight the benefits of digital finance: Firstly, by increasing financing channels, the threshold for financial services has been lowered; secondly, by greatly reducing service prices, comprehensive financial services have achieved sustainable development; thirdly, the personalized financial services can better meet the various requirements of different users; the fourth is to help reduce information asymmetry and provide new risk management methods 13 .

According to different levels of financial functions, digital finance can be divided into three categories: basic functions, leading functions and derivative functions. Figure  2 shows the mechanism of digital finance on the efficiency of urban green development. There are three behavioral paths for the above three functions. The first is digital finance → intermediary services → inclusive utility. Digital finance uses digital information technology to manufacture and expand the role of finance. The network effect of digital technology expands the boundaries of traditional financial services and reduces the service cost of traditional finance. The scale and economic characteristics of digital finance reduce the entry threshold and related costs for innovative enterprises. At the same time, by relying on digital technology, the ability to obtain data and analyze information has been greatly improved and the information asymmetry and the cost of credit intermediary companies have been reduced, and the credit environment has been optimized. After building a three-dimensional credit image based on enterprise big data and cloud technology, sporadic enterprises and start-up companies that are difficult to obtain the support of traditional credit services would obtain a high probability of credit. In order to increase the effectiveness of the urban green economy, the development of digital finance would also help traditional finance change and grow. It would also make full use of the complementary roles that traditional finance and digital finance play in advancing economic growth. Therefore, digital finance will promote the development of traditional finance, and will promote the economic development of the energy industry, and achieve the effect of improving the economic efficiency of the energy industry 14 , 15 .

The impact of digital finance on how well urban green development is carried out.

The second is digital finance → resource allocation service → upgrade utility. Resource allocation service is the core role of finance and an excellent way to correctly guide use value. On the one hand, the birth of digital finance has promoted competition among financial formats and enhanced the charm of folk capital and the financial system, and improved the efficiency and capability of capital allocation. The use of artificial intelligence and electronic information technology can better match the investment needs and financing needs, reduce the financing pressure of the energy industry, and make the capital used more efficiently and quickly for innovation. On the other hand, the circulation of capital factor commodities has been improved. For a long time, in the factor market, the government department has the dominance and dominance of the vast majority of manufacturing factors, and there may be behaviors such as abuse of power. In addition, the popularity of local protectionism and the emergence of administrative systems have resulted in serious market segmentation. The inconsistency and segmentation of the elements of the sales market make some enterprises, especially state-owned enterprises, lose the driving force of "self-innovation". This harms the development of the urban green economy's efficiency. To provide enough financial factors for the supply-side structure's green development, Digital finance enables the energy industry to overcome regional barriers and enhance the environment for the free flow of capital. Therefore, by enhancing and upgrading the efficiency of regional capital element allocation, data finance can achieve the effect of boosting the efficiency of urban green economy 16 .

The third is digital finance → redistribution of finance → inclusive utility. The rapid development of inclusive finance, on the one hand, helps low-income people get rid of poverty and become rich, which improves the level of per capita consumption and promotes economic transformation and upgrading; on the other hand, with the expansion of the number of netizens and network coverage and the rapid rise of e-commerce and Internet consumer finance, the consumption structure of urban residents has also gradually changed. The demand-side consumption capacity and consumption structure have been upgraded, and the energy industry has increased its demand for high-quality products. This has prompted the energy industry to expand the scope of its technology investment and product development efforts, and to encourage the growth of a local green economy. Therefore, digital financing encourages the energy industry to expand technology investment and product research and development, which has the effect of improving the efficiency of urban green economy 17 .

The energy industry is an indispensable part of economic development. Digital finance provides loans to small and medium-sized energy enterprises to meet the financing needs of small and medium-sized energy enterprises, thus stimulating regional economic growth. However, these small and medium-sized energy enterprises are struggling with financial problems and high financing costs. Only a small number of enterprises can apply for loans from financial institutions through official channels, and other enterprises are under pressure of capital loans. The growth of financial inclusion through digital means has reduced borrowing costs and simplified processes. By providing special loans to such enterprises to help them improve their financing and risk management capabilities, it will help improve their profitability and ultimately improve China's economic growth rate 18 , 19 .

If the capital supply cannot keep up, there will be a lock-in effect, and it is imperative to get rid of this inefficient equilibrium state. The basic strategy is to provide specific capital elements for the energy industry, so the assistance of participating banks is essential, and micro loans for small and medium-sized energy industries can help them achieve higher output. Continuous investment in capital and technology will reduce marginal costs, which will have an impact on increasing output and income 20 , 21 . As shown in Fig.  3 , the structure of micro credit's anti lock support effect.

Anti-lock-in support effect structure diagram of microfinance.

This paper discusses the impact of digital finance on the economic efficiency of the energy industry in the context of artificial intelligence. The calculation formula of some indicators related to the measurement of the economic efficiency of the energy industry is as follows:

\(T\) -set of control variables; \({GTFP}_{au}\) -Green economic efficiency of energy industry; \({df}_{au}\) -digital finance; \({df2}_{au}\) -square term of digital finance; \({\omega }_{au}\) -disturbance term; \({\theta }_{a}\) -time fixed effect

\({m}_{au}{^\prime}\) -a collection of independent variables; \({\mathrm{g}}_{\mathrm{au}}\) -threshold variables

\(distrk\) -degree of capital misallocation

\({\mathrm{lngdp}}_{\mathrm{au}}\) -degree of capital distortion

\({MP}_{au}\) -margin of capital

\(\mathrm{d}\) - \(\mathrm{d}\) kinds of inputs; L-L kinds of expected outputs; J-J kinds of undesired outputs; \(\upgamma \) -green total factor productivity efficiency value.

Restrictions:

Let the formulas be:

\({\mathrm{cap}}_{\mathrm{au}}\) -fixed capital stock of the whole society; \({\propto }_{\mathrm{a}}\) -capital depreciation rate

\({\mathrm{cap}}_{\mathrm{a},0}\) -cap initial capital stock; \({\mathrm{o}}_{\mathrm{a}}\) -cap average annual growth rate.

Empirical study on the impact of digital finance on economic efficiency of energy industry

In order to explore the impact of digital finance on the economic efficiency of the energy industry in the context of artificial intelligence, we calculated some indicators of the economic efficiency development level of the energy industry 22 , 23 . Kao (1999) Panel data cointegration test uses the correlation information between individuals to decompose Panel data into inter individual mean and intra individual changes. If the inter individual mean is non-stationary and the residual term is stationary, then the existence of cointegration can be verified. The results are as follows:

As shown in Fig.  4 , the change index of green economic efficiency development of energy industry in some cities of China from 2010 to 2020. We selected 20 cities in China for data analysis. The standard deviation is used to measure the Statistical dispersion of a group of data. The larger the standard deviation, the higher the volatility of the data. The average is the average of the green Economic efficiency development index. From the average and median, the average development level of green economic efficiency of these energy industries has increased from 0.1782 in 2012 to 0.3891 in 2020, and the median has also increased from 0.1342 in 2012 to 0.3247 in 2020. Both are rising year by year. From these two indicators, the green economic efficiency level of the energy industry shows a trend of doubling, this also means that the green economy development level of the energy industry has made a qualitative leap. The coefficient of variation did not change significantly from 2010 to 2020, with a value of 0.5687 in 2010 and 0.5682 in 2020. From the perspective of range and coefficient of variation, the range describes the difference between the highest level and the lowest level. In 2012, the range value of green economic efficiency of the energy industry was 0.4213, while in 2020, the range value of green economic efficiency of the energy industry was 0.8925, which also shows an increasing trend year by year. This means that the gap between the development levels of green economy of the energy industry is increasing year by year, while the difference between the extreme values from 2018 to 2020 shows a trend of slowing growth, this also shows that we are also increasing the level of green economy development in economically backward energy industries. It can be seen from the figure that the coefficient of variation of the green economic efficiency of the energy industry fluctuates, but it does not change much, and even shows a downward trend, which also shows that the green development level of the energy industry does not show a development trend of two-level differentiation.

Change index of green economic efficiency development of energy industry in some cities.

Regression analysis is conducted with or without control variables to examine the robustness of digital finance on the effectiveness of green economy in the energy industry 24 . The regression results of the efficiency standards of green economy and digital finance in the energy industry are shown in Fig.  5 . Where, A represents the result of basic regression without major control factors, and B represents the result of benchmark regression including major control components. It can be seen that before adding the main restrictions, the benchmark regression result of digital finance on the effectiveness of green economy is 0.4685. After the main limiting factors are included, the benchmark regression result of the effectiveness of digital finance on the green economy is 0.2243. Therefore, data finance has a beneficial impact on the effectiveness of the green economy. The green development level of the energy industry does not show a trend of two-stage differentiation, and the benchmark regression results slightly decrease after adding limiting factors. Digital finance will affect the green development level of the energy industry.

Digital finance and green economy efficiency benchmark regression results.

The benchmark regression coefficient results of the influence of pertinent variables on green economic efficiency are shown in Table 1 . It is clear that the benchmark regression coefficients for improving industrial structure, economic development level, and income from both the public sector and higher education are all positive and pass the 5% significance level test. This demonstrates how investing in financial education, upgrading the industrial structure, and the degree of economic development all help the green economy grow and become more efficient. Despite being positive, the benchmark regression coefficient of environmental legislation on green economic efficiency fails the test of significance. The expense of reducing environmental pollution has perhaps increased, which forces businesses to implement relevant technology advancements. The benchmark regression coefficient for openness to the effectiveness of the green economy is negative, and thus failed the significance threshold test. This may be because the entry of foreign high-tech has raised pressure on environmental governance by bringing about not only economic development but also an industrial chain that produces a lot of pollution and uses a lot of energy.

Choosing cross-sectional analysis with fixed effects rather than random effects means that there are fixed differences between individuals, and the impact of these differences on variables is constant. This fixed effects model assumes that individual specific factors have a significant impact on the observed variables, and these factors are fixed during the observation period.

The computation of the conduction effect is shown in Fig.  6 . They are digital finance-green economy development efficiency, digital finance-scientific and technical innovation-green economy efficiency, and digital finance-green economy efficiency as a whole. The conduction line of direct effect is digital finance-green economy efficiency. It can be seen that the computed value of the direct relationship between digital finance and green economic efficiency is 0.1698, indicating that the growth of urban green economic efficiency would be directly impacted by the development of digital finance. The calculated indirect effect value is 0.0413, which suggests that digital finance can boost technological innovation to make cities more environmentally friendly by saving energy and lowering consumption and pollution. The level of green economic growth can be raised while industrial upgrading is encouraged. The total effect of digital finance on the effectiveness of green economy in the energy industry is the sum of its direct effect and indirect effect, of which the intermediary effect accounts for 19.56% of the total effect.

Conduction effect calculation results.

The panel quantile estimation can assess the effect of digital finance on it under each quantile based on the distribution of green economy efficiency levels. The efficiency of the green economy and digital finance are shown in Fig.  7 as the panel quantile regression findings. It is can be seen that for the five quantiles, the estimated coefficient of digital finance climbs as the quantile increases from 0.3042 for the 10% quantile to 0.4276 for the 90% quantile. The increase in the favorable effect is 0.1234, and the significance threshold is 1%. In other words, digital finance has a good effect on the effectiveness of the green economy, and the promotion effect would get stronger as the quantile value rises. This does not help digital finance increase the efficiency of the green economy. However, as the green economy expands and digital infrastructure continues to advance, the beneficial role that digital finance plays in fostering the growth of the green economy would only grow.

Panel quantile regression results of digital finance and green economy efficiency.

In the panel Quantile regression analysis data of digital finance and green Economic efficiency, the estimation coefficient of digital finance is constantly improving, and the significance threshold has always been 1%, so the rise of quantile value will make the promotion of green Economic efficiency stronger.

Conclusions

This paper analyzes the impact of digital finance on the green economic efficiency of energy industry in the context of artificial intelligence, and evaluates the green economic performance of energy industry in some cities from 2010 to 2020. The empirical research results show that the rapid development of digital finance will significantly improve the efficiency of green economy in the energy industry, and show diversity with the change of city size and industrial development level. Digital finance has the synergistic effect of independent innovation and ecological compensation. Through independent innovation and environmental security management, we can jointly improve the efficiency of green economy. Based on this paper, the following suggestions are put forward: encourage financial institutions, insurance and other traditional finance to transform to digital, use data technology to safeguard the traditional financial system, and accelerate the construction of intelligent facilities in various regions; Give full play to the coordinating role of the financial technology service management system in the introduction of innovation policies, patent applications and other aspects. Accelerate the cooperation between the government and the digital financial platform, and give full play to the aggregation effect of financial markets and policies on independent innovation. Make full use of the ecological compensation effect of digital finance on production units, promote financial innovation through joint development of digital finance, and promote the growth of small and medium-sized enterprises in the upstream and downstream of the green industrial chain and supply chain. The government can formulate policies to encourage energy companies to adopt digital financial technologies, such as blockchain, Big data analysis and artificial intelligence, to improve efficiency and reduce costs. For example, the government can provide tax or subsidy incentives to encourage enterprises to invest in the research and application of digital technology. At the same time, it is necessary to prevent losses caused by excessive economic leverage, so that data finance can better provide energy for the urban real economy.

Data availability

Datasets generated and/or analyzed during the current study are available from the corresponding author on request.

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He, Q., Xue, Y. Research on the influence of digital finance on the economic efficiency of energy industry in the background of artificial intelligence. Sci Rep 13 , 14984 (2023). https://doi.org/10.1038/s41598-023-42309-5

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DOI : https://doi.org/10.1038/s41598-023-42309-5

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The impact of fintech and digital financial services on financial inclusion in india.

1. Introduction

2. reviews of literature, 3. research gap and objectives, 4. research methodology, 4.1. sample design, 4.2. data collection method, 4.3. results, 4.4. estimates, 5. conclusions, 6. implications, 7. scope of future research, author contributions, informed consent statement, data availability statement, conflicts of interest.

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Share and Cite

Asif, M.; Khan, M.N.; Tiwari, S.; Wani, S.K.; Alam, F. The Impact of Fintech and Digital Financial Services on Financial Inclusion in India. J. Risk Financial Manag. 2023 , 16 , 122. https://doi.org/10.3390/jrfm16020122

Asif M, Khan MN, Tiwari S, Wani SK, Alam F. The Impact of Fintech and Digital Financial Services on Financial Inclusion in India. Journal of Risk and Financial Management . 2023; 16(2):122. https://doi.org/10.3390/jrfm16020122

Asif, Mohammad, Mohd Naved Khan, Sadhana Tiwari, Showkat K. Wani, and Firoz Alam. 2023. "The Impact of Fintech and Digital Financial Services on Financial Inclusion in India" Journal of Risk and Financial Management 16, no. 2: 122. https://doi.org/10.3390/jrfm16020122

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Research Article

Digital finance and corporate breakthrough innovation: Evidence from China

Roles Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Visualization, Writing – original draft, Writing – review & editing

* E-mail: [email protected]

Affiliation School of Accounting, Shandong University of Finance and Economics, Jinan, China

• Published: July 29, 2024
• https://doi.org/10.1371/journal.pone.0307737
• Reader Comments

This paper empirically investigates the impact of digital finance on the breakthrough innovation of enterprises with a sample of A-share listed companies in Shanghai and Shenzhen from 2011 to 2022. It is found that digital finance can promote corporate breakthrough innovation, and presents certain structural heterogeneity characteristics. The mechanism test shows that digital finance has the dual attributes of a financing platform and a social platform, which can promote breakthrough innovation by alleviating corporate financing constraints and expanding corporate social networks. Heterogeneity analysis reveals that the role of digital finance in promoting breakthrough innovation is characterized by regional heterogeneity, with digital finance playing a greater role in promoting breakthrough innovation in provinces with a low level of development of the banking sector, provinces with a high level of development of the capital market sector, and the central region. In addition, the degree of firms’ external financing dependence and the degree of product market competition can strengthen the positive effect of digital finance on firms’ breakthrough innovation. This paper enriches the related research on the impact of digital finance on enterprise innovation, and provides theoretical basis and policy insights on how digital finance can better assist the innovation-driven development strategy.

Citation: Shi Y (2024) Digital finance and corporate breakthrough innovation: Evidence from China. PLoS ONE 19(7): e0307737. https://doi.org/10.1371/journal.pone.0307737

Editor: Suzan Dsouza, American University of the Middle East, KUWAIT

Received: March 11, 2024; Accepted: July 9, 2024; Published: July 29, 2024

Copyright: © 2024 Yanmin Shi. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: Data cannot be shared publicly because of the authors have no right to share the data. People who are interested can obtain the data via https://www.ccerdata.cn/ , https://www.cnrds.com/ and https://cn.gtadata.com/ .

Funding: The author(s) received no specific funding for this work.

Competing interests: The authors have declared that no competing interests exist.

1. Introduction

Enterprise innovation is of significant in promoting China’s industrial restructuring and economic transformation and is the core driving force in leading high-quality economic development. The Outline of the Fourteenth Five-Year Plan for the National Economic and Social Development of the People’s Republic of China and the Vision 2035 states that it is necessary to "strengthen the status of enterprises as the main body of innovation, and promote the concentration of all kinds of innovation factors in enterprises." Under the internal and external constraints of increasing uncertainty in the world economic situation and the domestic economy being in a critical period of transforming the growth momentum, the key to solving the problem of the "necklace" of critical technologies and the successful implementation of the innovation-driven development strategy lies in the ability to improve the quality of innovation. Although the quantity of innovation in Chinese enterprises has increased significantly, the quality of innovation still needs to improve. According to the dual innovation theory, enterprise innovation can be categorized into progressive and breakthrough innovation according to the nature of change and the degree of innovation [ 1 ]. Progressive innovation refers to minor improvements to existing products along the current path based on existing knowledge. In contrast, breakthrough innovation refers to breaking the boundaries of existing knowledge and utilizing brand-new technologies to create new products. Progressive innovation mainly reflects the quantity of innovation [ 1 ]. In contrast, breakthrough innovation can change the existing technological paradigm and expand the original technological boundaries, which is more groundbreaking and disruptive [ 2 ], and helps enterprises eliminate the "necklace" dilemma, which is an essential reflection of the quality of innovation [ 3 ]. Therefore, in the context of China’s efforts to enhance its core competitiveness and build world-class enterprises, it is of great practical significance to explore how to enhance breakthrough innovation for Chinese enterprises to improve the quality of innovation and gain international competitive advantages.

Breakthrough innovation is a destructive innovation that requires firms to invest more resources and take more significant risks. The innovation outcome is also more uncertain, leading to breakthrough innovation facing more serious financing constraints. Moreover, breakthrough innovation is based on brand-new knowledge, which requires enterprises to conduct extensive knowledge search and exploration [ 4 ]. Financial institutions can provide a source of funds for enterprise innovation activities. However, China’s traditional finance has revealed some structural mismatches in supporting enterprise innovation activities, which has led to an apparent “liquidity stratification” phenomenon of financial resources and constrained the potential driving force of financial institutions in the development of innovation, especially breakthrough innovation. In order to make finance better serve the real economy and improve the quality of enterprise innovation, the 20th Party Congress emphasizes “deepening the reform of the financial system.” The digital economy has become the most dynamic, innovative and widely radiating economic form. Traditional finance has taken the opportunity of the booming development of the digital economy to organically integrate with emerging digital technologies such as big data, cloud computing and information technology to form a new financial service model, and digital finance has emerged. Unlike traditional finance, digital finance empowers or upgrades financial products and business processes with the help of technology, characterized by low cost, low threshold and convenient sharing [ 5 ]. Among them, big data processing technology can alleviate the problem of information asymmetry in the financial market [ 6 ], cloud computing technology can promote the connection between financial subjects and reduces transaction costs to expand and strengthen the communication and exchange between the subjects involved in the financial market; information technology can help to broaden the content and boundaries of financial services and optimizes the allocation of resources. Therefore, digital finance may lay the foundation for breakthrough innovation of enterprises by alleviating financing constraints and enhancing networks relationships.

Studies have shown that digital finance can significantly contribute to corporate innovation [ 5 – 8 ]. For example, Zhao et al. argue that digital finance not only helps firms to increase R&D investment but also can positively affect the quantity and quality of innovations [ 7 ]. Zhang et al. demonstrate the positive effect of digital finance on innovations regarding the number of patents filed and granted [ 8 ]. Xie and Wu conducted a study using panel data from Chinese provinces and found that digital finance can boost regional R&D conversion rates [ 5 ]. Specifically, Yao and Yang conducted a study using a sample of Chinese GEM-listed companies and found that digital finance can stimulate innovation vitality and improve the innovation level of enterprises [ 6 ]. Scholars generally agree that digital finance can positively impact enterprise innovation. However, scholars have not yet reached a unanimous conclusion on the incentive mechanism therein, with most scholars agreeing with the mechanism of financing constraint alleviation in digital finance [ 6 – 8 ], and some scholars proposing a mechanism of bank competition improvement [ 8 ], and business environment improvement mechanism [ 7 ]. The above results provide strong theoretical support and methodological inspiration for this paper to explore how digital finance affects enterprise breakthrough innovation. However, breakthrough innovation belongs to a higher degree of innovation mode, which has similarities and differences with innovation, especially breakthrough innovation, which needs to be based on new knowledge, which determines that digital finance may have heterogeneous effects on enterprise breakthrough innovation through other mechanisms. Unfortunately, there is a lack of a complete analytical framework and empirical findings on the digital finance drive in corporate breakthrough innovation, and only Zhao et al. briefly discusses the differences in the degree of incentives of digital finance on incremental and breakthrough innovations in his study of digital finance to promote the innovation output of firms [ 7 ].

Digital finance, as a new financial service model resulting from the fusion of traditional finance and emerging digital technologies, is bound to have the financing attributes of finance and higher efficiency of its financing services on the one hand [ 9 , 10 ], and on the other hand, it also has the attributes of social networking based on emerging digital technologies [ 11 ]. Theoretically, financing services can provide the necessary capital for breakthrough innovation, while social networks can provide access to the knowledge needed. Given this, this paper takes A-share listed companies in Shanghai and Shenzhen from 2011 to 2022 as the research sample, empirically analyzes how digital finance affects corporate breakthrough innovation, and further examines its intrinsic mechanism. It has been found that digital finance can promote corporate breakthrough innovation. The mechanism analysis finds that the attributes of the financing platform and social networking platform of digital finance can alleviate the financing constraints and expand the social network of enterprises, positively promoting breakthrough innovation.

Compared with the existing literature, the research contribution of this paper is mainly reflected in the following three aspects: first, empirical analysis of the effect and path of digital finance on corporate breakthrough innovation, which not only expands the research on the impact of digital finance on the behavior of microenterprises, but also enriches the results of the literature on corporate breakthrough innovation; second, the study empirically examines the path of digital finance affecting corporate breakthrough innovation, and found that digital finance can promote corporate breakthrough innovation by alleviating the financing constraints and expanding social networks, which is specific guidance for the further development direction of China’s financial institutions; third, the study finds that in promoting corporate breakthrough innovation, digital finance has a deficiency-complementing effect of delivering charcoal in the snow and an advantageous gain of icing on the cake in the capital market, which provides direct empirical evidence supporting the government’s positive significance of the comprehensive development of the financial market.

2. Theoretical and hypotheses

According to the dual innovation theory, incremental innovation is to improve the original product based on existing knowledge [ 12 ], while breakthrough innovation requires companies to break the boundaries of established knowledge and make disruptive changes to existing products or services based on exploring new knowledge in order to enter into a completely new technological field [ 12 – 14 ]. It can be seen that breakthrough innovation emphasizes the exploration of new knowledge compared to incremental innovation’s use of existing knowledge, which requires firms to pay higher costs and take more significant risks, as well as more resource support [ 12 ]. Therefore, abundant financial support and heterogeneous knowledge allow firms to engage in breakthrough innovation [ 15 ]. However, Chinese firms generally need more conditions to carry out breakthrough innovation at present, and it has become an essential way for Chinese firms to enhance their innovation capability by obtaining financial support and heterogeneous knowledge to support their breakthrough innovation behavior [ 16 , 17 ].

Relying on information technology such as big data, cloud computing and blockchain, digital finance has the dual attributes of a financing platform and a social platform. By alleviating financing constraints and expanding social networks, digital finance can lay the foundation of capital and knowledge for corporate breakthrough innovations.

2.1 Financing platform attribute of digital finance and corporate breakthrough innovation

From the perspective of alleviating financing constraints, finance is a core component of the enterprise innovation environment, and the adequate supply of finance will inevitably also affect the development of corporate breakthrough innovation activities [ 18 ]. However, traditional finance has problems such as insufficient supply and uneven distribution in serving the real economy, which makes enterprises face more serious financing constraints and restricts the development of breakthrough innovation activities. According to the theory of financing constraints, information asymmetry, and transaction costs are the main reasons for financing constraints. At the same time, digital finance can alleviate the financing constraints of enterprises by increasing the quantity of financial resources supply, improving the efficiency of financial resources allocation, and reducing the information asymmetry between enterprises and financial institutions, thus promoting enterprises to carry out breakthrough innovation.

First, digital finance increases the amount of financial resources supplied. Under the current financial system, China’s financial resources rely mainly on the banking sector to provide them. However, because the knowledge assets accumulated by breakthrough innovations are usually intangible [ 19 ], the limited collateralized value of intangible assets restricts the use of debt [ 20 ]. According to the theory of financing constraints, in the case of the low collateralized value of corporate assets, the amount of financial resources available to the enterprise is limited, and the cost increases, resulting in the breakthrough innovation of the enterprise facing a severe problem of financing constraints. digital finance based on fintech can revitalize existing financial resources outside the formal financial system and bring into the market financial businesses that used to be fragmented, niche and unattended. Moreover, digital finance has a low-cost advantage, and developing a series of financial resources often accompanies its emergence. These are conducive to expanding the financial resource system and increasing the supply of financial resources, which enables enterprises to obtain more financial support at a lower cost and helps them to carry out breakthrough innovation.

Second, digital finance improves the efficiency of financial resource allocation. There are many decentralized small-scale investors in the financial market, and these investors are the long-tail group in the financial market. Traditional finance is confined to technology, cost, etc., and cannot efficiently absorb the long-tail group, resulting in the inefficiency of traditional financial services. Moreover, digital finance, supported by information technology, can process massive data based on low cost and low risk, broaden the boundary of financial services, reach a broader range of tail groups, reduce the threshold and cost of financial services, form a more efficient model of financial service, and reduce the cost of financing for breakthrough innovation of enterprises. In addition, digital finance, as a kind of financial spillover, subverts the traditional credit pricing model through the transparency and informatization of credit, which can force financial institutions to transform and upgrade to a certain extent [ 15 , 21 ] making financial services more compatible with the needs of enterprises, improve the efficiency of financial resource allocation, and provide financial support for the breakthrough innovation of enterprises.

Third, digital finance reduces the information asymmetry between firms and financial institutions. One of the essential functions of financial markets is to assume the role of information matcher between borrowers and lenders, and the key to lending and borrowing lies in the control of risk and credit. According to the information asymmetry theory, compared with the enterprises themselves, the financial sector needs a higher degree of understanding of the credit and risk information of the enterprises. The breakthrough innovation activities are characterized by significant investment, long cycles, and high uncertainty of the results, leading to enterprises facing more significant risks. When the traditional financial sector predicts that enterprises face more significant uncertainty risks, it is often reluctant to conduct a detailed assessment of the capital return on the output of breakthrough innovations, leading to a reduction in the willingness of financial institutions to lend to enterprises and the number of loans. Moreover, digital finance, relying on information technology and big data technology, can dynamically monitor enterprise behavior, capture enterprise behavior data promptly and effectively integrate it, quickly match information between different subjects, and deeply understand and master enterprise risk information [ 22 ]. On this basis, digital finance establishes a third-party credit system, conducts a more accurate credit evaluation of enterprises [ 23 ], reduces information asymmetry, enhances the willingness of financial institutions to lend money and the amount of money, and lays the financial foundation for corporate breakthrough innovation.

It can be seen that digital finance can play the role of a financing platform by increasing the supply of financial resources, improving the efficiency of financial resource allocation and reducing the information asymmetry between enterprises and financial institutions, thus promoting corporate breakthrough innovations. Therefore, this paper proposes the hypothesis1 as follows:

• H1: Digital finance can promote corporate breakthrough innovation by acting as a financing platform.

2.2 Social networking platform attribute of digital finance and corporate breakthrough innovation

From the perspective of expanding the social networks, which is the sum of a series of strong and weak social relationships owned by the top management of an organization [ 24 ], according to the theory of “embeddedness”, all the innovative activities of an enterprise are embedded in the social networks in which it is located. Since breakthrough innovation needs to be based on new heterogeneous knowledge [ 12 , 13 ], according to social networks theory, social networks can provide channels and paths for knowledge exploration. Moreover, digital finance not only has the attribute of a financing platform but also has the attribute of a social platform [ 11 ], which can broaden the social networks of enterprises, strengthen the strong social relations of the enterprise and develop the weak social relations of the enterprise, so that the enterprise can more conveniently carry out the exploration and acquisition of knowledge, and then promote the enterprise to carry out breakthrough innovation.

First, strong social relations refer are those multiple social relations based on trust and emotion, where transferring information and resources between networks subjects is more efficient [ 25 ]. Using digital payments and digital finance requires enterprises to transact financial assets that require a high level of security through the Internet, which increases trust in society and strengthens solid social relations [ 26 ]. Strong social relationships can increase the level of knowledge exchange and sharing among networks subjects, which helps enterprises obtain critical information about technological changes in the industry and market demand, thus giving rise to new ideas and technologies and laying the knowledge base for breakthrough innovation [ 27 ]. In addition, solid social relations can also shorten the path of innovation resource transfer so that enterprises with solid social relations can obtain relevant innovation knowledge promptly and gain a first-mover advantage in information, which helps to enhance the willingness and motivation of breakthrough innovation.

Second, a weak social relationship refers to a single relationship based on business, a non-redundant social relationship in which there is a high degree of heterogeneity in knowledge and information among networks subjects [ 17 ]. Digital finance is not only a financing platform that provides convenience for participants in financial activities but also a social platform that promotes collaboration between enterprises and other social subjects. Decentralized models such as the “fan economy” can help enterprises continuously expand their social networks, which contributes to weak social relationships [ 17 ]. Weak social relations can provide a bridge for network subjects with different knowledge, experience and cultural backgrounds to share and communicate [ 17 ], which facilitating knowledge transfer and technology exchange between enterprises and other enterprises, acquires heterogeneous information and knowledge different from the existing knowledge base, and promotes the generation of new knowledge and technology, thus facilitating corporate breakthrough innovation. In addition, weak social relationships have greater openness, more opportunities for cross-border exchanges, and lower knowledge acquisition costs, which can encourage enterprises to search for more partners and acquire more heterogeneous knowledge, thus helping to generate new ideas and promote breakthrough innovation.

It can be seen that digital finance can play the role of a social network platform by strengthening the solid social relations of enterprises and expanding the weak social relations of enterprises, thus promoting enterprises to carry out breakthrough innovation. Therefore, this paper proposes hypothesis H2 as follows:

• H2: Digital finance can promote corporate breakthrough innovation by acting as a social networking platform.

3. Methodology

3.1 sample selection and data sources.

This paper selects A-share listed companies in Shanghai and Shenzhen from 2011 to 2022 as samples to study the impact of digital finance on the breakthrough innovation of enterprises, and screens the data in accordance with the following criteria: (1) compared with other industries, the financial industry is relatively special in its business activities, and the preparation of financial statements is quite different from that of enterprises in other industries, therefore, the samples of listed companies in the financial industry are excluded; (2) To avoid the influence of abnormal data of ST and PT companies, the samples of ST, *ST, and PT companies are excluded; (3) Excluding the samples with missing values for key variables. A total of 18179 observations are obtained after screening. Meanwhile, in order to avoid the influence of sample outliers, continuous variables are subjected to Winsorize shrinkage at 1% and 99% quantile.

The patent classification data used in this paper are from the China Economic and Financial Database (CCER), the data on the number of patent applications are from the China Research Data Service Platform database (CNRDS), the data on digital finance are from the China Digital Inclusive Finance Index (provincial level) published by the China Center for Digital Finance Research of Peking University, and the data on company financials, corporate governance, and provinces are from the database of the CSMAR.

3.2 Variables

Dependent variable..

Independent variable.

The independent variable is Digital finance (Index), Drawing on the studies of Xue and Zha [ 31 ] and Wang and Liu [ 32 ], this paper takes the Digital Inclusive Finance Index of Chinese Provinces published by the China Digital Finance Research Center of Peking University (from now on referred to as the Peking University Digital Finance Index) as a proxy variable for digital finance, and logarithmizes the index.

Theoretically, digital finance is a multidimensional concept involving multiple indicators of different dimensions. The Peking University Digital Finance Index not only takes into account the population and geography covered by digital finance but also the depth of its use while also taking into account horizontal comparability at the regional level and vertical comparability in the time dimension from a dynamic perspective, so that the Peking University Digital Finance Index is better able to measure the degree of development of digital finance. Peking University Digital Finance Index covers 33 specific indicators in three dimensions: coverage, depth, and digitization. Among them, the coverage reflects the extent to which digital finance ensures that users get corresponding financial services, including account coverage rate, payment, and money fund; the depth reflects the actual use of digital financial services by users, including credit, insurance, investment, and credit; and the digitization reflects the advantages of low-cost and low-threshold advantage of digital financial services, including mobility, affordability, credibility, and Facilitation [ 33 ]. The details are shown in Table 1 .

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https://doi.org/10.1371/journal.pone.0307737.t001

Control variables.

This paper controls for a number of variables that may affect firms’ breakthrough innovations, Firm size (Size): measured using the natural logarithm of firms’ total assets; Gearing (Lev): measured using the ratio of total liabilities to total assets; Return on net assets (Roe): measured using the ratio of net income to the average balance of equity interest; Growth (Grow): measured using operating income growth rate; Current ratio (Flow): measured by the ratio of current assets to current liabilities; Asset liquidity (Liqui): measured by the ratio of current assets to total assets; Equity concentration (Top1): measured by the proportion of shares held by proxy shareholders; Two positions in one (Dual): if the chairman of the board of directors and the general manager are held by the same person, it takes the value of 1, otherwise, it takes the value of 0; Region level of economic development (Deve): measured using the natural logarithm of per capita GDP by province, and controlling for year (Year) and industry (Industry) fixed effects. Specific variable definitions are detailed in Table 2 .

https://doi.org/10.1371/journal.pone.0307737.t002

3.3 Model definition

Table 3 reports the descriptive statistics of the variables. The results show that the minimum value of the degree of dispersion of patent distribution of enterprises is 0.000, the maximum value is 1.000, and the standard deviation is 0.340, indicating that there are large differences in the degree of dispersion of patent distribution of the sample enterprises, with some enterprises exploring in more technological fields, with patents involved in more dispersed fields, and some enterprises exploring in only one or a few technological fields. The mean value of the number of enterprise invention patent applications is 2.220, the median is 2.197, the minimum value is 0.000, the maximum value is 6.236, and the standard deviation is 1.420, which indicates that at least half of the enterprises in the sample did not reach the mean value of the number of invention patent applications of the sample enterprises, and there is also a big difference in the number of invention patent applications of sample enterprises, which indicates that the breakthrough of Chinese enterprises innovation level is low, and the quality of enterprise innovation needs to be improved. The minimum value of digital finance is 3.426, the maximum value is 6.071, and the standard deviation is 0.550. The digital finance index of the province with the highest level of digital finance development is about 11 times higher than that of the province with the lowest level of digital finance development, which indicates that there are large differences in the level of digital finance development in different provinces.

https://doi.org/10.1371/journal.pone.0307737.t003

3.4 Correlation coefficients

Table 4 reports the correlation coefficients between the variables. The results show that the correlation coefficients between digital finance and the degree of dispersion of enterprise patent distribution and the number of enterprise invention patent applications are both significantly positive, indicating that digital finance can promote enterprises to explore in more technological fields and the quality of the patents they apply for is higher, which preliminarily proves the research hypotheses of this paper, H1 and hypothesis H2.The correlation coefficients between the control variables are all less than 0.7, which indicates that there is no serious multicollinearity.

https://doi.org/10.1371/journal.pone.0307737.t004

4. Empirical analysis

4.1 baseline regression analysis.

Table 5 reports the regression results of the model (2). The first two columns present the regression results of digital finance on the degree of decentralization of firms’ patent distribution. Column (1) is the regression result without controlling the variables that can affect both digital finance and the degree of patent distribution dispersion, while column (2) is the regression result with the addition of control variables, and the regression coefficients of digital finance on the degree of patent distribution dispersion of firms are all positive and significant at the 1% confidence level. The last two columns are the regression results of digital finance on the number of enterprise invention patent applications. Column (3) is the regression result without controlling variables that can affect digital finance and the number of invention patent applications at the same time, and the regression coefficients of digital finance on the number of enterprise invention patent applications are positive and significant at the 1% confidence level. Column (4) is the regression result of adding control variables, the regression coefficient of digital finance on the number of enterprise invention patent applications is positive and significant at 5% confidence level. The regression results in Table 4 show that digital finance can not only encourage enterprises to explore in more technological fields, but also the quality of patent applications is higher, digital finance can promote enterprises to carry out breakthrough innovation, and the research hypothesis H1 and hypothesis H2 is proved.

https://doi.org/10.1371/journal.pone.0307737.t005

Among the control variables, the regression coefficients of enterprise size on the degree of patent distribution dispersion and the number of invention patent applications are all significantly positively correlated at the 1% confidence level, indicating that the larger the enterprise, the higher the level of risk-taking, the easier it is to explore in a variety of technological fields, the greater the number of invention patents, and the higher the level of breakthrough innovation. The regression coefficient of gearing ratio on the number of invention patent applications of enterprises is significantly negative at 1% confidence level, indicating that the higher the gearing ratio is, the higher the long-term debt repayment pressure of enterprises, and the enterprises will reduce the breakthrough innovation behaviors in order to avoid risks. The regression coefficients of return on net assets on the degree of patent distribution dispersion and the number of invention patent applications are significantly positive at 1% confidence level, indicating that the higher the efficiency of the enterprise in utilizing its own capital, the easier it is to carry out breakthrough innovation. The regression coefficients of enterprise growth on the degree of patent distribution dispersion are significantly negative at 1% confidence level, and the regression coefficients of the number of invention patent applications are significantly positive at 5% confidence level, indicating that the higher the growth of the enterprise, the less likely to expand the field of technology, and the more likely to deepen the existing technology and improve the quality of innovation. The regression coefficients of asset liquidity on the degree of patent distribution dispersion and the number of invention patent applications are both significantly positive at the 1% confidence level, indicating that the more liquid assets, the more likely that enterprises will carry out breakthrough innovation. The regression coefficients of the shareholding ratio of the first major shareholder on the degree of patent distribution dispersion are positive but not significant, and the regression coefficients of the number of invention patent applications are significantly negative at 1% confidence level, which indicates that the higher the shareholding ratio of the first major shareholder is, the stronger the motivation of the major shareholder to infringe on the interests of the minority shareholders, and the more unfavorable it is for the enterprise to improve the quality of innovation.

4.2 Endogeneity test

4.2.1 instrumental variables approach..

Since breakthrough innovation is a firm-level behavior and digital finance is a provincial-level variable, it is less likely that firms’ breakthrough innovation will have a reverse causal effect on digital finance, but there may still be a problem of correlation between the main explanatory variables and the disturbance term. This paper addresses this endogeneity issue with the help of instrumental variables approach.

Referring to Jiang et al. [ 36 ], Wang and Guo [ 37 ], and Qu and Zhu [ 38 ], this paper uses Internet penetration (Internet) in each province as an instrumental variable for digital finance [ 39 ]. The selection of instrumental variables must satisfy the two conditions of relevance and exogeneity. Specifically, in this paper, the instrumental variables should be related to digital finance without direct correlation with the breakthrough innovation of enterprises. On the one hand, the development of digital finance cannot be separated from the popularization and application of the Internet. The Internet provides conditions for financial institutions to apply digital technologies such as big data and cloud computing, which can effectively promote the development of digital finance, so the Internet penetration rate as an instrumental variable of digital finance satisfies the relevance condition [ 36 , 37 ]; on the other hand, Internet penetration influences the behavior of enterprises in a longer path, and thus Internet penetration is unlikely to directly affect the corporate breakthrough innovation. Therefore, Internet penetration as an instrumental variable of digital finance satisfies the condition of exogeneity [ 38 ]. The P-value of Hausman test for the exogeneity test is 0.0210, which rejects the original hypothesis that all the explanatory variables are exogenous, suggesting that the model is indeed endogenous and suitable for the endogeneity test using the instrumental variable method. The Kleibergen-Paap rk LM F-value of the unidentifiable test is 1625.839, which is greater than the critical value of 10, rejecting the original hypothesis of unidentifiable. The Cragg-Donald Wald F-value of the weak instrumental variable test is 2184.423, which is greater than the critical value of 10, rejecting the original hypothesis that the instrumental variables are weakly instrumental variable. Thus, it proves that the Internet penetration as a digital instrumental variable of finance is valid.

The test results of the two-stage least squares (2SLS) regression with Internet penetration as the instrumental variable are shown in Table 6 . Column (1) shows that the regression coefficient of Internet penetration on digital finance is significantly positive, which meets the correlation requirement of instrumental variables; column (2) and column (3) show that the regression coefficients of digital finance on the degree of dispersion of enterprise patent distribution and the number of invention patent applications are both significantly positive at the confidence level of 1%, which indicates that after the endogeneity test of the instrumental variable with Internet penetration, the positive effect of digital finance on enterprises’ breakthrough innovation is still significant. After the endogeneity test of the variables, the positive effect of digital finance on promoting breakthrough innovation by enterprises is still significant, indicating that the previous benchmark regression results have good robustness.

https://doi.org/10.1371/journal.pone.0307737.t006

4.2.2 Control other possible missing variables.

First, financial development can reduce monitoring costs, weaken principal-agent problems, improve the availability of external financing, and have an impact on firms’ technological innovation. Therefore, the impact of digital finance on firms’ breakthrough innovation may be due to differences in regional financial development levels. In order to alleviate the endogeneity problem caused by possible omitted variables, this paper controls for the level of financial development in each province to test the previous benchmark regression again. In this paper, the level of bank development in each province is used as a proxy variable for the level of financial development in each province and is included in the control variables of the benchmark regression model (2). Among them, the level of bank development in each province is measured by the financial related ratio (Bank) and financial depth (Loan), with the financial related ratio being the ratio of the sum of deposit and loan balances of financial institutions to GDP, and the financial depth being the ratio of loan balances of financial institutions to GDP.

Second, while controlling for industry-and-year-fixed effects in the previous section, some characteristics of a firm’s province may also impact corporate breakthrough innovation. Although we control for province-level variables (Deve, Bank, Loan), there may still be some unobservable variables that can affect corporate breakthrough innovation. Therefore, this paper further controls for province-fixed effects and their joint fixed effects with industry. In addition, to control for the effects of unobservables that do not vary with industry and time, this paper also controls for industry and year joint fixed effects.

The regression results after controlling for other possible omitted variables are shown in Table 7 . The first two columns report regression results controlling for the level of financial development in each province, and the regression coefficients of digital finance on corporate breakthrough innovation are both significantly positive at the 1% confidence level. The last two columns report regression results controlling for province-fixed effects and their joint fixed effects with industry and joint fixed effects with industry and year, and the regression coefficients of digital finance on corporate breakthrough innovation are positive. The regression results controlling for other possible omitted variables are generally consistent with the previous benchmark regression results, indicating that digital finance can still play a positive role in corporate breakthrough innovations after controlling for factors at the province level that may affect corporate breakthrough innovation. It proves the robustness of the findings of the benchmark study in this paper.

https://doi.org/10.1371/journal.pone.0307737.t007

4.2.3 Control characteristics of the technical field.

Byun et al. argued that the number and concentration of a firm’s technological fields may impact its technological spillovers, which may affect its breakthrough innovations [ 12 ]. For this reason, referring to Byun et al. [ 12 ], this paper includes the number of fields covered by patents filed by firms (Techn) and their concentration (HHI) as control variables in the model (2).

Table 8 shows the regression results controlling for the characteristics of technological fields. The first two columns are regression results controlling for the number of fields covered by the patents applied by enterprises. The last two columns are regression results controlling for the concentration of technological fields covered by the patents applied by enterprises. The coefficients of digital finance on corporate breakthrough innovations are significantly positive, which is in line with the baseline regression results, indicating that the conclusions of this paper’s research are robust.

https://doi.org/10.1371/journal.pone.0307737.t008

4.3 Robustness tests

4.3.1 tobit regression..

From the previous descriptive statistical analysis, it can be seen that the degree of patent distribution dispersion and the number of invention patent applications are all greater than 0, and there are data that are zero. The breakthrough innovation indicators show the phenomenon of zero-value accumulation, and the regression with OLS model may have some bias. Therefore, this paper re-regresses the benchmark model (2) with the Tobit model.

The regression results using the Tobit model are shown in the first two columns of Table 9 , the regression coefficients of digital finance on the degree of patent distribution dispersion and the number of invention patent applications are significantly positive at least at the 5% confidence level, which is consistent with the previous benchmark regression results, indicating that there is a positive effect of digital finance on the breakthrough innovations of enterprises regardless of whether the OLS model or the Tobit model is used. The main conclusions of this paper are not affected by the choice of regression model, and the regression results are relatively robust.

https://doi.org/10.1371/journal.pone.0307737.t009

4.3.2 Independent variable lagged one period.

Although there is unlikely a reverse causality endogeneity problem of digital finance on corporate breakthrough innovations, there may be a certain lag in the promotion of digital finance on corporate breakthrough innovations due to the long breakthrough innovation cycle. Drawing on Xie and Wu [ 5 ] and Xue et al. [ 31 ], this paper regresses digital finance one period lagged.

The regression results of the independent variable lagged one period are shown in the last two columns of Table 9 . The regression coefficient of digital finance on corporate breakthrough innovation is significantly positive at the 1% level, which is consistent with the benchmark regression results, indicating that this paper’s research conclusions have good robustness.

4.3.3 Substitution of variable measures.

This paper further employs the method of replacing the measurement of variables for robustness testing. First, the measure of digital finance is changed by normalizing the digital finance index (Index_Normal) and regressing the benchmark model (2).

The regression results of replacing the measure of digital finance are shown in columns (1) and (2) of Table 10 , where the regression coefficients of digital finance on the degree of patent distribution dispersion and the number of invention patent applications are significantly positive at least at the 10% confidence level, which is consistent with the previous benchmark regression results, suggesting that replacing the measurement of the digital finance variable does not change the results of the baseline regression and that the conclusion that digital finance drives firms to breakthrough innovation is robust.

https://doi.org/10.1371/journal.pone.0307737.t010

Second, this paper also adopts the method of changing the way of measuring the variables of corporate breakthrough innovation for robustness testing. Referring to the common practice in the current literature, this paper adopts the number of citations of the enterprise’s authorized patents (Citation) and the number of the enterprise’s patents entering the second-level classification (Kind) as the proxy variables for the enterprise’s breakthrough innovation [ 40 , 41 ], respectively. Among them, the specific calculation of the number of citations of the enterprise’s authorized patents. The number of patent citations can reflect the technical importance of a firm’s innovations, and patents with high citations usually represent path-breaking critical innovations [ 42 ]. The number of enterprise patents entering the second classification level is calculated as the natural logarithm of the number of enterprise patents crossing the second level of IPC classification. The number of patents entering the secondary classification reflects the number of technological fields the firm enters. If a firm enters more technological fields, it indicates that it creates new knowledge with low relevance to the stock of knowledge. Therefore, these two indicators can also better measure corporate breakthrough innovation. In addition, referring to Byun et al. [ 12 ], this paper also adopts technology proximity (Techp) and patent citation ranking (Cita90) as proxy variables for breakthrough innovation. Technological proximity is the proximity between the technological field covered by a firm’s new patent application and the technological field covered by existing patents, reflecting the extent of the firm’s deviation from technological research. The larger the value of technological proximity, the smaller the degree of breakthrough innovation of the enterprise. Patent citation ranking refers to the number of patents in the top 10% of citation distribution among all patents applied by an enterprise in that year and the total number of patents applied by the enterprise in that year, reflecting the degree of recognition of patents. The larger the value of patent citation ranking, the higher the degree of breakthrough innovation of the enterprise.

The regression results of replacing the measurement of corporate breakthrough innovation variables are shown in columns (3) and (6) of Table 10 . The coefficients of digital finance on the number of citations of enterprises’ licensed patents is significantly positive at the 1% confidence level. The coefficients of the number of enterprises’ patents entering the second level of classification is significantly positive at 5% confidence level, the coefficients of the technology proximity are significantly negative at the 5% level, and the coefficients of the ranking of patent citations are significantly positive at the 10% level, which is consistent with the baseline regression results, indicating that replacing the measurement of breakthrough innovation variables will not change the results of the baseline regression, and the previous findings are robust. In summary, whether replacing the measure of digital finance or replacing the measure of firms’ breakthrough innovation, the regression results are consistent with the benchmark regression results, suggesting that the finding that digital finance drives firms to engage in breakthrough innovation is well robust.

5. Mechanism analysis of financing constraints and social networks

The regression results of the mechanism analysis of the role of digital finance on corporate breakthrough innovation are shown in Table 11 . The mechanism variable in columns (1) and (2) is financing constraint, and the regression coefficients of the interaction term between digital finance and financing constraints are significantly negative at the 10% and 1% levels, respectively, which indicate that digital finance can promote enterprises to make breakthrough innovations by alleviating financing constraints. The mechanism variable in columns (3) and (4) is social networks, and the regression coefficients of the interaction term between digital finance and social networks are significantly negative at the 5% and 1% levels, respectively, indicating that digital finance can promote corporate breakthrough innovation through expanding social networks.

https://doi.org/10.1371/journal.pone.0307737.t011

6. Further analysis

6.1 different dimensions of digital finance.

This paper uses the Digital Inclusive Finance Index of each province released by the Digital Finance Research Center of Peking University as a proxy indicator of digital finance in each province. Based on the data of Ant Gold Service transaction accounts, the Digital Inclusive Finance Index synthesizes the characteristics of traditional financial services and Internet services, and portrays the level of China’s digital finance development in three first-level dimensions: breadth of coverage, depth of use, and degree of digital support services. Among them, the breadth of digital financial coverage mainly examines the coverage of digital finance from three aspects: the number of Alipay accounts, the proportion of Alipay-bound cards, and the number of bank cards bound to each Alipay account; the depth of use of digital finance measures the actual use of digital finance from the aspects of payment business, insurance business, and money fund services; the degree of digital support services examines the degree of digitization of digital finance in terms of mobility, convenience, affordability and creditworthiness, and is a concentration of Internet technology in traditional financial services. The breadth of digital finance coverage is a precondition, the depth of use reflects the actual use of digital finance, and the degree of digital support services can be regarded as a potential condition. In order to investigate whether the three dimensions of breadth of coverage, depth of use and degree of digital support services have differentiated impacts on breakthrough innovations of enterprises, this paper replaces the digital finance indexes in the baseline model (2) with the breadth of coverage index (Cover), the depth of use index (Usage), and the degree of digital support services index (Digit), respectively, to further test the impacts of the breadth of coverage, depth of use and degree of digital support services on breakthrough innovations of enterprises.

The regression results of the breadth of digital financial coverage, the depth of use and the degree of digital support services on enterprise breakthrough innovation are shown in Table 12 . The regression coefficients of the breadth of digital financial coverage on the degree of dispersion of enterprise patent distribution and the number of invention patent applications are significantly positive at the confidence level of 10% and 5% respectively, indicating that the breadth of digital financial coverage has a positive effect on the breakthrough innovation of enterprises, and the wider the scope of digital financial coverage, the more conducive to promoting breakthrough innovation of enterprises; the regression coefficient of the depth of use of digital finance on the degree of dispersion of enterprise patent distribution and the number of invention patent applications are both significantly positive at the confidence level of 1%. The regression coefficients of the number of applications are all significantly positive at the 1% confidence level, indicating that the depth of the use of digital finance can significantly promote the breakthrough innovation of enterprises, and the deeper the degree of the use of digital finance by enterprises, the more conducive to their breakthrough innovation; the regression coefficients of the degree of digital payment services on the degree of dispersion of the distribution of patents by enterprises and the number of applications for patents for invention are all negative but not significant, indicating that the degree of digital support services does not have a significant effect on the breakthrough innovation of enterprises. breakthrough innovation of enterprises does not have a significant effect. Further, in terms of the size of regression coefficients, the regression coefficient of the breadth of digital financial coverage on enterprise breakthrough innovation is smaller than the regression coefficient of the depth of digital financial use on enterprise breakthrough innovation. This indicates that the actual use of digital financial services by enterprises has a greater impact on their breakthrough innovation than the coverage of digital finance. This may be because the breadth of digital financial coverage focuses on the quantitative supply of digital financial services, while the depth of digital financial use focuses more on the effective demand for digital financial services. Therefore, although both the supply and the actual demand for digital financial services can significantly affect the breakthrough innovation of enterprises, the actual demand for digital financial services has a greater impact on the breakthrough innovation of enterprises, which suggests that only the actual use of digital financial services by enterprises can improve their innovation capability.

https://doi.org/10.1371/journal.pone.0307737.t012

6.2 Particular digital finance tools

In order to more accurately portray the impact of digital finance on corporate breakthrough innovation, this paper further deconstructs the digital finance indexes to explore how particular digital financial tools affect corporate breakthrough innovation in six dimensions: Payment, Insurance, Monetary, Investment, Credit, and Investigation, respectively.

The regression results of particular digital financial tools on corporate breakthrough innovation are shown in Table 13 . The regression coefficients of Payment, Monetary, and Credit on corporate breakthrough innovation are significantly positive at the 1% level, indicating that Payment, Monetary, and Credit are important tools for digital finance to promote corporate breakthrough innovation. The regression coefficient of Insurance on the degree of patent distribution dispersion of enterprises is significant at 1% level, and the regression coefficient on the number of invention patent applications of enterprises is positive but not significant; the regression coefficient of Investigation on the degree of patent distribution dispersion of enterprises is positive but not significant, and the regression coefficient on the number of invention patent applications of enterprises is positive at 1% level, indicating that digital finance can promote corporate breakthrough innovation to a certain extent through Insurance and Investigation. The regression coefficient of Investment on corporate breakthrough innovation is positive but insignificant, indicating that the Investment of digital finance does not show the promotion effect on corporate breakthrough innovation.

https://doi.org/10.1371/journal.pone.0307737.t013

6.3 Moderating effect

6.3.1 enterprises’ dependence on external financing..

The regression results of the effect of the degree of enterprise external financing dependence on the relationship between digital finance and enterprise breakthrough innovation are shown in Table 14 . The regression coefficients of the cross-multipliers of the degree of dependence on external financing on the degree of dispersion of patent distribution and the number of invention patent applications of enterprises are both significantly positive at the 1% confidence level, indicating that digital finance has a greater effect on the enhancement of breakthrough innovations of enterprises with a high degree of dependence on external financing.

https://doi.org/10.1371/journal.pone.0307737.t014

6.3.2 Competition in product markets.

Currently, several literatures have confirmed the existence of a significant effect of competition on firms’ innovation, for example, Arrow points out that as firms increase their degree of monopoly over the market, firms make profits through monopoly rather than through innovation, which reduces the firms’ incentives to innovate [ 52 ]; however, Aghion found that there is an inverted U-shaped relationship between the “flight effect” and the “Schumpeterian effect” of competition on corporate innovation [ 53 ].

China’s favorable innovation environment and development opportunities drive the incentive effect of market competition on enterprises’ investment in innovation. As market competition intensifies, enterprises’ financing costs, capital needs and cash flow sensitivity increase, endogenous financing capacity decreases, and reliance on external funding increases. Therefore, as market-based competition intensifies, the positive effect of digital finance on breakthrough corporate innovation will become more prominent. In addition, market competition can improve the quality of corporate information disclosure, which is conducive to the firm’s understanding and access to information about other firms’ relevant technological innovations and learning and borrowing, which will strengthen the positive effect of digital finance on breakthrough innovations of enterprises.

In order to test the impact of market competition on the relationship between digital finance and corporate breakthrough innovation, this paper adds product market competition (Comp, Epcm) and its interaction term with digital finance (Index*Comp, Index*Epcm) to the benchmark regression model (2). Among them, the degree of competition in the product market is measured by two indicators: the degree of competition in the industry (Comp) and enterprise market power (Epcm), the degree of competition in the industry (Comp) is measured by the number of enterprises in the industry, and the enterprise market power (Epcm) is measured by the "enterprise Lerner index—industry Lerner index of the industry to which the enterprise belongs to in the current year", controlling for the differences in the structure of the industry. Comp is measured by the number of firms in the industry, and Epcm is measured by the “firm Lerner index—industry Lerner index for the industry to which the firm belongs to in the current year”, controlling for differences in industry structure. Enterprise market power represents the bargaining power and market position of an enterprise, and the greater the market power of an enterprise, the weaker the degree of market competition it faces. Meanwhile, in order to avoid the influence of variable covariance on the regression results, the degree of competition in the digital finance and product markets is centralized.

The regression results of the influence of product market competition degree on the relationship between digital finance and enterprise breakthrough innovation are shown in Table 15 . Columns (1) and (2) show how the degree of industry competition affects the positive relationship between digital finance and enterprise breakthrough innovation. It can be seen that the regression coefficient of the interaction term between digital finance and industry competition on the degree of enterprise patent distribution dispersion is significantly positive at 1% confidence level. The regression coefficient for the number of invention patent applications of enterprises is significantly positive at the confidence level of 5%, indicating that the degree of industry competition can strengthen the positive effect of digital finance on enterprises’ breakthrough innovation. Columns (3) and (4) show how enterprise market power affects the positive relationship between digital finance and enterprise breakthrough innovation. It can be seen that the regression coefficient of the interaction term of digital finance and enterprise market power on the degree of enterprise patent distribution dispersion is significantly negative at the 1% confidence level, and the regression coefficient on the number of enterprise invention patent applications is negative but not significant. It shows that the smaller the market power of enterprises, the stronger the positive impact of digital finance on enterprises’ breakthrough innovation. Based on the regression results in Table 13 , the degree of product market competition can generally strengthen the promoting role of digital finance on enterprise breakthrough innovation. The higher the degree of product market competition, the more prominent the role of digital finance on enterprise breakthrough innovation.

https://doi.org/10.1371/journal.pone.0307737.t015

6.4 Heterogeneity analysis

6.4.1 the level of financial development..

Financial repression in China is at a high level, and the process of improvement is slow, which prevents financial demand from being effectively matched. The mismatch between the quantity and quality of financial services and the effective demand for financial is one of the key reasons why digital finance has been able to develop rapidly in China. Digital finance has upgraded and transformed traditional finance with the help of emerging digital technologies such as big data, cloud computing, and blockchain, and to a certain extent, it has exerted the "inclusive effect" of incremental supplementation [ 36 , 54 ]. Therefore, in regions where traditional finance is relatively weak, digital finance may play a greater role in facilitating breakthrough innovation for enterprises. On the other hand, digital finance is a form of financial services implemented by the traditional financial sector with the help of technology, and technological innovation is a potential driving force for the development of digital finance. However, at the same time, it can also bring financial risks and affect the financial system’s stability [ 55 ]. The contagious nature of financial risks may lead to further contagion in the capital market. In contrast, more developed capital markets are more risk-resilient, thus helping to mitigate the adverse effects of digital finance. Therefore, digital finance may play a greater role in facilitating breakthrough innovation for firms in capital markets with higher levels of development.

In order to test whether there is a differential impact of digital finance on breakthrough innovation of enterprises under different financial endowment conditions, this paper examines the level of development of traditional finance from two aspects: the banking sector and the capital market sector. Among them, the development level of the banking sector is measured by the ratio of the total loan size of each province to its GDP size [ 56 ]; and the development level of the capital market sector is measured by the ratio of the total market value of stocks outstanding at the end of the year to the total GDP of each province [ 57 ]. On this basis, the annual median of the level of development of the banking sector was used as a dividing criterion, and samples above the annual median were categorized into the group with a high level of development of the banking sector (Bank_High), and samples below the annual median were categorized into the group with a low level of development of the banking sector (Bank_Low); similarly, using the annual median of the level of development of the capital market sector as a dividing criterion, the sample above the annual median is classified as the group with a high level of development of the capital market sector (Market_High) and the sample below the annual median is classified as the group with a low level of development of the capital market sector (Market_Low). Subgroup regressions are performed for the baseline model (2).

The results of the grouped regressions of digital finance on firms’ breakthrough innovations under different financial endowments are shown in Table 16 . Panel A shows the impact of digital finance on firms’ breakthrough innovations under different levels of development in the banking sector. It can be seen that in the group with low level of development of banking sector, the regression coefficients of digital finance on the degree of dispersion of enterprise patent distribution and the number of invention patent applications are positive and significant at 1% confidence level, in the group with high level of development of banking sector, the regression coefficients of digital finance on the degree of dispersion of enterprise patent distribution and the number of invention patent applications are positive but insignificant, and the test of coefficient of difference between the groups shows that, no matter it’s the degree of dispersion of enterprise patent distribution or the number of invention patent applications, there is a significant difference of regression coefficients of digital finance at 5% confidence level between the two groups of samples with high and low level of development of banking sector. Panel B shows the impact of digital finance on firms’ breakthrough innovations under different levels of capital market sector development. It can be seen that the regression coefficient of digital finance on the degree of dispersion of firms’ patent distribution is significantly positive at 1% confidence level in the group with a high level of development of the capital market sector, and the regression coefficient of digital finance on the degree of dispersion of firms’ patent distribution is positive but not significant in the group with a low level of development of the capital market sector; the regression coefficients of digital finance on the number of invention patent applications filed by firms are significantly positive in both the high and low sample groups for the level of development of the capital market sector, but the test for the difference in the coefficients between the groups reveals that the regression coefficients of digital finance in the two sample groups are significantly different at the 5% confidence level.

https://doi.org/10.1371/journal.pone.0307737.t016

Combining the regression results of the grouping of digital finance on corporate breakthrough innovation under the conditions of different levels of development of the banking sector and the capital market sector, digital finance can play a greater role in corporate breakthrough innovation in provinces with a low level of development of the banking sector; however, in provinces with a high level of development of the capital market sector, digital finance plays a greater role in corporate breakthrough innovation. The lower the level of development of the banking sector and the higher the level of development of the capital market sector, the more room for digital finance to play a role. This suggests that digital finance has a gap-filling effect on the banking sector and an advantage-gaining effect on the capital market sector in promoting breakthrough innovation. This phenomenon may be because, on the one hand, digital finance can not only absorb more financial resources and transform them into effective supply with the help of digital technology [ 10 ], but also reshape the competitive landscape of the banking sector [ 58 ], promote the transformation and upgrading of the banking sector, and form an "incremental supplement" and "stock optimization" to traditional finance. Therefore, digital finance can play a greater role in regions with a low level of development of banking sector development. On the other hand, although digital finance relies on digital technology to realize the lack of traditional finance, technological innovation is also an important part of the source of financial risk [ 55 ]. The contagious characteristics of financial risk will cause this instability to be transmitted to the capital market. The perfect capital market has a stronger ability to withstand risk, which makes the higher level of development of the capital markets less affected by financial risk. Thus, digital finance can play a greater role in regions with higher capital market sector development levels.

6.4.2 Regional disparities.

China is a vast country with large differences in resource endowment and different levels of economic development between regions. The eastern region is at a higher level in terms of the quality of the institutional environment and the development of the capital market. Therefore, the uncertainty and risk of digital financial development in the process of universalization in the eastern region are lower, and the level of development is higher. However, on the other hand, due to the large space for development, the less developed regions in the central and western regions may be affected by digital financial development to a greater extent compared with the developed regions in the east. This shows that the academic community has not yet reached a consensus on the regional variability of the consequences of the impact of digital finance. In order to test whether there is regional variability in the impact of digital finance on the breakthrough innovation of enterprises, this paper divides the sample enterprises according to the region into the sample group of the eastern region (East), the sample group of the central region (Mid) and the sample group of the western region (West), and carries out a group regression on the benchmark model (2).

The regression results of the regional variability of digital finance in driving breakthrough innovation in firms are shown in Table 17 . The regression coefficients of digital finance on the degree of dispersion of enterprise patent distribution and the number of invention patent applications are significantly positive at the 1% confidence level in the sample group of the central region, and positive but not significant in the sample groups of the eastern region and the western region. The test of difference in coefficients between groups shows that the regression coefficients of digital finance on breakthrough innovation of enterprises are significantly different in the sample group of the eastern region and the sample group of the central region, as well as in the sample group of the central region and the sample group of the western region. It shows that there is regional variability in the positive effect of digital finance on breakthrough innovation of enterprises, and the development of digital finance in the central provinces has a greater role in promoting breakthrough innovation of enterprises. The possible reason is that the eastern region has a high degree of marketization, developed capital market and high level of financial development, enterprises face lower financing constraints, the level of innovation is higher, and the space for digital finance to play is relatively small; in the central region, relative to the eastern region and the western region, the degree of marketization, capital market and financial development level are at the intermediate level, enterprises face more serious financing constraints, the level of innovation is relatively insufficient, and digital finance can play a larger space; the western region has a low level of economic development, the degree of marketization, the capital market and the level of financial development are in an underdeveloped state, enterprises face serious financing constraints, the level of innovation is low, the space for digital finance to play should be greater. However, on the other hand, the role of digital finance cannot be separated from the support of financial infrastructure, institutional environment, human resources, etc., and the western region is still immature in these institutions and mechanisms, resulting in digital finance not playing its due role.

https://doi.org/10.1371/journal.pone.0307737.t017

6.4.3 Enterprise scale.

Financing constraints are essential to corporate breakthrough innovation, and enterprise scale can significantly impact financing constraints. Hottenrott and Peters [ 48 ] argued that financing constraints do not significantly affect the investment behavior of large-scale enterprises. In contrast, Cao et al. [ 59 ] pointed out that financing constraints constrain the innovation of small-scale enterprises. In order to test whether enterprise scale heterogeneity can have an impact on the facilitating effect of digital finance on corporate breakthrough innovation, this paper conducts a group regression of the benchmark model (2) by dividing the sample enterprises into a sample group of large-scale enterprises (Large) and a sample group of small-scale enterprises (Small) using the yearly median of the enterprise scale as a criterion.

The regression results of the enterprise scale heterogeneity of digital finance driving breakthrough innovation are shown in Table 18 . In columns (1) and (3), the regression coefficients of digital finance on breakthrough innovation of large-scale enterprises are significantly positive at the 1% level, and in columns (2) and (4), the regression coefficients of digital finance on breakthrough innovation of small-scale enterprises are positive but not significant. The between-group coefficient difference test shows that digital finance promotes breakthrough innovation in large-scale enterprises more significantly than in small-scale enterprises. This may be due to large-scale enterprises being more willing to explore new technological fields because they have a specific innovation base and a more vital risk-taking ability.

https://doi.org/10.1371/journal.pone.0307737.t018

7. Conclusions and implications

7.1 conclusions.

This paper takes A-share listed companies in Shanghai and Shenzhen from 2011 to 2022 as research samples to empirically analyze the impact effect and path of digital finance on breakthrough innovation of enterprises. The study finds that: (1) digital finance can promote breakthrough innovation of enterprises. The path test shows that digital finance promotes breakthrough innovation through alleviating financing constraints and expanding social networks. (2) There are differences in the impact of different dimensions of digital finance on the breakthrough innovation of enterprises, with the depth of the use of digital finance having the greatest impact on the breakthrough innovation of enterprises, the breadth of the coverage of digital finance having the second greatest impact on the breakthrough innovation of enterprises, and the degree of digital support services not showing any impact on the breakthrough innovation of enterprises. (3) The degree of enterprises’ external financing dependence and the degree of product market competition can strengthen the positive effect of digital finance on enterprises’ breakthrough innovation; the higher the degree of enterprises’ external financing dependence and the degree of product market competition, the greater the positive effect of digital finance on promoting enterprises’ breakthrough innovation. (4) The promotion effect of digital finance on breakthrough innovation of enterprises is heterogeneous in provinces with different levels of financial development; in provinces with a lower level of development of the banking sector and a higher level of development of the capital market sector, the promotion effect of digital finance on the breakthrough innovation of enterprises is greater; there are differences in the impact of digital financial development on the breakthrough innovation of enterprises in different regions; relative to the eastern and western regions, the impact of digital finance on the breakthrough innovation of enterprises in the central region is greater than that in the eastern and western regions. finance has a greater role in driving breakthrough innovation for firms in the central region.

7.2 Implications

In view of the above findings, the following policy insights are obtained: (1) In the context of the country’s active financial supply measurement reform, on the one hand, provinces and municipalities should continue to steadily promote the development of digital finance, actively play a role in optimizing the allocation of financial resources, improve the financing environment, alleviate the constraints on enterprise financing, enable digital finance to better serve the real economy, promote breakthrough innovations, and support the enterprises’ healthy and long-term development. On the other hand, enterprises should seize the golden period of the current development of digital finance, make good use of the social platform attributes of digital finance, expand their own social networks, strengthen cooperation with other enterprises, acquire heterogeneous knowledge and cutting-edge technologies, actively carry out breakthrough innovation activities, improve the quality of innovation and enhance innovation capability. (2) In encouraging the integration of IT and financial markets and promoting the development of digital finance, provinces and cities should, on the one hand, continue to expand the coverage of financial services, give full play to the inclusive nature of digital finance, try to eliminate discrimination in innovation financing, promote the equalization of financial resource allocation, create a fair, inclusive and open innovation environment, and unleash the vitality of enterprise innovation. On the other hand, on the basis of the expanding coverage of digital finance, the depth of digital financial use should be enhanced by popularizing financial knowledge, and the degree of digital support services should be deepened by supporting the combination of “Internet Plus” and the financial industry, so as to realize the coordinated development of digital finance in multiple dimensions. (3) To further improve and supplement the financial system, on the one hand, in areas with a low level of development of the banking sector, traditional financial institutions should actively embrace the development trend of digital finance, utilize digital technology to effectively screen enterprises, and give sufficient financial support to enterprises with strong innovation ability, so as to play the role of digital finance in supplementing the shortcomings of the banking sector; on the other hand, to comprehensively develop the capital market, improve the level of development of the capital market, and effectively play the role of the capital market in the development of the digital finance sector. On the other hand, comprehensively develop the capital market, enhance the development of the capital market, effectively utilize the advantageous gain effect of the capital market in the process of digital finance to promote enterprises to make breakthrough innovations, and help the implementation of the innovation-driven development strategy. (4) Reform the current financial regulatory system to balance the relationship between digital financial development, financial risks, and innovation in the real economy. On the one hand, regulators should implement sustained and focused policies to stabilize market expectations. On the other hand, the use of digital technology, artificial intelligence, and other scientific and technological means to build a regulatory technology system, to enhance the relevance, immediacy, and penetration of regulatory technology, to effectively guide digital finance to inject kinetic energy into the development of innovation, and to prevent financial risks and other chaotic phenomena that may be induced in the process of its development.

7.3 Limitations and future outlooks

Although this paper has some marginal contributions, there are still some limitations: (1) This paper explores the role mechanism of digital finance affecting breakthrough innovation of enterprises from the perspective of financing constraints and social networks, but there may be other role paths, and in the future, a more precise and specific theoretical analytical analysis framework can be established to more comprehensively understand the impact of digital finance on corporate breakthrough innovation. (2) This paper mainly examines the impact of digital finance on corporate breakthrough innovation, but the impact on firm value and core competitiveness has not yet been explored in depth, and in the future, the research on digital finance and corporate breakthrough innovation can be extended to comprehensively assess the positive effects of digital finance on micro-enterprises.

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Digital Finance Research and Developments Around the World: A Literature Review

International Journal of Business Forecasting and Marketing Intelligence, June 2022

25 Pages Posted: 27 Jul 2022 Last revised: 11 Jan 2023

Peterson K Ozili

Central Bank of Nigeria

Date Written: June 1, 2022

This paper presents a concise review of the existing digital finance research in the literature, and highlight some of the developments in digital finance around the world. The paper reached several conclusions. Firstly, it showed that digital finance has become an important part of modern finance and the major application of digital finance can be found in Fintech, embedded finance, open banking, decentralized finance, central bank digital currencies, among others. Secondly, it identified some international determinants of digital finance which includes the need for efficiency in financial service delivery, the need to achieve the United Nations sustainable development goals through the use of existing digital finance technologies, the need to increase financial inclusion through digital financial inclusion and the need for efficient payments. The review also finds that digital finance research is growing fast, and recent studies have investigated contemporary issues in digital finance that are relevant for policy and practice. Regarding the digital finance developments around the world, the paper shows that the Fintech and mobile money industries are the largest beneficiary of investments in digital finance with the total number of users of mobile money services surpassing 1 billion globally. Also, the paper predicts that the future of digital finance is to create a digital environment that permits the offering of all kinds of financial product and services that can be customized and personalized to meet the unique needs of all users on a single digital platform and without requiring any form of human assistance or intermediary. The paper then suggest some areas for future research which include the need for more research on how regulators can keep pace with emerging digital finance transformation, the need for more research on user information security and compliance, the need for more research on how to deal with bias caused by bad data, the need for more research on how to deal with algorithmic bias, and the need for more research on how to combine a risk-conscious culture with a higher risk appetite for digital finance transformation.

Keywords: Digital finance, artificial intelligence, machine learning, financial inclusion, fintech, access to finance, financial stability, economic growth, blockchain, central bank digital currency, robotics, cryptocurrency

JEL Classification: E44, F65, G18, G21, G28

Suggested Citation: Suggested Citation

Peterson K Ozili (Contact Author)

Central bank of nigeria ( email ).

Abuja Abuja, 09 Nigeria

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Digital financial inclusion: next frontiers—challenges and opportunities

• Original Research
• Published: 18 August 2021
• Volume 9 , pages 127–134, ( 2021 )

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• Chandra Mohan Malladi   ORCID: orcid.org/0000-0002-3377-4673 1 ,
• Rupesh K. Soni 1 &
• Sanjay Srinivasan 1  

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India’s Financial Inclusion journey has been phenomenal in the last decade and expressly promoted by the Government of India through their Digital India Movement & Pradhan Mantri Jan Dhan Yojana. Reduction of poverty and addressing the challenges of ensuring sustainable income could become a key factor to achieve an inclusive society. Information and Communication Technology are providing access to unbanked population progressively and helping to bring them into the banking segment. Digital Technologies are driving usage and making a positive impact on livelihood of citizens. In this paper we are discussing on what is achieved in Financial Inclusion so far and what next and how do we leverage and harness digital technologies to achieve an inclusive society. This paper enlists various challenges that continue to prevail in achieving an inclusive society. We have put forth recommendations on addressing the key challenges and qualified the importance of collaboration and transparency between all the key stakeholders to achieve an inclusive ecosystem.

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1 Hypotheses Development

How do we enhance the process of Digital Financial Inclusion? How can Information and Communication Technology help in providing the citizens with a sustainable livelihood and inclusive growth? How can we safeguard the people who are included in the FI Framework and guarantee that they will not be excluded again?

To achieve a financially inclusive society that is sustainable and promotes inclusive growth for all, we need to provide the citizens of the country with access to education, basic financial services, affordable healthcare & suitable way for upskilling and improving their talent. They should be brought inside the legal framework where they can sustain and thrive.

The high amount of disparity and digital divide between Urban & Rural areas in India must be eliminated and people must be educated financially and included socially. There must be a cohesive ecosystem where Financial, Social & Health Inclusion that can work in tandem to accomplish a sustainable inclusive society. India’s digital payment and rural infrastructure must be improved to ensure zero disruption and continual access to telecom networks. Access to line of credit must be provided with adequate last mile services to ensure service delivery.

2 Deployment Approach and Methodology

This research study used quantitative and qualitative data from various official sources such as websites of Reserve Bank of India, Niti Aayog, Direct Benefit Transfer, PM Jan Dhan Yojana and other information published officially by the Govt. of India and Ministry of Finance. The data points and facts visibly showcase the impact of Financial Inclusion so far in India and helps us understand the gaps that must be filled to improve growth and ensure sustainability.

Comprehensive secondary research from published journal articles and expert committee opinions were considered to understand Digital Financial Inclusion initiatives and details of the best practices followed in various geographies. By leveraging this information, we have identified the key problems preventing us to realize an inclusive society and we have provided with qualified recommendations to tackle this.

Inclusive society is well-defined in terms of Financial Inclusion, Social Inclusion & Health Inclusion. Consistent with this approach, we define our key dependent variables ‘finance’ —as the access to a line of credit, availability and usage of basic financial services, ‘social’ —access to education and literacy, improvement of skills, & ‘health’— Personal & Societal Wellness. From this, we can understand that we are deploying a self-reporting measure to evaluate our research findings and we have substantiated our recommendations with real world examples from other studies conducted in similar functions. Prior research also acknowledges the subjectivity of these self-reported measures of FI [ 24 ].

3 Introduction

Financial Inclusion (FI) means delivering basic financial services to the marginalised and excluded members of society. It is the process in which we ensure adequate line of credit accessible by the weaker section of the society at a reasonable cost. Financial inclusion helps in developing a culture of savings among semi urban and rural population by bringing low income groups within the formal framework of banking and insurance sector which is significant for national economic development. It came into prominence around 2008 when it became clear to the government that it needs to be the key driver for economic growth of the country. Vision for Financial Inclusion in India is to induce inclusive financial growth by including the unbanked and unsupported individuals and MSMEs by formal financial institutions by providing them convenient access to basic financial products including bank accounts, remittances, bill payments, government supported insurance, pension products and formal credit at reasonable costs. There has been a growing evidence on how financial inclusion has a multiplier effect in boosting overall economic output, reducing poverty and income inequality at the national level.

With the advent of “ Digital India Movement ” and telecom penetration to deep rural areas, sincere efforts are made to bring widespread formal banking channels and innovative financial technology together to create a viable and vibrant ecosystem to drive accessibility of formal financial products to unbanked and deprived segments of Indian society. We at TCS, started this journey very early for some of our partner banks, with the services related to opening of no-frills accounts, delivering smart cards containing balance and biometric information to registered on the card. There was no active network connectivity during initial stages of FI. Last mile agents used to visit the bank, withdraw money & beneficiary list, go to each beneficiary, authenticate with biometrics, and deliver the services. Post which, they go back to the bank to reconcile. Out of 650,000 villages in India, around 150,000 was identified by the govt. initially to service through BC Model [ 15 ].

Fast-forward now, there is far more online connectivity in the remotest areas, smart card is replaced by real time Aadhaar based authentication, beneficiary enrolment & transactions can be done in real-time in field. Last mile channels like micro ATMs, Kiosks, PoS machines, Tablets, Mobile Phones are utilised for service delivery. Basic requirement of UPI based FI transaction is that the beneficiary account should be opened through PM JDY scheme and it is linked to the customer’s mobile number. Banks started channelling UPI based transactions on opened bank accounts. As of 2019, little over 470 Mn (~ 34.47%) is urban population of India. However, more than 65% are in semi urban and rural areas where access to digital services is lesser than major cities [ 13 ].

There is a great need for inclusive growth. By leveraging digital technologies, this is a great opportunity for Govts. and market leaders to improve digital penetration, ease of use of digital products, contextualised and personalised offerings to citizens increase availability, drive down costs, enhance security and trust. There is a need for sustainable cooperation between govts., businesses and unbanked population [ 15 ].

National leadership and policy making institutions like RBI and Niti Aayog have brought in some strong initiatives for inclusive growth which culminated in National Mission for Financial Inclusion namely Pradhan Mantri Jan Dhan Yojana PM JDY leveraging banking network and technology innovations. It enabled access to financial services and coverage of banking to excluded population.

Till date over 344.3 Mn plus new accounts have been opened and a bunch of social and financial security products are offered to the account holders like entrepreneurial credit, financial advice, mortgage, loans and insurance, overdraft of ₹10,000, Accidental Death cum Disability Insurance (PMSBY), Term Life Cover under PMJJBY, Old Age Pension (APY scheme), PM Kisan, Educational Scholarships to students etc. [ 6 ].

With over 95% of Indian population having Unique Identification through Aadhaar, India achieved 80% of adult population having bank account by 2017. 77% Indian Women have bank accounts. In the outbreak of Covid-19 pandemic, this back bone of bank account has been instrumental to provide help of ₹500 per month for 3 months to over 200 Mn woman beneficiaries, transfer of ₹6000/- in 3 instalments per year (currently citizens are receiving their 8th instalment) of PM Kisan Samman Nidhi Yojana to farmers through direct benefit transfer schemes [ 10 ]. Under PM JDY, 423.7 Mn total no of Beneficiaries of which 279.5 Mn Semi Urban/ Rural Beneficiaries [ 24 ]. Rapid digital penetration along with enhancing the financial literacy of people has started. We are moving from assisted to self-service model for multiple services.

For almost all the public and private sector banks, TCS has provided its Financial Inclusion Solution Suite enabling end to end integration with their core banking systems (CBS) through its Branchless Banking Solution. With a wide range of services catalogue, TCS is delivering last mil services to over 150 + thousand locations. TCS has been the technology service provider (TSP) to DBT for various stake holders in which we are running a Heterogenous Technology System for money transfer. TCS is co-ordinating with multiple stakeholders in the DBT value chain such as Central & State Govts., banks & financial institutions in the country, RBI. DBT has proven to be critical in arresting leakage of govt. funds (~ ₹1700 Bn), eliminate involvement of middlemen in transactions, has capacity to cover a variety of areas, increase the number of beneficiaries (~ 770 Mn) and transactions and lower the distribution cost per transaction (Over 6 Mn Trnxs/day) [ 11 ].

Multiple technological solutions such as FI Platform, Beneficiary Registration Application, TCS BaNCS Enterprise Payments Hub, APBS (Aadhaar Payment Bridge System) Adaptor, TCS BaNCS CBS, Aadhaar Data Vault Solution were implemented by TCS and leveraged for end-end service delivery. RBI has played the guiding role which helped banks in achieving various objectives such as the introduction of MICR based cheque processing, Implementation of the electronic payment system such as RTGS (Real Time Gross Settlement), Electronic Clearing Service (ECS), Electronic Funds Transfer (NEFT), Cheque Truncation System (CTS), Mobile Banking System etc. [ 8 ].

Further to that, under the Digital India Movement, various digital payment methods—UPI, BBPS, IMPS, NETC, AePS, etc. were launched by NPCI, in coordination with RBI, some of which was run by TCS on behalf of RBI & NPCI. RBI’s working group reviewed the BC Model and suggested that BC agents or BF agents (Business Facilitator) can deliver last mile services in semi urban & rural areas. Individuals working as PCO Operators, Retired Teachers, Petrol Pump Owners, Grocery, Chemist & Fir Price Shop owners, NGOs, MFIs, SHGs linked to banked were authorised to act as last mile agents and provided a commission based on amount of services rendered [ 9 ].

There is a huge market for several financial institutions & other ecosystem players in the bottom of the pyramid by creating right products & services and ensures it reaches the intended customer [ 15 ]. TCS has been chosen as primary service provider for kiosk banking solution for many of the Customer Service points established by various Public Sector Banks (PSBs).

4 Current Challenges and Observations

People included in the Financial inclusive ecosystem end up getting excluded and are not able to sustain within the framework due to various reasons general or health related causes [ 1 ].

There is a clear demarcation of digital divide among—some are tech savvy people and delivering the services and making them understand is not difficult, where as some in semi-urban and majority of people in rural areas find difficult to understand and utilise technology efficiently [ 16 ].

Lack of financial literacy and awareness on financial cybercrimes has resulted in general mistrust among rural population which leads to reduced digital penetration [ 27 ].

There is a burden on running sustainable last mile delivery model, particularly in rural areas & last mile level service delivery. Multiple Govt. & Business agencies are trying to reach the same location for various reasons related to FI, Social or Healthcare inclusion and these are disjoint efforts and driving higher costs.

Different data elements available with govt. such as healthcare schemes data, social inclusion data, COVID data, vaccination data, etc. are not leveraged to full extent as there is clear lack of coherence between these data elements.

Last mile technological systems and artefacts are vulnerable to exposure and exploitations. It is loosely handled by BC or BF agents as adequate security measures to control it are not put in place. This has resulted in lot of frauds happening on the ground. About 22% BC agents faced fraud in 2017, a noteworthy increase from 2% in 2015 [ 17 ]. Business model of Last mile & BC Agent network must be looked at again from privacy security & safety angle.

Data Privacy is still a major concern as a lot of captured data is easily available to various stakeholders as PII norms are not completely followed. KYC Data & mobile numbers are available everywhere.

Biometric data is captured duplicitously by some BC Agents in clay who will replicate it later for fraudulent reasons.

Another way is when they give a manual receipt instead of computerised one during transactions.

SMS messages for transactions in an account are not reaching the customer due to lack of mobile device (More than 310 Mn people still do not possess a basic feature phone or a smart phone) or financial institutions are not sending these messages for low value transactions. This has led to increased dependency on local agents.

Access to credit is still a concern as small time lenders charging high rate of interest are prevalent in rural areas. Govt. schemes have not penetrated fully and need more rural outreach to enhance credit access [ 15 ]. Lack of avenues for digital lending and online loans from credible financial institutions is missing.

Recommendations for individuals based on their requirement is not provided and leveraging the personalised data of the person, by performing analytics using AI & ML, banks can offer loans, insurance and other services based on analytics & credit score [ 15 ].

5 National Strategy for Financial Inclusion

In the year 2020, RBI came up with national strategy for Financial Inclusion with focus on creating an outreach of financial services outlets to provide banking access to every household within 5KM radius. All eligible adults must have access to basic financial services such as Bank Account, line of credit, both life and other insurance, pension scheme and suitable investment product. Now, the next paradigm for financial inclusion program (2020–2024) is focused addressing inherent behavioural and practical aspects [ 22 ].

A strong financial transaction grievance redressal system to address concerns of arguably less technology savvy citizens.

Increasing digital penetration as still the smartphone usage for financial transactions are limited to urban and semi urban population predominantly.

Bank account opening for the remaining population of the country as still the PMJDY penetration is about 80% of the population.

Ensuring the privacy of data and information of citizens and prevention of fraudulent transactions and demographic data.

Easy and affordable digital payment options to suit the needs of small businesses and unstructured sector workers.

Providing access to basic and most essential financial products such as transactional accounts, digital payments, basic term insurance, basic medical insurance, and pension options to the population specially in the agricultural and unorganized MSME sector workers.

Acc. to a World Bank report, globally achieving Universal Financial Access by 2020 [ 3 ] has been one of the key developmental agenda of the World Bank which aims to provide adults who currently aren’t part of the formal financial system, with access to a transaction account to store money, send and receive payments to manage their financial lives. Our National Strategy is also aligned to these broad virtues suggested by World Bank. On key parameters, India is quite ahead and continuously progressing:

Leadership in India is having singular focus on technology enabled financial inclusion. It is evident through steps like DBT, PM Kisan, financial assistance to woman and poor during the recent Covid-19 pandemic etc.

Target based approach for specific sectors & regions including “National Mission for Capacity Building” by bankers for MSME sector, Certified Credit Counsellor Scheme for MSME to join them with the formal Financial Channels and informed financial credit decisions.

Regulatory Framework in Banking to protect customers, promote fair business processes and prevent unhealthy practices by market players. Initiatives like exclusive “Financial Inclusion Fund” (with initial corpus Rs.2000 Crore), issuances of differentiated banking license—Small Finance Banks, Payments Banks etc., launch of BC Registry with Indian Banks Association (IBA) etc. are steps towards the same.

Market Development initiatives like Branch Authorization Guidelines (2017) etc. to ensure accurate targeting of the beneficiaries, de-duplication and reduction of fraud and leakage have been taken. Linking all financial assistance schemes to DBT is a strong footprint in this direction

Strengthening Payments Structure through digital retail payments systems like AEPS, NACH, UPI, CTS, IMPS etc. operated by NPCI are significant steps. Aadhaar linked direct benefit transfer has changed the scenario for public funds distribution in India.

Last mile delivery to bridge the gap for remote connectivity and doorstep financial services is key to success. ICT based solution like business correspondents/ facilitators and IPPB are landmark steps in this area, launch of UPI on features phones will be a big game changer also enabling ecosystem for NFC based touch less payments.

Financial Literacy and Awareness is a primary bottleneck in progressive financial inclusion in India. Launch of financial literacy program in 2013 helped in addressing this to some extent.

6 Sustainability through Comprehensive Inclusion

An inclusive society helps sustain socioeconomic development and understanding the correlation between Financial Inclusion, Social Inclusion & Health inclusion helps sustainability. Having taken the right initiatives to ensure wider coverage of Financial Inclusion, it is now time to look at the rationalization of the inclusive society by leveraging iterative technology and other two key aspects—Social Inclusion (Education, Literacy, Skill), Health Inclusion (Personal & Societal Wellness).

FI implemented in a standalone ecosystem may not be enough to achieve. FI must be complemented by Social and Health Inclusion through improving skillset, education, physical and mental well-being to ensure a sustained livelihood [ 12 ]. Current model has a major short-coming. If there is a functionality lapse in any single inclusion, someone may fall out of the inclusive ecosystem.

We need to ensure that whoever is excluded financially is brought into the fold again and has all the necessary tools to sustain within the ecosystem.

To handle this, we need to focus on increasing the digital penetration and continue the account opening process for all citizens. FI Ecosystem must aim to work in tandem with Healthcare Inclusion & Education Inclusion ecosystem to ensure well-being of people and educate the citizens financially. The technological initiatives under ‘JAM Trinity’, that is, PM Jan Dhan Yojana, Aadhaar and increased Mobile Phone & internet usage had led to 355 Mn accounts opened in the last 5 years (Figs. 1 , 2 ).

Current State in India

Desired State in India

Technology should drive the recommendations to every individual to ensure social, health and fin. Inclusion. Cross Leveraging of existing and new citizen databases to provide strategic Analytics & insights to the deciding authorities.

Blockchain could prove to be a gamechanger in enhancing the value chain securely without any duplications of efforts [ 23 ]. There following measures could be taken to improve the living standard of citizens using ICT technology to deliver last mile services [ 19 ]. They are,

Fix technological breakdowns and connectivity issues and ensure wider coverage in remote areas

Facilitate a hassle-free digital experience for new users

Enhance digital security standards to improve the confidence of citizens to make digital transactions

Finetuning limits on daily transactions and commissions on low value withdrawals & deposits

Make changes to the minimum balance criteria in SB Accounts

Delivery services at BC points through Controlled devices for better safety and security for end users

People should be educated and learn to protect themselves against financial cybercrimes. Provide profile wise recommendations and better offers for people by leveraging Analytics, AI & ML using the data gathered from available official databases. For ex., through COVID Patient DB, recommendation for vaccination, availability of various health insurance schemes, access to medical loans could be provided. Building information sharing systems leveraging multiple public databases is crucial for success.

One such example may be leveraging the vaccination database to provide profile wise vaccination recommendations, information regarding availability of loan and credit lines, developing a ‘fraud repository’, and ensuring that online digital commerce platforms carry warnings to alert consumers to the risk of frauds etc. can play a game changer role in FI endeavours. RBI has guided banks to introduce a General-Purpose Credit Card (GCC) facility. It is revolving credit which entitles the card holder to make transactions of Rs 25,000 above the credit limit. This is completely based on customer's credit assessment and the limits are sanctioned without any security or collateral. Rate of Interest on revolving credit is deregulated. Under PM SVANidhi Scheme, micro lending amount of up to Rs 10,000 is provided to street vendors as working capital. Under PM MUDRA scheme, credit is provided to non-corporate, non-farm SMEs up to Rs 1 million. Microfinance institutions can help widen the coverage of reach by offering their services in remote areas using analytics & basic credit risk assessment [ 20 ].

7 Observations and Recommendations for accelerating Financial Inclusion

Innovations in the field of technology & communications strongly complements the FI ecosystem which results in inclusive socio-economic growth. This improves transparency and competitive efficiency, has the potential to reduce cost of service delivery and strengthens the back-end administrative processes [ 21 ].

The objective of providing a basic bouquet of financial services can be achieved through designing and developing customized financial products by banks and ensuring efficient delivery of the same through leveraging of FinTech and BC networks [ 18 ]. Some of the constructive recommendations are following-

Combining Financial inclusion with health inclusion and Social Inclusion to make the it more inclusive for citizens in the lower strata of the society. PM SBY, PM JJBY, RWBCIS, Ayushman Bharat (PM JAY) must be promoted. Till date, 158 Million + Ayushman Cards issued which requires expedite efforts to reach the full population of eligible citizens.

By analysing the impact of COVID-19, we can leverage FI and drive vaccination programs and other welfare schemes such as access to Medical Insurance & Loans for the needy. Comprehensive coverage of Health & Wellness through various initiatives to drive Health & Social Inclusion to achieve a sustainable growth [ 7 ].

Crucial aspect of FI is Financial Literacy [ 27 ]. Promote Financial Literacy and educate people on features such as Phone Banking, UPI & NFC enabled feature phones can be made available at low cost, enhance touchless payment (NFC & QR) framework. Common features such as Bill Payments, Ticket Booking are already interoperable through Bharat QR.

Strengthening the payment infrastructure to promote a level playing field for (NBFCs) and banks. Digitizing registration and compliance processes and diversifying credit sources to enable growth opportunities for MSMEs is an essential step for comprehensive inclusion [ 2 ].

Enabling agricultural NBFCs to access low-cost capital and deploy a ‘physical’ (physical + digital) model suggested by Niti Aayog for achieving better long-term digital outcomes is a crucial step. Digitizing land records will also provide a major boost to the sector.

Tech should aim to reduce cost per transaction and continue to drive the recommendation to every individual to ensure, social, health and financial inclusion and ensure that the money has been reaching the last mile beneficiary at low costs [ 26 ].

By combining digital education tools & digital financial tools, and slight changes to tax regulations, underbanked & unbanked people can break the chain of poverty and sustain successfully in a cash lite economy [ 5 ].

Geospatial technology could be used to analyse the population density of target service areas so that there is a clear understanding of required amount of work force for a particular area and can also be used to identify gaps in current services [ 25 ].

8 Summary of Key Problems we identified

Summary of problems identified & possible solutions in brief is displayed below in Table 1 .

In conclusion, we can say that a technological, multi-faceted & dynamic approach centred around enhancing financial literacy, social & education inclusion, improved cybersecurity & stricter laws, enhanced digital infrastructure is mandatory for wider coverage of next wave of financial inclusion in the country.

Data availability

All the data used in this paper for research purposes are properly cited with references to Source.

Abbreviations

Point of Sale

Micro, Small and Medium Enterprises

Reserve Bank of India

Pradhan Mantri Jan Dhan Yojana

Under PM Jeevan Jyoti Bima Yojana

Atal Pension Yojana

Pradhan Mantri Suraksha Bima Yojana

Aadhaar Payments Bridge System

Core banking system

PM Kisan Samman Nidhi Yojana

PM Street Vendors' Atmanirbhar Nidhi

Pradhan Mantri MUDRA

Bharat Interface for Money

Unified Payments Interface

National Automated Clearing House

Business correspondent network

Direct benefit transfer

Aadhaar enabled payments system

Cheque truncation system

National Payments Corporation of India

• Information and Communication Technology

Indian Post Payment Bank

PM Jan Arogya Yojana

Restructured Weather Based Crop Insurance Scheme

Near Field Communication

Non-Banking Financial Company

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Malladi, C.M., Soni, R.K. & Srinivasan, S. Digital financial inclusion: next frontiers—challenges and opportunities. CSIT 9 , 127–134 (2021). https://doi.org/10.1007/s40012-021-00328-5

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Received : 01 June 2021

Accepted : 04 July 2021

Published : 18 August 2021

Issue Date : June 2021

DOI : https://doi.org/10.1007/s40012-021-00328-5

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