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Determinants affecting profitability of state-owned commercial banks: case study of china.
1. Introduction
2. literature review, 2.1. international empirical research, 2.2. empirical studies from china, 2.3. selection of variables and hypotheses.
- Dependent variables
- Internal explanatory variables
- External explanatory variables
3. Data and Methodology
- i refers to an individual bank, and t refers to time.
- α 0 and β 0 are constants, α 1 − α 6 and β 1 − β 6 are coefficients. ε it and μ it are the error terms.
- NLTAR it refers to Net Loan to Total Asset Ratio.
- NPLTAR it refers to Non-Performing Loan to Total Asset Ratio.
- LLPTAR it refers to Loan Loss Provision to Total Asset Ratio
- CCETAR it refers to Cash and Cash Equivalents to Total Asset Ratio.
- DTAR it refers to Deposit to Total Asset Ratio.
- GDP t refers to Natural logarithm of GDP.
4.1. Descriptive Statistics
4.2. regression results, 5. discussion, 6. conclusions, author contributions, data availability statement, conflicts of interest.
Author | Sample | Y | NLTAR | DTAR | NPLTAR | LLPTAR | CCETAR | GDP |
---|---|---|---|---|---|---|---|---|
( ) | 14 major commercial banks in China from 1999 to 2005 | R O A | + | + | / | N | − | + |
( ) | 4 state-owned commercial banks in China from 1999 to 2008 | / | / | / | / | N | N | |
( ) | 5 state-owned commercial banks in China from 2004 to 2008 | / | / | / | + | + | N | |
( ) | 8 commercial banks in India from 2003 to 2011 | / | + | / | / | / | + | |
( ) | 16 listed commercial banks in China in 2018 | + | / | / | N | / | / | |
( ) | 5 largest state-owned banks in China from 2005 to 2011 | / | / | / | N | N | + | |
( ) | 14 major commercial banks in China from 1999 to 2008 | N | / | / | N | N | / | |
( ) | 12 big commercial banks in Albania from 2005 to 2012 | / | + | − | / | / | / | |
( ) | 15 schedule banks in Pakistan from 2001 to 2009 | / | - | / | − | / | / | |
( ) | 3 commercial banks in Turkey from 1998 to 2011 | ROA and ROE | / | + | / | / | − | / |
( ) | 144 commercial banks in China from 1997 to 2010 | N | N | − (ROA) N (ROE) | / | / | / |
1 | (accessed on 7 December 2020). |
2 | (accessed on 17 July 2021). |
3 | (accessed on 17 July 2021). |
4 | (accessed on 17 July 2021). |
5 | . (accessed on 17 July 2021). |
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Banks | Total Asset (2020, Million Yuan) | Total Equity (2020, Million Yuan) | Net Income (2020, Million Yuan) | The Banker Ranking 2020 |
---|---|---|---|---|
Industrial and Commercial Bank of China (ICBC) | 31,621,939 | 2,780,808 | 304,492 | 1st |
China Construction Bank (CCB) | 27,294,127 | 2,318,515 | 268,174 | 2nd |
Agricultural Bank of China (ABC) | 27,000,802 | 2,186,780 | 216,400 | 3rd |
Bank of China (BOC) | 21,363,483 | 1,838,794 | 177,200 | 4th |
Bank of Communications (BoCom) | 10,130,645 | 828,750 | 79,570 | 11th |
Variable | Obs | Mean | Std. Dev. | Min | Max |
---|---|---|---|---|---|
roe | 65 | 0.16 | 0.03 | 0.09 | 0.22 |
roa | 65 | 0.01 | 0.00 | 0.01 | 0.01 |
nltar | 65 | 0.51 | 0.04 | 0.43 | 0.57 |
npltar | 65 | 0.02 | 2.80 | 0.01 | 0.24 |
llptar | 65 | 0.01 | 0.00 | 0.01 | 0.02 |
ccetar | 65 | 0.05 | 0.02 | 0.02 | 0.12 |
dtar | 65 | 0.76 | 0.07 | 0.56 | 1.00 |
gdp | 65 | 17.83 | 0.40 | 17.11 | 18.41 |
roe | roa | nltar | npltar | llptar | ccetar | dtar | gdp | |
---|---|---|---|---|---|---|---|---|
roe | 1 | |||||||
roa | - | 1 | ||||||
nltar | −0.37 | 0.1 | 1 | |||||
npltar | −0.07 | −0.28 | −0.1 | 1 | ||||
llptar | −0.16 | −0.05 | −0.14 | −0.16 | 1 | |||
ccetar | 0.187 | −0.02 | −0.36 | 0.12 | 0.01 | 1 | ||
dtar | 0.55 | 0.27 | −0.34 | 0.47 | 0.19 | 0.13 | 1 | |
gdp | −0.6 | −0.01 | 0.47 | −0.31 | 0.33 | −0.25 | −0.47 | 1 |
POOL | RE | FE | ||||
---|---|---|---|---|---|---|
b (se) | Sig. Level | b (se) | Sig. Level | b (se) | Sig. Level | |
nltar | −0.21 | *** | −0.21 | *** | −0.10 | |
(0.06) | (0.06) | (0.09) | ||||
npltar | −0.03 | **** | −0.03 | **** | −3.27 | **** |
(0.00) | (0.00) | (0.00) | ||||
llptar | −1.19 | −1.19 | −3.50 | **** | ||
(0.73) | (0.73) | (0.98) | ||||
ccetar | 0.06 | 0.06 | 0.32 | ** | ||
(0.11) | (0.11) | (0.13) | ||||
dtar | 0.25 | **** | 0.25 | **** | 0.13 | * |
(0.04) | (0.04) | (0.06) | ||||
gdp | −0.04 | **** | −0.04 | **** | −0.05 | **** |
(0.01) | (0.01) | (0.01) | ||||
_cons | 0.84 | **** | 0.84 | **** | 1.08 | **** |
(0.13) | (0.13) | (0.18) | ||||
r2_a | 0.8 | 0.81 | ||||
r2_w | 0.81 | 0.84 | ||||
r2_o | 0.82 | 0.63 | ||||
r2_b | 0.9 | 0.02 | ||||
N | 64 | 64 | 64 | |||
N_g | 5 | 5 |
POOL | RE | FE | ||||
---|---|---|---|---|---|---|
b (se) | Sig. Level | b (se) | Sig. Level | b (se) | Sig. Level | |
nltar | 0.00 | 0.00 | 0.00 | |||
(0.01) | (0.01) | (0.01) | ||||
npltar | −0.00 | **** | −0.00 | **** | −0.17 | **** |
(0.00) | (0.00) | (0.00) | ||||
llptar | −0.09 | −0.09 | −0.02 | |||
(0.06) | (0.06) | (0.07) | ||||
ccetar | 0.00 | 0.00 | 0.03 | *** | ||
(0.01) | (0.01) | (0.01) | ||||
dtar | 0.02 | **** | 0.02 | **** | 0.00 | |
(0.00) | (0.00) | (0.00) | ||||
gdp | −0.00 | −0.00 | −0.00 | * | ||
(0.00) | (0.00) | (0.00) | ||||
_cons | 0.00 | 0.00 | 0.03 | ** | ||
(0.01) | (0.01) | (0.01) | ||||
r2_a | 0.52 | 0.51 | ||||
r2_w | 0.46 | 0.58 | ||||
r2_o | 0.56 | 0.33 | ||||
r2_b | 0.96 | 0.07 | ||||
N | 64 | 64 | 64 | |||
N_g | 5 | 5 |
zROE | zROA | |||
---|---|---|---|---|
FE | FE | |||
b (se) | Sig. Level | b (se) | Sig. Level | |
zNLTAR | −0.11 | 0.02 | ||
(0.11) | (0.13) | |||
zNPLTAR | −0.64 | **** | −0.63 | **** |
(0.07) | (0.08) | |||
zLLPTAR | −0.35 | **** | −0.01 | |
(0.10) | (0.12) | |||
zCCETAR | 0.17 | ** | 0.25 | *** |
(0.07) | (0.09) | |||
zDTAR | 0.25 | * | 0.05 | |
(0.13) | (0.16) | |||
zGDP | −0.61 | **** | −0.24 | |
(0.11) | (0.14) | |||
_cons | −0.00 | 0.00 | ||
(0.05) | (0.06) | |||
r2_a | 0.809 | 0.499 | ||
r2_w | 0.839 | 0.578 | ||
r2_o | 0.630 | 0.335 | ||
r2_b | 0.016 | 0.077 | ||
N | 64 | 64 |
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Koroleva, E.; Jigeer, S.; Miao, A.; Skhvediani, A. Determinants Affecting Profitability of State-Owned Commercial Banks: Case Study of China. Risks 2021 , 9 , 150. https://doi.org/10.3390/risks9080150
Koroleva E, Jigeer S, Miao A, Skhvediani A. Determinants Affecting Profitability of State-Owned Commercial Banks: Case Study of China. Risks . 2021; 9(8):150. https://doi.org/10.3390/risks9080150
Koroleva, Ekaterina, Shawuya Jigeer, Anqi Miao, and Angi Skhvediani. 2021. "Determinants Affecting Profitability of State-Owned Commercial Banks: Case Study of China" Risks 9, no. 8: 150. https://doi.org/10.3390/risks9080150
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HDFC Bank Case Study 2021 – Industry, SWOT, Financials & Shareholding
by Jitendra Singh | Mar 4, 2021 | Case Study , Stocks | 1 comment
HDFC Bank Case Study and analysis 2021: In this article, we will look into the fundamentals of HDFC Bank, focusing on both qualitative and quantitative aspects. Here, we will perform the SWOT Analysis of HDFC Bank, Michael Porter’s 5 Force Analysis, followed by looking into HDFC Bank’s key financials. We hope you will find the HDFC Bank case study helpful.
Disclaimer: This article is only for informational purposes and should not be considered any kind of advisory/advice. Please perform your independent analysis before investing in stocks, or take the help of your investment advisor. The data is collected from Trade Brains Portal .
Table of Contents
About HDFC Bank and its Business Model
Incorporated in 1994, HDFC Bank is one of the earliest private sector banks to get approval from RBI in this segment. HDFC Bank has a pan India presence with over 5400+ banking outlets in 2800+ cities, having a wide base of more than 56 million customers and all its branches interlinked on an online real-time basis.
HDFC Limited is the promoter of the company, which was established in 1977. HDFC Bank came up with its 50 crore-IPO in March 1996, receiving 55 times subscription. Currently, HDFC Bank is the largest bank in India in terms of market capitalization (Nearly Rs 8.8 Lac Cr.). HDFC Securities and HDB Financial Services are the subsidiary companies of the bank.
HDFC Bank primarily provides the following services:
- Retail Banking (Loan Products, Deposits, Insurance, Cards, Demat services, etc.)
- Wholesale Banking (Commercial Banking. Investment Banking, etc.)
- Treasury (Forex, Debt Securities, Asset Liability Management)
HDFC Bank Case Study – Industry Analysis
There are 12 PSU banks, 22 Private sector banks, 1485 urban cooperative banks, 56 regional rural banks, 46 foreign banks and 96,000 rural cooperative banks in India. The total number of ATMs in India has constantly seen a rise and there are 209,110 ATMs in India as of August 2020, which are expected to further grow to 407,000 by the end of 2021.
In the last four years, bank credit recorded a growth of 3.57% CAGR, surging to $1698.97 billion as of FY20. At the same time, deposits rose with a CAGR of 13.93% reaching $1.93trillion by FY20. However, the growth in total deposits to GDB has fallen to 7.9% in FY20 owing to pandemic crises, which was above 9% before it.
Due to strong economic activity and growth, rising salaries, and easier access to credit, the credit demand has surged resulting in the Credit to GDP ratio advancing to 56%. However, it is still far less than the developed economies of the world. Even in China, it is revolving around 150 to 200%.
As of FY20, India’s Retail lending to GDP ratio is 18% , whereas in developed economies (US, UK) it varies between 70% – 80%).
Michael Porter’s 5 Force Analysis of HDFC Bank
1. rivalry amongst competitors.
- The banking sector has evolved very rapidly in the past few years with technology coming in, and now it is not only limited to depositing and lending but various categories of loans and advances, digital services, insurance schemes, cards, broking services, etc.; hence, the banks face stiff competition from its rivals.
2. A Threat by Substitutes
- For services like mutual funds, investments, insurances, categorized loans, etc., banks are not the only option these days because a lot of niche players have put their foot in the specialized category, surging the threat by substitutes for the banks.
- Another threat for the traditional banks is NEO Banks. The Neo Banks are virtual banks that operate online, are completely digital, and have a minimum physical presence.
3. Barriers to Entry
- Banks run in a highly regulated sector. Strict regulatory norms, huge initial capital requirements and winning the trust of people make it very tough for new players to come out as a national level bank in India. However, if a company enters as a niche player, there are relatively fewer entry barriers.
- With RBI approving the functioning of new small finance banks, payment banks and entry of foreign banks, the competition has further intensified in the Indian banking sector.
4. Bargaining Power of Suppliers
- The only supply which banks need is capital and they have four sources for the capital supply viz. deposits from customers, mortgage securities, loans, and loans from financial institutions. Customer deposits enjoy higher bargaining power as it is totally dependent on income and availability of options.
- Financial Institutions need to hedge inflation, and banks are liable to the rules and regulations of the RBI which makes them a safer bet; hence, they have less bargaining power.
5. Bargaining Power of Customers
- In modern days, customers not only expect proper banking but also the quality and faster services. With the advent of digitalization and the entry of new private banks and foreign banks, the bargaining power of customers has increased a lot.
- In terms of lending, creditworthy borrowers enjoy a high level of bargaining power as there is a large availability of banks and NBFCs which are ready to offer attractive loans and services at low switching and other costs.
HDFC Bank Case Study – SWOT Analysis
Now, moving forward in our HDFC Bank case study, we will perform the SWOT analysis.
1. Strengths
- Currently, HDFC Bank is the leader in the retail loan segment (personal, car and home loans) and credit card business, increasing its market share each year
- The HDFC tag has become a sign of trust in the people as HDFC has come out as a pioneer not only in banking, but loans, insurances, mutual funds, AMC and brokerage.
- HDFC Bank has always been an institution of its words as it has, without fail, delivered its guidance and this has created a strong brand loyalty in the market for them.
- HDFC Bank has very well leveraged the technology to help its profitability, only 34% transaction via Internet Banking in 2010 to 95% transaction in 2020.
2. Weaknesses
- HDFC bank doesn’t have a significant rural presence as compared to its peers. Since its inception, it has focused mainly on high-end clients. However, the focus is shifting in the recent period as nearly 50% of its branches are now in semi-urban and rural areas.
3. Opportunities
- The average age of the Indian population is around 28 years and more than 65% of the population is below 35, with increasing disposable income and rising urbanization, the demand for retail loans is expected to increase. HDFC Bank, being a leader in retail lending, can make the best out of this opportunity.
- With modernization in farming and a rise in rural and semi-urban disposable income, consumer spending is expected to rise. HDFC Bank can increase its market share in these segments by grabbing this opportunity. Currently, the bank has only 21% of the branches in rural areas.
- A lot of niche players have set up their strong branches in respective segments, which has shown stiff competition and has shrined the market share and profit margin for the company. Example – Gold Loans, Mutual Funds , Brokerage, etc.
- In-Vehicle Financing (which is HDFC Bank’s major source of lending income), most of the leading vehicle companies are providing the same service, which is a threat to the bank’s business.
Asian Paints Case Study 2021 – Industry, SWOT, Financials & Shareholding
HDFC Bank’s Management
HDFC Bank has set high standards in corporate governance since its inception.
Right from sticking to their words to proper book writing, HDFC has never compromised with the banking standards, and all the credit goes to Mr. Aditya Puri, the man behind HDFC Bank, who took the bank to such great heights that today its market capitalization is more than that of Goldman Sachs and Morgan Stanley of the US.
In 2020, after 26 years of service, he retired from his position in the bank and passed on the baton of Managing Director to Mr. Shasidhar Jagadishan. He joined the bank as a Manager in the finance function in 1996 and with an experience of over 29 years in banking, Jagadishan has led various segments of the sector in the past.
Financial Analysis of HDFC Bank
- 48% of the total revenue for HDFC bank comes from Retail Banking, followed by Wholesale Banking (27%), Treasury (12%), and 13% of the total comes from other sources.
- Industries receive a maximum share of loans issued by HDFC bank, which is 31.7%, followed by Personal Loans and Services both at a 28.7% share of the total. Only 10.9% of the total loans are issued to Agricultural and allied activities.
- HDFC Bank has a 31.3% market share in credit card transactions, showing a growth of 0.23% from the previous fiscal year, which makes it the market leader, followed by SBI.
- HDFC Bank is the market leader in large corporate Banking and Mid-Size Corporate Banking with 75% and 60% share respectively.
- In Mobile Banking Transaction, the market share of HDFC bank is 11.8%, which has seen a degrowth of 0.66% in the current fiscal year.
- With each year, HDFC Bank has shown increasing net profit, which makes the 1-year profit growth (24.57%) greater than both 3-year CAGR (21.75%) and 5-year CAGR (20.78%).
CAR | |
---|---|
18.52 | |
16.11 | |
17.89 | |
17.53 | |
15.04 | |
27.43 |
- Capital Adequacy Ratio, which is a very important figure for any bank stands at 18.52% for HDFC Bank.
- As of Sept 2020 HDFC, is at the second position in bank advances with a 10.1% market share, which has shown a rise from 9.25% a year ago. SBI tops this list with a 22.8% market share, Bank of Baroda is at the third spot with a 6.68% share, followed by Kotak Mahindra Bank (6.35%).
- HDFC Bank is again at the second spot in the market share of Bank deposits with 8.6%. SBI leads with a nearly 24.57% market share. PNB holds 7.5% of the market share in this category, coming out as the third followed by Bank of Baroda with 6.89%.
HDFC Bank Financial Ratios
1. profitability ratios.
- As of FY20, the net profit margin for the bank stands at 22.87%, which has seen a continuous rise for the last 4 fiscal years. This a very positive sign for the bank’s profitability.
- The Net Interest Margin (NIM) has been fluctuating from the range of 3.85% to 4.05% in the last 5 fiscal years. Currently, it stands at 3.82% as of FY20.
- Since FY16, there has been a constant fall in RoE, right from the high of 18.26% to 16.4% as of FY20.
NPM | NIM | RoE | RoA | |
---|---|---|---|---|
22.87 | 3.82 | 16.4 | 1.89 | |
10.6 | 3.28 | 7.25 | 0.77 | |
22.08 | 3.88 | 13.08 | 1.77 | |
2.6 | 3.05 | 2.15 | 0.19 | |
15.35 | 4.26 | 14.71 | 1.51 | |
27.78 | 7 | 22.91 | 4.08 |
- RoA has been more or less constant for the company, currently at 1.89%, which is a very positive sign.
2. Operational Ratios
- Gross NPA for the bank has fallen from FY19 (1.36) to 1.26, which a positive sign for the company. A similar improvement is also visible in the Net NPA, currently standing at 0.36.
- The CASA ratio for the bank is 42.23%, which has been seeing a continuous fall since FY17 (48.03%). However, there has been a spike rise in FY17 as in FY16, it was 43.25 and in FY18, again came to the almost same level of 43.5.
- In FY19, Advance Growth witnessed a massive spike from 18.71 level in FY18 rising to 24.47%. However, in FY20, it again fell nearly 4 points, coming down to 21.27%.
Gross NPA | Net NPA | CASA | Advance Growth | |
---|---|---|---|---|
1.26 | 0.36 | 42.23 | 21.27 | |
1.54 | 45.11 | 10 | ||
2.3 | 0.71 | 56.17 | 6.83 | |
4.86 | 1.56 | 41.2 | 15.49 | |
2.45 | 0.91 | 40.37 | 10.94 | |
1.48 | 0.58 | 36.84 | 68.07 |
HDFC Bank Case Study – Shareholding Pattern
- Promoters hold 26% shares in the bank, which has been almost at the same level for the last many quarters. In the December quarter a years ago, the promoter holding was 26.18%. The marginal fall is only due to Aditya Puri retiring and selling few shares for his post-retirement finance, which he stated.
- FIIs own 39.95% shareholding in the bank, which has been increasing for years in every quarter. HDFC bank has been a darling share in the investor community.
- 21.70% of shares are owned by DIIs as of December Quarter 2020. Although it is less than the SeptQ2020(22.90%), it is still far above the year-ago quarter (21.07).
- Public holding in HDFC bank is 12.95% as of Dec Q2020, which has tanked from the year-ago quarter (14.83%) as FIIs increasing their share, which is evident from the rising share prices.
Closing Thoughts
In this article, we tried to perform a quick HDFC Bank case study. Although there are still many other prospects to look into, however, this guide would have given you a basic idea about HDFC Bank.
What do you think about HDFC Bank fundamentals from the long-term investment point of view? Do let us know in the comment section below. Take care and happy investing!
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Lean Six Sigma solves a commercial bank's growth problem
When credit issues constrained growth for a commercial bank client, Bain applied Lean Six Sigma principles to improve the credit process. The resulting rule-based credit policies and faster approval process helped the client delegate more responsibility to front-line employees, reduce processing time and increase accuracy.
At a Glance
- 30% reduction in time required to approve credit applications (with fast track deals)
- 10-15% reduction of deals requiring approval by central credit head
- 25% reduction in applications requiring rework
The Situation
As the residential property market slowed, local banks shifted their focus to commercial banking. However, credit issues were a major constraint to growth of the business.
- Credit issues included credit processes, policies, capabilities and culture
- Problems existed throughout the organization, from sales force and front line credit approvals team to central group credit
Commercial Bank Co.* engaged Bain to help develop a growth strategy to increase the speed, accuracy and efficiency of credit processes and decision making.
Our Approach
Bain applied Lean Six Sigma principles to improve the performance and efficiency of credit process.
Our Recommendations
Bain recommended rule-based credit policies with faster approval process to enable growth, reduce processing time and increase accuracy.
The Results
Commercial Bank Co. implemented Bain's recommendations, along with metrics to track improvements and change management processes to ensure success.
How We've Helped Clients
Sales and marketing building a more valuable salesforce, performance improvement streamlining engine assembly boosts output, change management the change process unlocks potential and profits, ready to talk.
We work with ambitious leaders who want to define the future, not hide from it. Together, we achieve extraordinary outcomes.
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Winning corporate clients with great onboarding
Lengthy approvals for a new account. Providing the same information three times. Getting emails for documents you’ve already submitted. No visibility about the status of an application or where you are in the process.
Corporate clients often encounter these and other pain points when trying to access banking services as a new customer or when trying to add more services as an existing customer. Much like consumers in the retail banking space, corporate clients want easy, intuitive, user-friendly digital access to banking services. Yet too often, they don’t get what they’re looking for.
Instead, banks lead companies through an onboarding process that’s slow, duplicative, and overly complex, often causing potential customers to drop off or creating significant dissatisfaction among existing clients. The average onboarding process for a new corporate client can take up to 100 days and varies significantly depending on the banking products and geographies involved.
Global banking revenues are expected to rise by 9 percent a year through 2025, with corporate clients at the heart of this growth.
This challenge has significant financial implications for banks. Time-to-revenue has become an increasingly key metric for banks, so the longer onboarding takes, the slower the process of booking revenue. In addition, the onboarding of new corporate clients represents a sizeable growth opportunity. According to McKinsey Panorama, global banking revenues are expected to rise by 9 percent a year through 2025, with corporate clients at the heart of this growth. Much of the industry’s growth will come from fee-based services, such as digital, real-time domestic payments and beyond-banking features like spend analytics and cash forecasting. Although less visible than other areas of wholesale banking, these global transaction banking (GTB) services already represent about $1.2 trillion—almost half of total global wholesale banking revenues (Exhibit 1).
Participating in this growth opportunity will depend upon banks optimizing their end-to-end onboarding experience for transaction banking customers. Doing so can create real value—we have seen banks taking this approach boost EBITDA, increase the proportion of new clients receiving approval, raise customer satisfaction scores, and reduce onboarding operating costs.
Although historically overlooked and underfunded, onboarding is an area of increased focus and investment for global banks. With the acceleration of digital behaviors among all customer segments and the continued strength of fintechs, banks are feeling pressure to differentiate themselves from their peers. Based on detailed quantitative surveys and one-on-one qualitative interviews with two dozen global banks, this article delves into the state of the industry’s efforts and the specific opportunities banks have to improve their onboarding experience. It also offers a road map for what the optimization of onboarding looks like.
Key findings from our most recent survey include:
- Know-your-customer (KYC) due diligence and account opening are significant bottlenecks . Banks report that more than 40 percent of the time a customer spends onboarding is consumed by these two processes (Exhibit 2). As such, they are key targets for efforts to streamline and improve onboarding. Lengthy account openings are caused primarily by the manual input of client data and a lack of internal system connectivity. KYC due diligence is a highly important process that banks must get right. But it can be complex, because banks write many client contracts individually to comply with variations in local regulations. This complexity can be reduced, however, by automating the aggregation of public data through utilities, leveraging data that banks already have on customers, and eliminating duplicative data elements on forms. In addition, banks can rigorously reevaluate the often-excessive levels of documents they believe are necessary to satisfy local and global requirements.
- Automation and technology present the biggest onboarding challenges for banks . Many banks simply do not have the technology infrastructure to make onboarding the seamless, transparent digital experience it needs to be. In our research, we found that half of all banks have no tech solutions for many onboarding processes. Many of the solutions that do exist have been developed by banks to reflect a need for heavy customization and are not integrated with other solutions. Under the pretext of offering white-glove service to clients, processes are often extremely manual, which can lead to errors and confidence gaps. Often, no single digital repository exists for customer data such as contracts, documents, and transaction information. In addition, internal case management systems are outdated and require manual customizations for any changes or updates, and the testing of client payment files is unnecessarily labor-intensive. Banks that invest in flexible API technology for file testing enable a much quicker, more seamless process.
- Many banks are in the process of adding key digital functionality . The most common digital feature banks offer is the electronic signing of documents (80 percent say they have this) (Exhibit 3). Half say they allow clients to apply for multiple products at the same time, with another 25 percent saying this capability will be implemented within the next 12 months. Some 40 percent enable customers to instantly open accounts, with an account number issued and KYC process pending. Many banks are also working on adding features that are currently not widespread, such as analytical capabilities that provide clients with insights about their customers or competitors, the option to submit KYC documents electronically, and the ability for customers to check the status of their applications in real time.
- In-house tech solutions predominate . Due to the complexity of onboarding and a lack of solutions from vendors, leading banks use in-house technology over that of vendors or hybrid approaches (Exhibit 4). All the institutions in our survey say they primarily rely on in-house technology for client portals and client communication tools. When banks do opt to work with vendors, they often choose a complete solution that’s standardized and can be easily integrated with their enterprise resource planning systems, rather than a hybrid approach.
- Banks are implementing some features more quickly than others . Technologies that help address obvious pain points—such as a self-service client portal, document management automation, and end-to-end workflow software—are planned for the near term. Portals provide clients a unified place to submit information and documents and to do real-time tracking of account openings and applications. Document automation helps client paperwork move through the system more quickly and without errors, and workflow solutions give relationship managers an integrated view of where a customer is in the application process. While portals need to be built and customized by banks, document management automation and workflow solutions can be supplied by vendors and then integrated with a bank’s internal processes. Capabilities that involve more complex implementation are slated for medium- to long-term efforts (Exhibit 5).
A road map for onboarding transformation
Leading banks are starting to shift their approach to onboarding. They are moving away from fragmented data architectures and in-house technology and redesigning an end-to-end onboarding experience from the customer perspective. Here, fintechs, which have promoted smooth onboarding as part of their value proposition, are a source of inspiration. Without any legacy systems, they have been free to build a flexible tech architecture that lets them use APIs to leverage or build new and advanced solutions. Many fintechs have also benefited from a culture of customer-centricity, with teams laser focused on how the customer experiences onboarding. This, coupled with a flexible architecture, has allowed fintechs to offer customers what they want—speed, transparency, and fewer documents to handle.
Our work with banks across the industry shows that corporate clients care most about having access to fast, streamlined digital processes (one with minimal handoffs, no duplicate information, and a user-friendly portal) and an expert team of knowledgeable support staff offering services tailored to their needs. Based on our evaluation of offerings from front-runner banks and fintechs, we have identified a variety of best practices across five key dimensions.
- A connected client experience . Our recent research shows that most corporate clients like having a self-service portal that functions as a single point of engagement with the bank. For this to be effective, the portal should feature a smart, personalized client intake interface that only asks for information relevant to that client. It should also be tailored to a client’s previous answers to questions and subject to continuous improvements based on client feedback. We have seen banks that equip their client portals with several essential features—status tracking, automated document upload, multifactor biometric authentication, electronic signatures, and an AI-enabled chatbot—experience significant boosts in adoption of these portals. Other digital capabilities that drive smoother onboarding include prepopulated data from public sources and prefilled documents that only ask clients for approval instead of asking them to fill out yet another form. Given that many corporate clients work with multiple banks, they also want the ability to access banking services directly and seamlessly from their own financial infrastructure or ecosystem via APIs.
- A commitment to speed and transparency about timing . To ensure that onboarding is truly meeting client expectations, leading banks are communicating clear goals to their clients about how long it will take to onboard for different products—whether through service-level agreements or less formal checklists. Since the time it takes to generate revenue from a client is a key metric (this can run from 30 to 100 days), leading banks are tracking this business performance driver and addressing any delays.
- A tech-enabled process . Currently, case managers and the (often large) onboarding teams that work with them have limited transparency into the effectiveness and efficiency of the process. As noted earlier, banks are now actively investing in intelligent workflow solutions to address this problem, especially given the recent availability of software that requires no or low additional code writing while still allowing a level of customization. These solutions perform automated case assignment based on the experience of the case manager and the client business and risk profile. Supported by real-time (or near-real-time) API-enabled data feeds, they also give case managers alerts on onboarding progress and next steps, as well as notifications for when clients haven’t complied with document requests. Fintechs and leading banks are going a step further to empower these workflows by using AI to resolve duplicate documents, detect data anomalies, identify inconsistencies across sources, automate the enforcement of business rules, and digitize documents.
Beyond using data to improve client onboarding, we believe banks have a significant opportunity to use the vast amount of data they collect from clients to both benefit customers and generate new business. Upon a customer’s consent, banks can use data from client transactions, profiles, and KYC sources to create an intelligent, 360-degree view of customers, which can then inform new, customized product offerings. Leading banks are leveraging embedded “wizard” tools to estimate their share of the customer’s wallet in an effort to make their product offerings more targeted and personalized.
- Investment in new skills . The management of fast, tech-enabled, and more efficient corporate client onboarding requires new employee skills. Case managers will want to have a holistic understanding of the end-to-end workflow, as well as of various analytics components of the process. This training and upskilling of employees will require significant investment from banks but will also result in the creation of higher-knowledge career paths for many. As technology becomes effective in addressing data-quality issues and other pain points, it’s possible that fewer overall personnel will be needed for onboarding.
Leading banks are using centralized databases to automatically upload existing documentation and prepopulate templates for additional accounts their clients seek to open.
Prioritizing the onboarding of corporate clients is quickly becoming a top agenda item for many banks. Investing in this overlooked aspect of customer experience represents not only an opportunity for competitive differentiation and greater process efficiency but also future revenue growth. If anything, the current global environment of rising interest rates and appeal of providing clients with fee-based transactions (which don’t require a risk to capital) could further accelerate the value of onboarding in GTB and promote additional investment by leading banks and fintechs. Even though this kind of transformation is a complex, multiyear journey, many banks are seeing quick wins by starting with a self-service portal and setting a clear road map for what success will look like.
Imke Jacob and Siggy Seibold are partners in McKinsey’s New York office.
The authors wish to thank Suvan Agarwal, Philip Bruno, Saswati Hazarika, Vaibhav Jindal, Ming-Lan Fu, and Craig Vaream for their contributions to this article.
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Risk Management in Commercial Banks (a Case Study of Public and Private Sector Banks)
Indian Institute of Capital Markets 9th Capital Markets Conference Paper
22 Pages Posted: 25 Jan 2006
Rekha Arunkumar
Bapuji Institute of Engineering & Technology
G. Kotreshwar
University of Mysore
"Banks are in the business of managing risk, not avoiding it . . . ." Risk is the fundamental element that drives financial behavior. Without risk, the financial system would be vastly simplified. However, risk is omnipresent in the real world. Financial Institutions, therefore, should manage the risk efficiently to survive in this highly uncertain world. The future of banking will undoubtedly rest on risk management dynamics. Only those banks that have efficient risk management system will survive in the market in the long run. The effective management of credit risk is a critical component of comprehensive risk management essential for long-term success of a banking institution. Credit risk is the oldest and biggest risk that a bank, by virtue of its very nature of business, inherits. This has, however, acquired a greater significance in the recent past for various reasons. Foremost among them is the wind of economic liberalization that is blowing across the globe. India is no exception to this swing towards market-driven economy. Better credit portfolio diversification enhances the prospects of the reduced concentration credit risk as empirically evidenced by direct relationship between concentration credit risk profile and NPAs of public sector banks. ". . . a bank's success lies in its ability to assume and aggregate risk within tolerable and manageable limits."
Keywords: Banks, Risk Management, Credit risk, NPA, India, Concentration risk, Risk based supervision
Suggested Citation: Suggested Citation
Rekha Arunkumar (Contact Author)
Bapuji institute of engineering & technology ( email ).
Karnataka India
University of Mysore ( email )
Manasagangotri, karnataka 570006 India
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Risks and Efficiency in the Islamic Banking Systems: The Case of Selected Islamic Banks in MENA Region
By Ali Said
Banking on data
How Siam Commercial Bank reimagined data to drive value.
Call for change
Every day, banks generate terabytes of data—information from transactions, loan applications and more. Even a simple customer action, such as making a deposit at their local branch, creates a data point that banks can use to better understand customer needs and identify marketplace trends.
Siam Commercial Bank (SCB), the third-largest bank in Thailand by asset size, wanted to unlock the value of its data to enhance experiences for consumers, optimize operations and fuel future growth. The bank’s main repository of data—its data warehouse—was hosted on premises and outdated technology, making it costly to manage, and was limited in its ability to scale. The lake also wasn’t equipped to handle new types of unstructured data. These lake limitations prevented the bank from using more advanced data analytics to derive key insights and drive decisions.
SCB wanted to be a pioneer amongst its peers and set out on an ongoing, multi-year transformation journey to jumpstart the business. At the heart of the project was the desire to use a constant stream of data-derived insights to reinvent its approach and customer experience.
When tech meets human ingenuity
SCB partnered with Accenture to develop and deliver an award-winning digital transformation strategy. The approach combined advanced data and analytics capabilities with people-focused processes and tools.
The first step was shoring up the data lake—migrating the bank's foundational data repository to Microsoft Azure Cloud, making SCB the first bank in the region to achieve this milestone.
The team also made data and analytics easier to access and use by deploying Microsoft Power BI to create interactive dashboards for several business areas. To improve ATM cash management, the team used artificial intelligence and a combination of advanced machine learning techniques to analyze more than 12 million transactional data points and more than 200 variables—such as locations, pay days, seasons and holidays—to determine optimal cash levels for each ATM.
Creating a data-driven culture takes more than just new technologies and analytics. It requires data governance and change management to help employees adapt to new ways of working. Creating a Data Governance Office, an Analytics Center of Excellence and a bank-wide data stewardship program helped implement clear guidelines for effective and secure use of data and analytics.
Now, marketers can access insights from this data on interactive Power BI dashboards to identify and craft personalized marketing messages for prospects based on their lifestyles, interests and financial needs. Also, automated underwriting risk tools reduce time to process loan applications.
A valuable difference
Having achieved impressive results with their digital transformation efforts, the International Data Corporation (IDC) recognized the team with its Information Visionary in Thailand award in 2019.
Replacing the old data lake and migrating the new lake to the cloud reduced the bank’s data storage costs, while enabling specific functions for retail banking to apply customer insights to serve their customized needs.
Automating daily forecasts for ATM cash management began producing savings within eight weeks from idea to execution and achieved 98.8% ATM service levels with 50% less cash balance. Reducing both the amount of cash in ATM circulation and delivery costs for ATM replenishment. Centralizing institutional knowledge also ensured that insights are retained within the bank to support knowledge retention and continuous improvement.
In addition, SCB’s innovative approach to increasing unsecured lending business is getting results. Data-driven digital marketing generated 10% more campaign responses and a 3x improvement on the model. Automation reduced manual processes by 40%, improved accuracy and accelerated loan approvals and processing, securing higher customer satisfaction while effectively managing risks.
Reduction in data storage due to compression techniques
Improvement to ATM service levels
We are very grateful for the opportunity to work with SCB on this award winning, strategic transformation journey over the years.
Joon Seong Lee / ASIAM, SEA & Innovation Lead, Strategy & Consulting
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Profitability in Commercial Bank -A Case Study of Nepal
2021, International Journal of Case Studies in Business, IT and Education (IJCSBE)
Purpose: Banking in Nepal is under the process of being systematized. Foreign aid is believed as key component for development in Nepal. This study aims to assess the impact, contribution and relationship of size, loans and deposit, inflation and capital on the profitability of the banks. Design/Methodology/Approach: Secondary data from 2013 to 2019 from seven commercial banks along with the survey as primary data were collected. The correlation and regression along with ratio analysis have been used to assure a contributory association among return on assets (ROA), return on equity (ROE) and net interest margin (NIM). Findings/Result: The size of banks is in increasing trend. The decreasing trend of standard deviation showed that the size of Nepalese commercial banks has lower variation in the use of total assets as the year increases. There is a negative relation between ROA and ROE with loan ratio, deposit ratio and capital ratio, while there is positive relation with bank size and inflation. However, in case of NIM, bank size, loan ratio, deposit ratio and inflation exhibit a positive relation while the capital ratio shows the negative relationship with NIM. Majority of the respondents feel that the publication of financial reports is one of the major influencing factors of bank profitability. Originality/Value: It is an empirical research to signify the contribution of Bank Size, Loan Ration, Deposit Ratio, Capital Ratio and Inflation as determinants of Profitability. Paper Type: Analytical Business Research.
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Purpose-The purpose of this study is to examine the the key determinants of profitability of Nepalese commercial banks. Methodology-This study employs descriptive statistics to describe the profitability of Nepalese banks and its determinants. Further, the degree of correlation among different indicators of profitability and its determinants has been assessed by calculating correlation coefficient. Finally, this study has adopted a panel data regression model (Fixed Effect Model and Random Effect Model) to investigate the determinants and their impact on profitability of Nepalese commercial banks. Findings-The analysis reveals that the bank pofitability measured by ROA of Nepalese commercial banks is significantly affected by concentration ratio, banking sector development, GDP growth, inflation and exchange rate significantly in opposite direction rather it is not significantly affected by the internal factors like bank size, capital base, deposit, loan, off-balance sheet activities and number of branches. Another indicator of bank profitability; NIM is significantly affected only by capital adequacy, absolute number of branches and inflation rate. Conclusion-This study concluded that the profitability of Nepalese commercial banks measured by return on assets is significantly influenced by the external factors. Among external factors, industry specific factors have high degree of impact on return on assets whereas macroeconomic variables have quite a weak degree but significant impact on profitability of Nepalese commercial banks as measured by return on assets. Further, the profitability measured by net interest margin (NIM) is significantly influenced only by capital adequacy, absolute number of branches and annual inflation rate.
Transstellar Journal , 2019
This study is to determine the factors that effects on profitability of Nepalese commercial banks. The study is based on secondary data of 11 banks with 77 observations for the period 2010/11 to 2016/17. The independent variables such as, credit deposit ratio, market share, liquidity, non-performing loans, GDP and inflation and dependent variable return on assets taken for the study. The market share price, liquidity and GDP has explained the profitability in Nepalese sample commercial banks cases.
Tribhuvan University Journal, 2021
This paper aims to investigate the impact of bank specific factors unprofitability of Nepalese commercial banks. Total assets, total deposit, total loan and advance and total equity are taken as independent variables and return on assets is taken as dependent variable. The study is based on pooled least square method. The seven years’ panel data from 2012 to 2018 is taken for the study. Taking 112 observations from sixteen commercial banks, the regression result, F-test and t-test are used for analysis. The study found that the total assets and total loan and advance have positive significant impact on profitability of Nepalese commercial banks. The study also revealed that the total equity has not significant impact and deposit has negative significant impact on profitability of commercial banks in Nepal. The study has important implications for the policy makers of Nepalese commercial banks to utilize their assets, loans, deposits properly and equity for sound profitability.
Account and Financial Management Journal, 2020
This study seeks to examine the relationship between the capital structure and the profitability of commercial Banks in Nepal. In this connection, 18 Nepalese commercial banks were selected as study samples and their financial data were gathered from NRB BI Statistics and Bank Supervision Report for the period of 2010-2019. Return on Equity was used as indicator of profitability while short term debt, long term debt, deposits and total debt to assets ratio were used as a proxy of capital structure along with the control variables of bank size and assets growth. Results showed that more than 40 percent bank profitability measured by return on equity is predicted by the explanatory-capital structure variables. It is also revealed that return on equity is insignificantly positively related with long term debt and deposits whereas it is insignificant negative with short term debt and total debt. In all regression models, profitability is significantly positively related with banks size indicating that larger the size of the bank, higher is the return for shareholders.
This paper examines the determinants of financial performance of commercial bank in Nepal. In order to investigate the determinants of financial performance, 10 commercial banks have been taken as sample covering the period of time 2006/07 to 2016/17. Data are collected from annual report of the respective banks. Multiple linear regression models have been employed for the analysis of data. The result shows a positive relationship of return on assets with capital adequacy ratio, management efficiency and gross domestic product whereas negative with assets quality and liquidity management. It is evident from the findings that financial performance of commercial banks are strongly affected by capital adequacy ratio, management efficiency, gross domestic product, liquidity management and assets quality.
The Nepalese financial system consists of different types of banks and financial institutions which are responsible for the development of the country's economy. Commercial banks are the major financial institutions which play an important role in the mobilization and allocation of resources in an economy. The performance of the financial sector in a larger prospective affects the growth of the economy. The financial sector reform program initiated in Nepal since 1980's have very strong far reaching impact in the development of banking sector and economy. This paper attempts to study the working and operational performance of the Nepalese commercial banks from period 2009 and 2015. The indicators selected for study are aggregate deposits mobilized by commercial banks, credits and investments made by the commercial banks, credit-deposits ratios, investment-deposits ratios, and the share of Commercial Banks in the Priority Sector Lending. This study concludes commercial banks ...
The Lumbini Journal of Business and Economics, 2022
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A LARGE INTERNATIONAL BANK ASKED US TO DEFINE AND CREATE A NEW EXPERIENCE FOR ITS COMMERCIAL BANKING TEAM THAT WOULD POSITION IT AS A PARTNER TO SME BUSINESSES AND CORPORATES, AT EVERY STAGE OF THEIR JOURNEY, ACROSS 70 SITES IN 50 MARKETS.
In addition to defining the role and purpose of the experience we were asked to move the entire CMB website ecosystem from Sitecore 8.2 to 9.3 whilst integrating with new data technologies to our clients environment. Our client would usually use a traditional re-platforming (lift and shift) approach moving all existing content, services and tools to the new infrastructure, meaning long timelines to launch and large budgets.
When responding to the brief, we proposed a more aggressive approach, creating an entirely new service that we would launch quickly and start learning defined customer behaviours that would determine future product releases.
This new approach meant the new service was customer-centric, data-led and more agile, helping move our client’s business from:
- Brand-out to customer-in
- Data-aware to data-driven
- Linear customer journeys to behavioural-led experiences
- Globally distributed to local creation
- Siloed product development to omni-channel service design
- One-off big launch to incremental value-driven releases.
Guided by AF’s behaviour-led approach, we defined a new proposition for an intelligent service that delivers contextually relevant content, that could be flexible and efficient for local markets to react to fast changing customer needs.
The intelligent service allows markets to understand the content tools and services are that have the desired impact on desired customer behaviours. This data then informs the marketing message, increasing effectiveness of acquisition. By understanding the end to end customer experience it allows us to be hyper local, using the behaviours across the service and the marketing message to create new relevant content, tools and services for individual markets.
Rather than a traditional big-bang launch we planned to launch fast through an MVP and then evolve through ongoing learning of customer behaviour to define the rest of the new tools and services of the experience. Ultimately using these learnings to inform and integrate with marketing communications to make them more relevant and effective . To create a rich MVP experience for each user, we reimagined how our client position their thought leadership, products/solutions to be customer-first . Working with global and local teams, we developed new ways for customers to identify their needs and increasingly customise the experience every time a user visits.
Working in an agile scrum of scrums framework, we integrated data, experience, design and technology teams together to create the MVP with two pilot markets The information /behaviours gained from the MVP will feed into the development of the content, tools and services of the full product release in 2021.
Typically launching a new PWS experience inside our client’s environment would take a few years, however with our ambitious approach, we launched our MVP solution in our two chosen markets – Canada and Australia.
Our next challenge is to learn from the MVP and create content, tools and services for the full experience that will be rolled out across 50 markets in 2021.
Our unique approach of getting part of the experience (content) live as soon as possible in the latest technology has allowed us to get key customer insights long before a traditional roll-out would. RMs are already indicating they are getting new, essential leads.
These are the early behaviours we have that show the proven value we have given our client in a short period of time.
- Content exposure and exploration has increased
- Scroll depth has increased with 15% reaching the bottom of the page and time on site 4x the current site
- Increased engagement with both articles and products and solutions
- Average number of pages viewed per visit has tripled across the MVP
- Intent to contact RMs has increased
- Clicks through to contact has increased by 2.5x in Canada and 7x in Australia driving new leads
CUSTOMER NEEDS
- Varying needs across markets providing a new understanding of the support our client can provide:
- Canada – Enable growth, Expanding abroad and Ensure sufficient cash flow are the top topics
- Australia – Enable growth, Make & Receive payments, Digital adoption and Green banking are the top topics
- And markets are already using these insights to develop new content and aligning marketing activities to customer needs.
case studies
A large international bank asked us to define and create a new experience for its Commercial Banking team that would position it as a partner to SME businesses and corporates, at every stage of their journey, across 70 sites in 50 markets.
Rather than a traditional big-bang launch we planned to launch fast through an MVP and then evolve through ongoing learning of customer behaviour to define the rest of the new tools and services of the experience. Ultimately using these learnings to inform and integrate with marketing communications to make them more relevant and effective. To create a rich MVP experience for each user, we reimagined how our client position their thought leadership, products/solutions to be customer-first. Working with global and local teams, we developed new ways for customers to identify their needs and increasingly customise the experience every time a user visits.
CASE STUDIES
- Automated Capture Automatically capture sales data, activities, and leads to Salesforce
- Calendar sync Sync Salesforce calendar with Outlook and Gmail calendars
- Inbox Sidebar Access, edit, and manage Salesforce data directly from your email inbox
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- Sales sequences for Salesforce Send automated nurturing and prospecting campaigns and sequences
- Engagement Signals Gain insights on your most engaged leads, prospects, and accounts
- Performance and revenue reports Get comprehensive reports on sequences, content, and teams
- Pipeline Visibility Inspect your pipeline health and track important shifts and changes
- Revenue Signals Help your team execute better with actionable real-time deal alerts
- Deal insights Get intelligence on risks, weak spots, and openings for every deal
- Team Analytics Analyze your sales team’s activities and improve sales process
- Sales forecasting Track and manage forecasts with revenue analytics and dashboards
- Team coaching Make your sales coaching initiatives effective and scalable
- Productivity package
- Engagement package
- Intelligence package
- Activity Capture Engine
- Revenue Grid vs. Competitors Discover why Revenue Grid trumps other competitors in the RO&I market
- EAC vs. Revenue Grid Compare Einstein Activity Capture and Revenue Grid side-by-side
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- Salesforce for Outlook retirement Transition seamlessly from Salesforce for Outlook to Revenue Grid
- Recruitment How one recruiter stood out from the competition with unique messaging
- Emerald Scientific An equipment distributor improved pipeline efficiencies and visibility to drive growth
- Rand Simulation A leading simulation solutions and services provider improved lead generation 25%
- Vapotherm How a medical device manufacturer saved 761 working days in one year
- Slalom The sales team rebuilt its sales model and grew its business
- Morgan and Morgan A law firm increased its caseload load by 15-20% while optimizing CRM usage and adoption.
- Insurance How full-service insurance brokerage firm expanded its business
- VDA A vertical transportation consulting firm increased customer engagement 20%
- Commercial Bank How one multi-billion dollar commercial bank enhanced customer relationships
- CAPIS How capital market company overcomes data inaccuracy and improve visibility
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- Funding Raised Revenue Grid raises $20 million to transform Revenue Operations
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