To read this content please select one of the options below:

Please note you do not have access to teaching notes, automobile insurance fraud detection in the age of big data – a systematic and comprehensive literature review.

Journal of Financial Regulation and Compliance

ISSN : 1358-1988

Article publication date: 8 April 2022

Issue publication date: 2 August 2022

The purpose of this paper is to survey the automobile insurance fraud detection literature in the past 31 years (1990–2021) and present a research agenda that addresses the challenges and opportunities artificial intelligence and machine learning bring to car insurance fraud detection.

Design/methodology/approach

Content analysis methodology is used to analyze 46 peer-reviewed academic papers from 31 journals plus eight conference proceedings to identify their research themes and detect trends and changes in the automobile insurance fraud detection literature according to content characteristics.

This study found that automobile insurance fraud detection is going through a transformation, where traditional statistics-based detection methods are replaced by data mining- and artificial intelligence-based approaches. In this study, it was also noticed that cost-sensitive and hybrid approaches are the up-and-coming avenues for further research.

Practical implications

This paper’s findings not only highlight the rise and benefits of data mining- and artificial intelligence-based automobile insurance fraud detection but also highlight the deficiencies observable in this field such as the lack of cost-sensitive approaches or the absence of reliable data sets.

Originality/value

This paper offers greater insight into how artificial intelligence and data mining challenges traditional automobile insurance fraud detection models and addresses the need to develop new cost-sensitive fraud detection methods that identify new real-world data sets.

  • Literature review
  • Data mining
  • Automobile insurance fraud detection

Benedek, B. , Ciumas, C. and Nagy, B.Z. (2022), "Automobile insurance fraud detection in the age of big data – a systematic and comprehensive literature review", Journal of Financial Regulation and Compliance , Vol. 30 No. 4, pp. 503-523. https://doi.org/10.1108/JFRC-11-2021-0102

Emerald Publishing Limited

Copyright © 2022, Emerald Publishing Limited

Related articles

All feedback is valuable.

Please share your general feedback

Report an issue or find answers to frequently asked questions

Contact Customer Support

Information

  • Author Services

Initiatives

You are accessing a machine-readable page. In order to be human-readable, please install an RSS reader.

All articles published by MDPI are made immediately available worldwide under an open access license. No special permission is required to reuse all or part of the article published by MDPI, including figures and tables. For articles published under an open access Creative Common CC BY license, any part of the article may be reused without permission provided that the original article is clearly cited. For more information, please refer to https://www.mdpi.com/openaccess .

Feature papers represent the most advanced research with significant potential for high impact in the field. A Feature Paper should be a substantial original Article that involves several techniques or approaches, provides an outlook for future research directions and describes possible research applications.

Feature papers are submitted upon individual invitation or recommendation by the scientific editors and must receive positive feedback from the reviewers.

Editor’s Choice articles are based on recommendations by the scientific editors of MDPI journals from around the world. Editors select a small number of articles recently published in the journal that they believe will be particularly interesting to readers, or important in the respective research area. The aim is to provide a snapshot of some of the most exciting work published in the various research areas of the journal.

Original Submission Date Received: .

  • Active Journals
  • Find a Journal
  • Proceedings Series
  • For Authors
  • For Reviewers
  • For Editors
  • For Librarians
  • For Publishers
  • For Societies
  • For Conference Organizers
  • Open Access Policy
  • Institutional Open Access Program
  • Special Issues Guidelines
  • Editorial Process
  • Research and Publication Ethics
  • Article Processing Charges
  • Testimonials
  • Preprints.org
  • SciProfiles
  • Encyclopedia

risks-logo

Article Menu

research paper auto insurance

  • Subscribe SciFeed
  • Recommended Articles
  • Google Scholar
  • on Google Scholar
  • Table of Contents

Find support for a specific problem in the support section of our website.

Please let us know what you think of our products and services.

Visit our dedicated information section to learn more about MDPI.

JSmol Viewer

Exploring industry-level fairness of auto insurance premiums by statistical modeling of automobile rate and classification data.

research paper auto insurance

1. Introduction

2. materials and methods, 2.1. background and data, 2.2. risk relativity estimates by generalized linear models, 2.3. distance measures for comparing premiums and loss costs, 2.4. modeling fixed effect using loss costs and premiums, 2.4.1. comparing loss costs and premiums within same territory, 2.4.2. comparing loss costs and premiums between territories, 4. conclusions, author contributions, data availability statement, conflicts of interest.

  • Abraham, Kenneth S. 1985. Efficiency and fairness in insurance risk classification. Virginia Law Review , 403–51. [ Google Scholar ] [ CrossRef ]
  • Arora, Nidhi, and Poonam Arora. 2014. Insurance Premium Optimization: Perspective of Insurance Seeker and Insurance Provider. Journal of Management and Science 4: 43–53. [ Google Scholar ] [ CrossRef ]
  • Avraham, Ronen. 2017. Discrimination and Insurance. The Routledge Handbook to Discrimination Lippert-Rasmussen Ed, University of Texas Law, Law and Econ Research Paper No. E574. Available online: https://ssrn.com/abstract=3089946 or http://dx.doi.org/10.2139/ssrn.3089946 (accessed on 4 July 2022).
  • Barry, Laurence. 2020. Insurance, big data and changing conceptions of fairness. European Journal of Sociology/Archives Européennes de Sociologie 61: 159–84. [ Google Scholar ] [ CrossRef ]
  • Berry-Stölzle, Thomas R., and Patricia Born. 2012. The effect of regulation on insurance pricing: The case of Germany. Journal of Risk and Insurance 79: 129–64. [ Google Scholar ] [ CrossRef ]
  • Cao, Longbing, Qiang Yang, and Philip S. Yu. 2021. Data science and AI in FinTech: An overview. International Journal of Data Science and Analytics 12: 81–99. [ Google Scholar ] [ CrossRef ]
  • Charpentier, Arthur, Laurence Barry, and Molly R. James. 2022. Insurance against natural catastrophes: Balancing actuarial fairness and social solidarity. The Geneva Papers on Risk and Insurance-Issues and Practice 47: 50–78. [ Google Scholar ] [ CrossRef ]
  • Chiappori, Pierre-André, Bruno Jullien, Bernard Salanié, and François Salanié. 2006. Asymmetric information in insurance: General testable implications. The RAND Journal of Economics 37: 783–98. [ Google Scholar ] [ CrossRef ]
  • Cohen, Alma. 2005. Asymmetric information and learning: Evidence from the automobile insurance market. Review of Economics and Statistics 87: 197–207. [ Google Scholar ] [ CrossRef ]
  • Cummins, J. David, and Mary A. Weiss. 1992. Regulation and the Automobile Insurance Crisis. Regulation 15: 48. [ Google Scholar ]
  • Dugas, Charles, Yoshua Bengio, Nicolas Chapados, Pascal Vincent, Germain Denoncourt, and Christian Fournier. 2003. Statistical learning algorithms applied to automobile insurance ratemaking. In CAS Forum . Arlington: Casualty Actuarial Society, Vol. 1, pp. 179–214. [ Google Scholar ]
  • Ferreira, Joseph, Jr., and Eric Minikel. 2012. Measuring per mile risk for pay-as-you-drive automobile insurance. Transportation Research Record 2297: 97–103. [ Google Scholar ] [ CrossRef ] [ Green Version ]
  • Frees, Edward W., and Fei Huang. 2021. The discriminating (pricing) actuary. North American Actuarial Journal , 1–23. [ Google Scholar ] [ CrossRef ]
  • Frezal, Sylvestre, and Laurence Barry. 2020. Fairness in uncertainty: Some limits and misinterpretations of actuarial fairness. Journal of Business Ethics 167: 127–36. [ Google Scholar ] [ CrossRef ]
  • Grabowski, Henry, W. Kip Viscusi, and William N. Evans. 1989. Price and availability tradeoffs of automobile insurance regulation. Journal of Risk and Insurance 56: 275–99. [ Google Scholar ] [ CrossRef ]
  • Hanafy, Mohamed, and Ruixing Ming. 2021. Machine learning approaches for auto insurance big data. Risks 9: 42. [ Google Scholar ] [ CrossRef ]
  • Isotupa, K. P. Sapna, Mary Kelly, and Anna Kleffner. 2019. Experience-rating mechanisms in auto insurance: Implications for high-risk, low-risk, and novice drivers. North American Actuarial Journal 23: 395–411. [ Google Scholar ] [ CrossRef ]
  • Landes, Xavier. 2015. How fair is actuarial fairness? Journal of Business Ethics 128: 519–33. [ Google Scholar ] [ CrossRef ] [ Green Version ]
  • Liu, Lixin, Wenzhuo Li, Wu He, and Justin Zuopeng Zhang. 2022. Improve enterprise knowledge management with internet of things: A case study from auto insurance industry. Knowledge Management Research & Practice 20: 58–72. [ Google Scholar ]
  • Medders, Lorilee A., Jamie A. Parson, and Matthew Thomas-Reid. 2021. Gender X and Auto Insurance: Is Gender Rating Unfairly Discriminatory? Journal of Insurance Regulation 40: 1–31. [ Google Scholar ] [ CrossRef ]
  • Meyers, Gert, and Ine Van Hoyweghen. 2018. Enacting actuarial fairness in insurance: From fair discrimination to behaviour-based fairness. Science as Culture 27: 413–38. [ Google Scholar ] [ CrossRef ]
  • Regan, Laureen, Sharon Tennyson, and Mary Weiss. 2008. The Relationship Between Auto Insurance Rate Regulation and Insured Loss Costs: An Empirical Analysis. Journal of Insurance Regulation 27. [ Google Scholar ]
  • Ronka-Chmielowiec, Wanda, and Ewa Poprawska. 2005. Selected Methods of Credibility Theory and its Application to Calculating Insurance Premium in Heterogeneous Insurance Portfolios. In Innovations in Classification, Data Science, and Information Systems . Berlin and Heidelberg: Springer, pp. 490–97. [ Google Scholar ]
  • Ryan, Stephen R. 1986. Elimination of Gender Discrimination in Insurance Pricing: Does Automobile Insurance Rate Without Sex. Notre Dame L. Rev. 61: 748. [ Google Scholar ]
  • Saito, Kuniyoshi. 2006. Testing for asymmetric information in the automobile insurance market under rate regulation. Journal of Risk and Insurance 73: 335–56. [ Google Scholar ] [ CrossRef ]
  • Schmeiser, Hato, Tina Störmer, and Joël Wagner. 2014. Unisex insurance pricing: Consumers’ perception and market implications. The Geneva Papers on Risk and Insurance-Issues and Practice 39: 322–50. [ Google Scholar ] [ CrossRef ] [ Green Version ]
  • Sud, Keshav, Pakize Erdogmus, and Seifedine Kadry, eds. 2020. Introduction to Data Science and Machine Learning . Norderstedt: BoD–Books on Demand. [ Google Scholar ]
  • Thiery, Yves, and Caroline Van Schoubroeck. 2006. Fairness and equality in insurance classification. The Geneva Papers on Risk and Insurance-Issues and Practice 31: 190–211. [ Google Scholar ] [ CrossRef ]
  • Xin, Xi, and Fei Huang. 2022. Anti-Discrimination Insurance Pricing: Regulations, Fairness Criteria, and Models. Fairness Criteria, and Models . Available online: https://ssrn.com/abstract=3850420 (accessed on 4 July 2022). [ CrossRef ]
  • Zahi, Jamal. 2021. Non-life insurance ratemaking techniques. International Journal of Accounting, Finance, Auditing, Management and Economics 2: 344–61. [ Google Scholar ]

Click here to enlarge figure

CLASS1$858$873$546$440$863$502$318$1381$1237$1074$985$949$580$440
CLASS2$1119$915$840$732$703$444$305$1824$1591$1428$1295$1115$810$526
CLASS3$813$615$568$1085$630$309$305$1714$1502$1342$1207$1097$787$521
CLASS5$56$68$61$162$104$56$88$193$162$147$130$114$93$80
CLASS6$62$49$76$59$517$75$208$389$332$317$313$258$199$199
CLASS7$270$389$237$650$537$305$243$1410$1571$1323$1510$1102$678$503
CLASS8$3966$ -$413$634$ -$ -NA$1600$1258$1364$1153$877$1001
CLASS9$1678$2036$1495$2082$213$350$389$1673$1482$1445$1301$1117$887$658
CLASS10$397$1049$465$1138$311NANA$1701$1363$1158$1184$1937
CLASS11$6096$467$590$317$140$150NA$1767$1540$1425$1120$909$1298
CLASS12$383$545$823$641$204$119$1412$1795$1475$1357$1175$1046$818$721
CLASS13$974$846$797$725$251$360$217$1826$1600$1343$1233$1078$897$680
CLASS18$886$558$465$522$367$168NA$1429$1239$1118$989$865$879
CLASS19$750$742$724$462$441$303$496$1549$1369$1207$1034$950$762$651
CLASS1$193$460$440$342$1129$229$169$865$756$649$582$533$422$259
CLASS2$466$582$896$811$868$211$222$1183$975$843$776$650$512$307
CLASS3$680$604$313$436$353$292$238$1213$990$878$835$713$551$352
CLASS5$54$59$238$29$2$0$69$142$116$100$80$67$56$47
CLASS6$27$9$33$314$ -$6$54$347$291$253$229$187$149$137
CLASS7$14$25$188$11$537$146$111$995$1018$836$855$716$515$342
CLASS8$ -$ -$ -$91$ -$ -NA$1570$1153$1072$840$700$753
CLASS9$621$ -$366$192$253$44$371$1319$1042$935$829$731$572$436
CLASS10$852$99$119$196$ -NANA$1491$1120$1023$838$1535
CLASS11$510$102$2149$1036$61$50NA$1797$1429$1241$833$691$866
CLASS12$607$169$237$3255$139$1362$196$1702$1345$1165$898$825$595$509
CLASS13$404$22$554$11$273$77$145$1711$1245$1055$913$796$688$469
CLASS18$4215$300$137$336$136$109NA$1206$1052$935$770$698$705
CLASS19$586$684$365$1317$385$449$313$1167$966$833$707$660$561$454
200920102011
GammaPoissonGammaPoissonGammaPoisson
AB
Rural
DR0.300.120.060.060.120.17
CLASS0.180.160.160.160.170.16
Urban
DR0.050.050.060.040.080.04
CLASS0.230.210.210.170.080.07
Rural
DR0.260.220.120.110.120.11
CLASS0.110.110.100.110.160.16
Urban
DR0.020.020.120.110.060.02
CLASS0.090.090.070.060.050.05
Rural
DR0.050.060.040.030.080.02
CLASS0.070.070.200.180.090.06
Urban
DR0.050.040.050.050.030.01
CLASS0.190.190.130.100.080.06
GaussianPoissonGamma
TermEstimateStandardStatisticp-ValueLossEstimate Standard Statistic p-ValueLoss Estimate Standard Statistic p-ValueLoss
Error Relativity Error Relativity Error Relativity
(Intercept)6.790.05147.230.00 6.790.0057,577.370.00 6.750.1161.100.00
DR00.00 1.540.00 1.530.00 1.57
DR1−0.210.05−4.330.001.25−0.210.00−1412.510.001.25−0.220.14−1.620.111.26
DR2−0.360.05−7.530.001.07−0.350.00−2490.090.001.09−0.270.13−2.130.031.20
DR3−0.430.04−9.820.001.00−0.430.00−3359.130.001.00−0.450.12−3.860.001.00
DR4−0.600.05−11.730.000.85−0.580.00−4188.700.000.86−0.550.13−4.410.000.91
DR5−0.930.04−20.800.000.61−0.910.00−7455.190.000.62−0.870.11−7.610.000.66
DR6−1.370.04−36.680.000.39−1.350.00−12,133.800.000.40−1.300.11−11.910.000.43
CLASS10.00 0.850.00 0.860.00 0.86
CLASS20.160.027.480.001.000.160.004200.700.001.000.150.027.470.001.00
CLASS30.000.040.070.940.850.050.00810.880.000.900.090.042.560.010.94
CLASS5−2.170.35−6.230.000.10−2.110.00−7428.640.000.10−2.010.09−23.330.000.12
CLASS6−1.490.16−9.370.000.19−1.420.00−7674.170.000.21−1.290.08−16.340.000.24
CLASS7−0.120.07−1.630.100.76−0.070.00−629.560.000.80−0.050.06−0.860.390.81
CLASS80.790.213.850.001.880.680.00871.210.001.700.590.870.670.501.54
CLASS90.470.114.450.001.360.430.001497.780.001.320.400.231.800.071.29
CLASS100.160.091.750.081.000.180.00746.470.001.020.250.211.240.221.11
CLASS110.140.072.010.050.980.160.00900.320.001.000.220.151.510.131.07
CLASS120.200.063.260.001.040.270.001891.160.001.120.410.113.610.001.29
CLASS130.210.063.320.001.050.250.001719.570.001.100.280.102.740.011.14
CLASS18−0.110.07−1.530.130.76−0.060.00−385.790.000.810.030.120.240.810.88
CLASS190.040.050.690.490.880.100.00933.660.000.950.200.072.670.011.05
Fixed Effect0.030.021.850.07 −0.030.00−789.060.00 −0.080.02−4.480.00
Territory0.610.0323.330.00 0.620.0015,838.140.00 0.640.0233.160.00
GaussianPoissonGamma
TermEstimateStandardStatisticp-ValueLossEstimateStandardStatisticp-ValueLossEstimateStandardStatisticp-ValueLoss
Error Relativity Error Relativity Error Relativity
(Intercept)5.970.04152.220.00 5.940.0053,997.660.00 5.920.0878.420.00
DR00.00 1.490.00 1.490.00 1.51
DR1−0.150.04−3.290.001.29−0.140.00−1049.440.001.29−0.150.09−1.620.111.29
DR2−0.210.04−4.870.001.22−0.210.00−1641.890.001.20−0.230.09−2.610.011.19
DR3−0.400.04−10.060.001.00−0.400.00−3338.020.001.00−0.410.08−5.080.001.00
DR4−0.550.05−11.520.000.87−0.550.00−4140.260.000.86−0.550.09−6.410.000.87
DR5−0.760.04−18.390.000.70−0.760.00−6575.990.000.70−0.770.08−9.800.000.70
DR6−1.060.03−30.240.000.52−1.050.00−10,009.820.000.52−1.050.07−14.180.000.53
CLASS10.00 0.890.00 0.920.00 0.93
CLASS20.110.026.190.001.000.090.002582.050.001.000.070.014.690.001.00
CLASS30.140.034.880.001.030.150.002710.720.001.060.160.026.450.001.10
CLASS5−1.420.17−8.180.000.22−1.390.00−6840.650.000.23−1.360.06−22.130.000.24
CLASS6−0.720.08−9.080.000.43−0.710.00−5235.600.000.45−0.650.06−11.630.000.49
CLASS70.260.045.870.001.150.250.002805.290.001.180.240.045.560.001.19
CLASS80.420.291.430.151.350.390.00439.090.001.350.360.610.590.551.34
CLASS90.500.105.100.001.460.480.001823.170.001.480.460.162.890.001.48
CLASS100.840.0516.120.002.060.850.004870.390.002.140.870.146.020.002.23
CLASS110.630.0514.030.001.680.640.004665.350.001.740.670.106.550.001.83
CLASS120.610.0414.540.001.640.650.005553.230.001.750.720.088.950.001.92
CLASS130.500.0510.790.001.480.500.004169.580.001.520.510.077.060.001.56
CLASS180.250.054.990.001.150.270.001989.330.001.200.300.083.530.001.26
CLASS190.220.045.130.001.110.230.002371.560.001.150.260.054.920.001.21
Fixed Effect−0.220.02−14.490.00 −0.210.00−7273.300.00 −0.210.01−16.430.00
Territory0.290.0216.630.00 0.340.0010,279.170.00 0.370.0127.070.00
GaussianPoissonGamma
TermEstimateStandardStatisticp-Value LossEstimateStandardStatisticp-Value LossEstimateStandardStatisticp-Value Loss
Error Relativity Error Relativity Error Relativity
(Intercept)6.120.03224.610.00 6.110.0021,740.800.00 6.100.0788.680.00
DR00.00 1.320.00 1.310.00 1.34
DR1−0.080.03−2.460.011.22−0.070.00−192.630.001.23−0.050.09−0.570.571.27
DR2−0.230.03−7.100.001.05−0.240.00−706.650.001.03−0.260.08−3.190.001.03
DR3−0.280.03−9.740.001.00−0.270.00−890.900.001.00−0.290.07−3.960.001.00
DR4−0.410.03−12.550.000.88−0.410.00−1242.490.000.87−0.440.08−5.570.000.86
DR5−0.530.03−19.130.000.78−0.530.00−1840.770.000.77−0.530.07−7.480.000.79
DR6−0.900.03−34.840.000.54−0.910.00−3301.030.000.53−0.900.07−13.290.000.54
CLASS10.00 0.900.00 0.910.00 0.92
CLASS20.110.0110.060.001.000.090.001348.340.001.000.080.017.250.001.00
CLASS30.170.0210.770.001.060.180.001620.740.001.090.190.029.960.001.11
CLASS5−1.330.08−15.890.000.24−1.270.00−3424.250.000.26−1.160.05−25.490.000.29
CLASS6−0.630.04−16.000.000.48−0.640.00−2476.690.000.48−0.610.04−14.440.000.50
CLASS70.280.0211.950.001.200.270.001505.800.001.190.260.037.850.001.19
CLASS80.820.174.920.002.040.840.00390.000.002.100.880.691.270.212.21
CLASS90.590.069.790.001.630.610.001011.070.001.670.630.144.350.001.72
CLASS101.000.0423.460.002.461.000.001706.970.002.471.020.205.020.002.56
CLASS110.840.0327.230.002.090.830.002175.640.002.080.840.127.090.002.13
CLASS120.740.0327.230.001.880.740.002520.960.001.910.770.089.590.001.98
CLASS130.730.0327.270.001.860.740.002750.600.001.910.750.0711.280.001.96
CLASS180.480.0315.610.001.460.490.001520.960.001.480.520.086.250.001.55
CLASS190.440.0219.860.001.400.470.002365.800.001.450.500.0411.490.001.52
Fixed Effect−0.500.01−52.270.00 −0.500.00−7957.490.00 −0.500.01−48.620.00
Territory0.110.0112.030.00 0.130.002033.710.00 0.150.0114.220.00
200920102011
GaussianPoissonGammaInverseGaussianPoissonGammaInverseGaussianPoissonGammaInverse
Gaussian Gaussian Gaussian
AB
Rural
DR1.241.221.211.201.441.451.451.451.411.421.441.45
CLASS1.321.241.201.221.511.461.461.641.401.451.491.52
Urban
DR0.700.710.710.730.820.830.840.861.651.631.621.62
CLASS0.690.700.700.710.800.820.830.831.621.601.591.58
TPL
Rural
DR1.401.441.461.481.321.321.321.331.281.301.321.33
CLASS1.451.461.441.421.351.321.311.291.261.331.351.36
Urban
DR1.401.441.461.481.151.161.171.171.331.291.271.26
CLASS1.141.131.121.101.151.141.131.121.321.291.271.25
COL
Rural
DR1.821.831.841.851.821.841.861.861.681.691.701.70
CLASS1.841.821.801.781.841.831.821.811.661.671.671.66
Urban
DR1.651.661.661.671.611.621.621.631.561.551.551.54
CLASS1.641.641.631.611.611.601.591.581.541.531.531.51
200920102011
GaussianPoissonGammaInverseGaussianPoissonGammaInverseGaussianPoissonGammaInverse
Gaussian Gaussian Gaussian
AB
Rural
Fixed Effect1.301.231.21NA1.431.451.48NA1.361.441.49NA
Urban
Fixed Effect0.670.700.720.740.780.820.840.841.651.621.601.59
TPL
Rural
Fixed Effect1.401.451.471.461.341.321.311.311.231.321.361.38
Urban
Fixed Effect1.141.141.121.101.141.151.151.131.351.291.261.24
Rural
Fixed Effect1.831.821.811.801.811.821.831.821.641.671.67NA
Urban
Fixed Effect1.631.641.641.621.591.601.601.581.541.541.521.50
Average Effect1.231.241.24NA1.231.241.24NA1.401.401.39NA
200920102011
GaussianPoissonGammaInverseGaussianPoissonGammaInverseGaussianPoissonGammaInverse
Gaussian Gaussian Gaussian
AB
Rural
Fixed Effect0.720.790.86NA0.840.931.02NA1.611.571.55NA
Urban
Fixed Effect1.541.601.71NA1.711.852.08NA2.442.452.47NA
TPL
Rural
Fixed Effect1.201.211.230.981.181.201.201.201.331.301.291.28
Urban
Fixed Effect1.701.791.891.001.621.681.711.741.661.741.801.84
COL
Rural
Fixed Effect1.691.701.701.691.661.671.681.681.571.581.571.56
Urban
Fixed Effect1.891.941.971.981.861.931.982.021.751.791.821.83
Average Effect1.501.561..63NA1.501.551.61NA1.691.721.75NA
Two-Way CombinedThree-Way Combined
GaussianPoissonGammaGaussianPoissonGamma
AB
Rural
Fixed Effect (CLASS&DR)1.381.371.370.971.031.09
Urban
Fixed Effect (CLASS&DR)0.910.940.951.781.902.06
Rural
Fixed Effect (CLASS&DR)1.341.361.371.241.241.24
Urban
Fixed Effect (CLASS&DR)1.211.191.171.661.731.79
Rural
Fixed Effect (CLASS&DR)1.761.771.771.641.651.65
Urban
Fixed Effect (CLASS&DR)1.591.591.581.831.881.92
Average Fixed Effect1.281.281.271.541.601.65
MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Share and Cite

Xie, S.; Luo, R.; Li, Y. Exploring Industry-Level Fairness of Auto Insurance Premiums by Statistical Modeling of Automobile Rate and Classification Data. Risks 2022 , 10 , 194. https://doi.org/10.3390/risks10100194

Xie S, Luo R, Li Y. Exploring Industry-Level Fairness of Auto Insurance Premiums by Statistical Modeling of Automobile Rate and Classification Data. Risks . 2022; 10(10):194. https://doi.org/10.3390/risks10100194

Xie, Shengkun, Rebecca Luo, and Yuanshun Li. 2022. "Exploring Industry-Level Fairness of Auto Insurance Premiums by Statistical Modeling of Automobile Rate and Classification Data" Risks 10, no. 10: 194. https://doi.org/10.3390/risks10100194

Article Metrics

Article access statistics, further information, mdpi initiatives, follow mdpi.

MDPI

Subscribe to receive issue release notifications and newsletters from MDPI journals

Advertisement

Advertisement

A data science approach to risk assessment for automobile insurance policies

  • Regular Paper
  • Published: 22 March 2023
  • Volume 17 , pages 127–138, ( 2024 )

Cite this article

research paper auto insurance

  • Patrick Hosein 1  

531 Accesses

7 Citations

1 Altmetric

Explore all metrics

In order to determine a suitable automobile insurance policy premium, one needs to take into account three factors: the risk associated with the drivers and cars on the policy, the operational costs associated with management of the policy and the desired profit margin. The premium should then be some function of these three values. We focus on risk assessment using a data science approach. Instead of using the traditional frequency and severity metrics, we instead predict the total claims that will be made by a new customer using historical data of current and past policies. Given multiple features of the policy (age and gender of drivers, value of car, previous accidents, etc.), one can potentially try to provide personalized insurance policies based specifically on these features as follows. We can compute the average claims made per year of all past and current policies with identical features and then take an average over these claim rates. Unfortunately there may not be sufficient samples to obtain a robust average. We can instead try to include policies that are “similar” to obtain sufficient samples for a robust average. We therefore face a trade-off between personalization (only using closely similar policies) and robustness (extending the domain far enough to capture sufficient samples). This is known as the bias–variance trade-off. We model this problem and determine the optimal trade-off between the two (i.e., the balance that provides the highest prediction accuracy) and apply it to the claim rate prediction problem. We demonstrate our approach using real data.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Subscribe and save.

  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime

Price includes VAT (Russian Federation)

Instant access to the full article PDF.

Rent this article via DeepDyve

Institutional subscriptions

research paper auto insurance

Similar content being viewed by others

research paper auto insurance

Risk Assessment for Personalized Health Insurance Products

research paper auto insurance

A “pay-how-you-drive” car insurance approach through cluster analysis

research paper auto insurance

Improving automobile insurance ratemaking using telematics: incorporating mileage and driver behaviour data

Availability of data and materials.

The data used for this publication are confidential, and hence, we are only permitted to provide results but cannot share the data.

Code Availability

The code used to generate results is also proprietary to the company, but we hope that our pseudo-code can be used if one wishes to apply the model to their datasets.

Albrecher, H., Bommier, A., Filipović, D., et al.: Insurance: models, digitalization, and data science. Eur. Actuar. J. 9 , 349–360 (2019)

Article   MathSciNet   Google Scholar  

Bian, Y., Yang, C., Zhao, J.L., et al.: Good drivers pay less: a study of usage-based vehicle insurance models. Transp. Res. A: Policy Pract. 107 , 20–34 (2018). https://doi.org/10.1016/j.tra.2017.10.018

Article   Google Scholar  

David, M., Jemna, D.V.: Modeling the frequency of auto insurance claims by means of poisson and negative binomial models. Analele stiintifice ale Universitatii “Al I Cuza” din Iasi Stiinte economice/Scientific Annals of the“ Al I Cuza” (2015)

Denuit, M., Trufin, J.: Effective Statistical Learning Methods for Actuaries. Springer Actuarial Lecture Notes (2019)

Errais, E.: Pricing insurance premia: a top down approach. Annals of Operations Research, pp. 1–16 (2019)

Esfandabadi, Z.S., Ranjbari, M., Scagnelli, S.D.: (0) Prioritizing risk-level factors in comprehensive automobile insurance management: A hybrid multi-criteria decision-making model. Glob. Bus. Rev. https://doi.org/10.1177/0972150920932287 ,

Guelman, L.: Gradient boosting trees for auto insurance loss cost modeling and prediction. Expert Syst. Appl. 39 (3), 3659–3667 (2012)

Hanafy, M., Ming, R.: Machine learning approaches for auto insurance big data. Risks 9 (2), 42 (2021)

Hassani, H., Unger, S., Beneki, C.: Big data and actuarial science. Big Data Cogn. Comput. 4 , 40 (2020)

He, B., Zhang, D., Liu, S., et al.: Profiling driver behavior for personalized insurance pricing and maximal profit. In: 2018 IEEE International Conference on Big Data (Big Data), pp. 1387–1396. https://doi.org/10.1109/BigData.2018.8622491 (2018)

Hosein, P.: On the prediction of automobile insurance claims: the personalization versus confidence trade-off. In: 2021 IEEE International Conference on Technology Management, pp. 1–6. Operations and Decisions (ICTMOD), IEEE (2021)

Hosein, P., Rahaman, I., Nichols, K., et al.: Recommendations for long-term profit optimization. In: ImpactRS@ RecSys (2019)

Jeong, H., Valdez, E.A.: Predictive compound risk models with dependence. Insurance Math. Econom. 94 , 182–195 (2020)

Kanchinadam, T., Qazi, M., Bockhorst, J., et al.: Using discriminative graphical models for insurance recommender systems. In: 2018 17th IEEE International Conference on Machine Learning and Applications (ICMLA), pp. 421–428 (2018). https://doi.org/10.1109/ICMLA.2018.00069

Liu, Y., Wang, B.J., Lv, S.G.: Using multi-class adaboost tree for prediction frequency of auto insurance. J. Appl. Finance Bank. 4 (5), 45 (2014)

Google Scholar  

Lundberg, S.M., Lee, S.I.: A unified approach to interpreting model predictions. In: Guyon, I., Luxburg, U.V., Bengio, S., et al. (Eds.) Advances in Neural Information Processing Systems, vol 30. Curran Associates, Inc (2017). https://proceedings.neurips.cc/paper/2017/file/8a20a8621978632d76c43dfd28b67767-Paper.pdf

Qazi, M., Fung, G.M., Meissner, K.J., et al.: An insurance recommendation system using bayesian networks. In: Proceedings of the Eleventh ACM Conference on Recommender Systems. Association for Computing Machinery, New York, NY, USA, RecSys ’17, pp. 274–278 (2017). https://doi.org/10.1145/3109859.3109907

Qazi, M., Tollas, K., Kanchinadam, T., et al.: Designing and deploying insurance recommender systems using machine learning. WIREs Data Min. Knowl. Discovery 10 (4), e1363 (2020). https://doi.org/10.1002/widm.1363

Su, X., Bai, M.: Stochastic gradient boosting frequency-severity model of insurance claims. PLoS ONE 15 (8), e0238000 (2020)

Zhang, Y., Dukic, V.: Predicting multivariate insurance loss payments under the bayesian copula framework. J. Risk Insurance 80 (4), 891–919 (2013)

Download references

The authors did not receive support from any organization for the submitted work.

Author information

Authors and affiliations.

Department of Computer Science, The University of the West Indies, St. Augustine, Trinidad and Tobago

Patrick Hosein

You can also search for this author in PubMed   Google Scholar

Contributions

The sole author performed the research, wrote the code for evaluating the solution and wrote the entire paper

Corresponding author

Correspondence to Patrick Hosein .

Ethics declarations

Conflict of interest.

The authors have no conflicts of interest to declare that are relevant to the content of this article.

Ethics approval

Not applicable.

Consent to participate

Consent for publication, additional information, publisher's note.

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Hosein, P. A data science approach to risk assessment for automobile insurance policies. Int J Data Sci Anal 17 , 127–138 (2024). https://doi.org/10.1007/s41060-023-00392-x

Download citation

Received : 13 September 2022

Accepted : 05 March 2023

Published : 22 March 2023

Issue Date : January 2024

DOI : https://doi.org/10.1007/s41060-023-00392-x

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

  • Motor insurance
  • Machine learning
  • Premium pricing
  • Claims prediction

Mathematics subject classification

  • Find a journal
  • Publish with us
  • Track your research
  • Insights and Resources
  • White Paper
  • Auto Insurance Trends Report

LexisNexis® U.S. Auto Insurance Trends Report

Top 5 auto insurance trends to watch.

The annual LexisNexis® Risk Solutions U.S. Auto Insurance Trends Report explores key trends from the previous year and offers insights to help insurers make more informed business decisions. This year, we identified five trends impacting U.S. consumer auto insurance shopping, claims, driving violations and more.

As U.S. auto insurers steer through the challenges of the current market, these trends offer insights to help navigate the road ahead. Insurers can leverage proprietary and industry consortium data to help gain a clearer view of performance benchmarks and plan for the road ahead.

research paper auto insurance

Access the report to explore :

  • High claim severities show little signs of slowing down 
  • Insurers take aggressive steps to address profitability challenges 
  • Consumers respond to market conditions by shopping and switching auto policies
  • Risky driving behavior persists
  • As electric vehicle sales grow, so do insurance risks

Access the report now

We appreciate your interest.

Explore each section to gain additional insights 

High claim severities show little signs of slowing down.

research paper auto insurance

  • Sustained rise in claims severity
  • Increase in uninsured motorist and attorney-represented claims
  • Total loss claims
  • Length of repair times
  • Rising costs of medical bills, towing services and storage costs

Trend Details

Both the severity and frequency of claims, including severe auto physical damage and bodily injury, have increased since 2020. Bodily injury severity has increased 20% in the post-pandemic years.

More than a quarter of collision claims were deemed total losses in 2023. While that percentage is the same as the previous year, total loss claims have jumped 29% since 2020.

More claimants are seeking advice from attorneys before settling. In fact, according to our 2023 survey, a majority of claimants who hired an attorney for their last claim would most likely do so again. 

Consumers respond sharply to market conditions by shopping and switching auto policies 

As rate increases went into effect throughout 2023, many consumers reacted by shopping for lower policy prices. Many of those who shopped for lower rates ended up switching insurers, resulting in new policy growth of 6.2% last year.

research paper auto insurance

Source: LexisNexis Risk Solutions Insurance Demand Meter

Get the latest auto insurance shopping trend data in our quarterly report.

Insurance Demand Meter

Driving behavior continues to change dramatically

As miles driven returned to 2019 levels in 2023, moving and non-moving violations returned as well. In fact, all driving violations have increased 4% from 2022 to 2023. Speeding, distracted driving and DUIs all increased year over year, resulting in escalating risk profiles. Get additional details in this blog post .

Both major and minor speeding violations continue to rise, consistent with the post-pandemic trend.

research paper auto insurance

Unlike other violations, DUIs take longer to move through the court system, so they can be a lagging metric. Comparing the first six months of 2022 to the first six months of 2023, DUI violations increase 8%. Our latest driving violations blog  dives into current unsafe driving trends.

Distracted Driving

Distracted driving violations continue to rise as people return to the roads. Younger drivers continue to be the more susceptible problematic age group when it comes to increases in distracted driving. This increase in violations, plus Gen Z’s inexperience compared to other generations, has implications for both personal lines and commercial lines insurers. Read more in our latest blog article .

Access the Report

Download previous lexisnexis® u.s. auto insurance trends reports.

2023 Auto Insurance Trends Report

2022 auto insurance trends report, 2021 auto insurance trends report .

Academia.edu no longer supports Internet Explorer.

To browse Academia.edu and the wider internet faster and more securely, please take a few seconds to  upgrade your browser .

Enter the email address you signed up with and we'll email you a reset link.

  • We're Hiring!
  • Help Center

paper cover thumbnail

A Study on Customer Awareness on Car Insurance Policies with Special Reference to

Profile image of IJIRST - International Journal for Innovative Research in Science and Technology

Purpose: The purpose of this study is to understand the customer awareness on car insurance policies with special reference to United India Insurance with the important element to improve the customer awareness towards insurance policies based on literature review and case study of successful vehicle Insurance Company. This study mainly focused on customer's awareness and satisfaction level on the car insurance policies offered by the company. Research Design: This research study is mainly based on the method of probability sampling with random sampling techniques, this research study is conducted within shivamogga city with the sample size of 150 respondents from the Primary data which is collected through structured questionnaire as a sample tool for the information's assembly, secondary data is collected by the magazine, journals of the marketing, articles and books, Findings: From the study came to know that respondents or policy holders are not aware about the terms and conditions, procedures of claiming during the time of damage or loss of the insurance policy offered by the company. Results: United India Insurance Corporation is a well-known insurance organization in the field of vehicle insurance Business which is a leading insurance sectors in providing service to the customers and customers are well satisfied with the price of the insurance policies offered by the united India insurance organization to the customers. Conclusion: From this study it is cleared that most of the policy holders are not aware about the procedures, terms and conditions, policies premium calculation procedure based on vehicle ID value, age, model etc. The concept of car insurance policies is very much needed aspects to the people who have owned a car, having car insurance policies makes the customers feel protected from the loss or damage if caused by the accident.

Related Papers

Journal of emerging technologies and innovative research

Josephine Stella A.

Motor insurance contributes to one third of the premium income for the General Insurance industry in India. The growth of the economy and consequently, the standard of living of the people, further supported by the increased choice for the customer and entry of large number of automobile players led to a sharp increase in motor insurance. The main aim of the motor insurance is to protect the people from the loss arising out of accident. It covers loss made vehicle. The awareness of the people towards Insurance is low in India generally it is very difficult to create the buying attitude among the prospective buyers towards the different kinds of insurance. The General Insurance Corporation finds it difficult to identify and to make the clients believe the concepts of Insurance Policy. At the same time, the policy will be valued for only one year. The lack of insurance awareness is the main problem in general insurance particularly in motor insurance. Vehicle owners buy it only on the...

research paper auto insurance

International Journal of Research in Commerce and Management

Dhiraj Jain

vikas kumar gautam

International Journal of Management, Technology, and Social Sciences (IJMTS)

Srinivas Publication , Swati Basu Ghose

The primary purpose of vehicle insurance is to cover the vehicle against damage, personal injury, and third-party liability. In addition to this, some insurance companies also provide value-added services such as roadside assistance and other services in return of the amount called as premium which attracts a large number of customers. However, our study shows that vehicle owners give maximum importance to the cost of insurance in terms of the annual premium. Primary data has been collected through questionnaire and analysed to ascertain about the factors responsible for taking out vehicle insurance, choice between private and public sector insurance companies, preferred insurance companies among the major players in the field, factors that play a role in the customers' choice of a particular insurance company, customers' opinion about the affordability of the premium to be paid, customers' satisfaction with their chosen company, whether customers consider fast and efficient service as a deciding factor, and whether the brand value of the company plays a role in the customers' choice.

Turkish Online Journal of Qualitative Inquiry (TOJQI) Volume 12, Issue 2, March 2021: 801-815

veera venkat satyanarayana penumarthi

An effort is being made in this study to show how Vijayawada customers see insurance services. Respondents to a five-point Likert scale questionnaire were used to compile the data for this research. More than 377 people were surveyed to determine their degree of knowledge and attitude about insurance services. According to a new study, Vijayawada customers' perceptions about insurance services are strongly influenced by socioeconomic and demographic factors. Insurance businesses in Vijayawada may use the results of this research as a basis for developing marketing plans that include socio-demographic and economic factors.

Dharmesh Motwani

IJIRIS:: AM Publications,India

IJIRIS International Journal of Innovative Research in Information Security

The journey of new India Insurances scheme has stated 17th century England. Insurances are the co– operative device who distribute the loss caused by a particular risk.When any insurances company face any types of mismanagement, they should look for a market for that policy instead of constantly lying to the public or with their clients. Market competition brings decrease in price of the insurances company and increase in the quality but customer play their part according to their views. In the unpredictable society insurances paly a secure part but customers face many other problems. In this paper we will discussed about the problems faced by the customers and also their reasons why many people don’t have faith in the insurances company. The paper is focused on the problems faces by the customer in insurances sector.

Pranjal Bezborah

Sathishkumar Ramasamy

the present study analyzes the attitudes of policyholders of Life Insurance Corporation of India with special reference to Tiruchirappalli district, the data were collected and analysed as per the requirement of the study. The primary data were collected from the respondents through interview schedule in June 2011 to March 2012. The study has adopted proportionate stratified random sampling method for selecting 500 respondents. The results revealed the fact that the factors, age, education, marital status, family size, number of earning members, income and awareness have influenced the level of attitude of the policyholders. Whereas the factors like sex, occupation and patronage mentality did not influence the level of attitude.

IP innovative publication pvt ltd

IP Innovative Publication Pvt. Ltd.

With the increase in risk there is need of insurance to bear the losses. Insurance is the instrument used as the financial protection against various contingency. This paper examines the customer perception towards the General Insurance. A study had been conducted at Gwalior region with the sample of 200 respondents to find out the perception of the customer (policyholders). In this context, the respondents’ opinion on the various related statements were collected with a 5 point scaling. Reliability, Factor analysis, multivariate technique had been applied on the data. The result concluded that loyalty, transparency, proficiency, reliable and convenient services are the five factors from the 18 statements on the basis of the expectation of the customers. This study signifies that various customer had different expectation from the insurance company in the studied area.

Loading Preview

Sorry, preview is currently unavailable. You can download the paper by clicking the button above.

RELATED PAPERS

Dr.Dhiraj Jain

iaeme iaeme

Carmelo Panepinto

Murangirwa Festus

International Journal of Engineering and Advanced Technology

Srimannarayana Gajula

Ahmed Salman Syed

SHS Web of Conferences

Sesilya Kempa

Mohammad Jamal Hossain

IOSR Journal of Business and Management

Festus Epetimehin

International Journal of Law Management & Humanities (IJLMH) A peer-reviewed, HeinOnline, MANUPATRA, Google Scholar & 23 databases Indexed Int'l Journal with IF of 6.530.

Jayshree Singh

Velmurugan Ramasamy

As-Syirkah: Islamic Economic & Financial Journal

Nurul Jannah

Journal of Asian Finance, Economics and Business

adinoto nursiana

Arti Sharma

Sarang S Bhola

PARIPEX INDIAN JOURNAL OF RESEARCH

Chitralekha Dhadhal

Restaurant Business

Bhavna Pathak

International Journal of Engineering & Technology

Dr. Arun Vijay

Nepalese Journal of Insurance and Social Security

Aayush Poudel

Lakshmi Sivaramakrishnan

The Journal of Risk Management

Bonny Bagenda

Sunil Kumar

IAEME PUBLICATION

IAEME Publication

Publishing India Group

https://www.ijrrjournal.com/IJRR_Vol.6_Issue.8_Aug2019/Abstract_IJRR0041.html

International Journal of Research & Review (IJRR)

RELATED TOPICS

  •   We're Hiring!
  •   Help Center
  • Find new research papers in:
  • Health Sciences
  • Earth Sciences
  • Cognitive Science
  • Mathematics
  • Computer Science
  • Academia ©2024

You might be using an unsupported or outdated browser. To get the best possible experience please use the latest version of Chrome, Firefox, Safari, or Microsoft Edge to view this website.

  • Best Pet Insurance Companies

Best Pet Insurance Companies Of August 2024

Jason Metz

Expert Reviewed

Updated: Aug 5, 2024, 2:03pm

We evaluated 13 policies and found that Pets Best is the best pet insurance company.

A solid pet insurance plan covers major medical emergencies like getting struck by a vehicle, cancer treatment, torn ligaments and swallowed foreign objects. It also covers common health problems like digestive issues and ear infections. You’ll find that pet insurance companies offer a wide variety of coverage types and benefits.

To help you narrow your options, we analyzed the best pet insurance for discounts, superior benefits, short waiting periods and more.

  • Cheapest Pet Insurance Companies
  • Best Pet Insurance Wellness Plans For Routine Care
  • Best Emergency Pet Insurance
  • Compare Pet Insurance Quotes

Summary: Ratings of Pet Insurance Companies

Compare the best pet insurance companies, how much does pet insurance cost, how to choose the right pet insurance, methodology, best pet insurance frequently asked questions (faqs).

How We Chose the Best Pet Insurance

We analyzed key coverage categories such as pet insurance costs, the ability to pay the vet directly, the availability of a 24/7 vet health line and the option to add a wellness plan. Our editors are committed to bringing you unbiased ratings and information. Our editorial content is not influenced by advertisers. We use data-driven methodologies to evaluate insurance companies so all companies are measured equally. You can read more about our editorial guidelines and methodology for the ratings below.

  • 32 coverage categories evaluated
  • 7,360 pet insurance rates crunched
  • 102 years of insurance experience on the editorial team

The Best Pet Insurance Companies of August 2024

Best for deductible choices.

Pets Best

Maximum annual coverage

$5,000, Unlimited

Average monthly cost for unlimited coverage

$48 for dogs; $27 for cats

Deductible choices

$50, $100, $200, $250, $500, $1,000

We’re impressed by Pets Best’s range of deductible choices combined with costs that are well below average among the companies we analyzed. It provides solid basic coverage and you can add a wellness plan for routine pet care expenses.

Our rating is based on Pets Best’s Plus plan. For broader coverage (at a higher price), consider the Pets Best Elite plan.

More: Pets Best Pet Insurance Review

  • Accident coverage waiting period of only 3 days.
  • Has a 24/7 pet telehealth line.
  • Can pay the vet directly if the vet agrees.
  • Covers vet exam fees.
  • 6-month waiting period for coverage of cruciate ligament issues.
  • The Plus plan does not cover alternative therapies, but the Pets Best Elite plan will cover acupuncture and chiropractic care if your pet needs rehabilitation.
Our Expert Take Company Company - Logo Forbes Advisor Rating Forbes Advisor Rating
5.0
4.6
4.6
4.4
4.0
Healthy Paws 4.0
Coverage type Plan details

From my experience, Pets Best offers comprehensive coverage that is particularly beneficial for breeders and new pet owners. Their plans are customizable, which allows for flexibility depending on specific needs, such as covering congenital conditions, which is essential for certain breeds.

– Bricks Coggin, CEO of ABCs Puppy Zs

BEST FOR HEALTHY PET DISCOUNT

Embrace

$5,000, $8,000, $10,000, $15,000, Unlimited

$76 for dogs; $37 for cats

$100, $250, $500, $750, $1,000

We like Embrace because it offers a unique way to save on accident and illness plans with its Healthy Pet Discount Program. If your claim reimbursements are less than $300 per pet in the year prior to the discount period, you’ll qualify for a 5% discount in the first year and 10% in the second year for each pet. Embrace will automatically apply the savings to your annual payment or monthly bill.

More: Embrace Pet Insurance Review

  • Accident coverage begins at 12:01 a.m. ET the day after you purchase your policy.
  • Has a 24/7 pet telehealth line and optional wellness plan.
  • Can pay a veterinary hospital directly—but generally only for very large claims where it would be prohibitively expensive to pay and wait for reimbursement.
  • Higher-than-average costs compared to top competitors in our analysis.
  • Waiting period of 6 months for coverage of orthopedic conditions, which can be waived if your pet has an orthopedic exam after you purchase a plan.

Embrace stands out for its Wellness Rewards program, which reimburses for routine and preventative care, a feature that encourages pet owners to maintain regular veterinary visits. This can be extremely beneficial in the long term by preventing severe health issues that can lead to high medical costs.

Best For Reduced Waiting Periods

ManyPets

$49 for dogs; $30 for cats

ManyPets stood out in our evaluation because of its unique approach to reducing the accident and illness waiting period to 24 hours if you’re switching over from another pet insurer. ManyPets also does not have a special waiting period for orthopedic conditions like cruciate ligament issues, which can range from six to 12 months at other insurers.

More: ManyPets Pet Insurance Review

  • Below average prices among the companies we evaluated.
  • 24/7 pet telehealth line.
  • Includes coverage for vet exam fees.
  • Optional wellness plan available.
  • No coverage for alternative therapies such as acupuncture, hydrotherapy or chiropractic care.
  • No coverage for behavioral therapy.
  • No multipet discount.

GREAT FOR SHORT WAITING PERIOD FOR ACCIDENT COVERAGE

Figo

$5,000, $10,000, Unlimited

Average monthly cost for Unlimited coverage

$59 for dogs; $32 for cats

$100, $250, $500, $750, $1,000, $1,500

We picked Figo due to its short 1-day waiting period for accident coverage. It also offers a wide variety of coverage, reimbursement and deductible options so you can work within your budget.

More: Figo Pet Insurance Review

  • Offers a 100% reimbursement option.
  • Routine wellness plan available.
  • Coverage for vet exam fees can be added but for an extra cost. Some top competitors include this in the base coverage.
  • 6-month waiting period for orthopedic problems, but can be waived if your vet signs an orthopedic conditions waiver within the first 30 days of the policy.
  • No option to pay the vet directly.

I love that Figo has a variety of solutions and tools for pet owners to care for their pets. Figo goes beyond just pet insurance and takes a more holistic approach to pet care.

– Beth Tofel, Co-Founder and President of FootprintID and PawprintID

BEST FOR ADD-ON COVERAGE

AKC

$2,500, $5,000, $7,500, $10,000, $15,000, Unlimited

$60 for dogs; $32 for cats

$100, $250, $300, $400, $500, $750, $1,000

We like that AKC offers a good number of add-on coverage options, including a wellness plan, exam coverage for vet fees, breeding coverage for dog breeders and final respects coverage for cremation, burial and memorial expenses for your pet.

More: AKC Pet Insurance Review

  • 2-day waiting period for accident coverage.
  • Covers curable conditions like allergies and ear infections after a 12-month waiting period.
  • 180 day waiting period for intervertebral disc disease and cruciate ligament conditions.
  • You’ll have to pay extra for exam fee coverage. Some top competitors include this with base coverage.

GREAT FOR UNLIMITED ANNUAL COVERAGE

Healthy paws.

Healthy Paws

$55 for dogs; $22 for cats

We picked Healthy Paws because it offers unlimited annual coverage at a lower-than-average cost compared to other top competitors. But vet exam fees are not covered and pets enrolled at age 6 and older will not be covered for hip dysplasia.

More: Healthy Paws Pet Insurance Review

  • No annual coverage limit on claim payouts.
  • Pays vet directly if you make a request to Healthy Paws in advance of treatment.
  • Choices for deductibles and reimbursement levels are related to the pet’s age and other factors, but Healthy Paws does not disclose the exact deductible schedule. You have to get a quote to find out your choices.
  • Doesn’t offer wellness or routine care coverage.
  • Doesn’t cover vet exam fees for accidents or illnesses.

Healthy Paws is notable for its straightforward coverage and unlimited benefits with no cap on claims. In my professional circle, it’s highly regarded for its ease of use and quick reimbursement process, which is crucial for managing unexpected medical expenses effectively.

With all the variations in pricing and coverage details, it can be challenging to compare pet insurance plans in an apples-to-apples way. We found the best way to do it is by prioritizing the benefits that are the most important to you and then comparing prices among the policies that match your must-haves. Here’s how we chose the best pet insurance.

The first thing we recommend looking at is the plan type. We recommend a comprehensive pet insurance plan that covers accidents and illnesses. Pet insurance can generally be broken down into these plan types.

  • Accident and illness plan. This covers vet bills for accidents (like broken bones) and illnesses (such as cancer, allergies and skin infections).
  • Accident-only plan. This covers accident-related vet expenses, such as broken bones, bite wounds and ingested foreign objects. It does not cover illness-related vet expenses.
  • Pet wellness plans for routine care. This is typically an add-on policy that covers routine vet expenses like annual wellness exams, flea and heartworm prevention, and vaccinations.
  • Comprehensive plan. Sometimes called a “nose-to-tail” policy, this typically refers to an accident and illness plan plus an optional wellness plan.

Related: What Does Pet Insurance Cover?

Compare Plans Available by Company

We recommend looking at valuable benefits like coverage for vet exam fees. Not all insurers include this with their base policies. If having access to a 24/7 vet telehealth line is important to you, we recommend choosing an insurer that provides this benefit. It’s also a good idea to look at insurers that offer optional pet insurance wellness plans for routine care if you want coverage for expenses like annual wellness exams and vaccinations.

Company Covers pet exam fees for accidents and illnesses? 24/7 vet telehealth line available? Offers optional wellness plan? Offers option to pay vet directly

Coverage Levels

Pet insurance policies will typically offer a range of annual maximums, deductibles and reimbursement levels to choose from. We would prioritize choosing coverage levels you’re comfortable with rather than focusing on price alone. In the event of an expensive claim, you’ll be glad you bought sufficient coverage.

  • Annual maximum coverage. This is the maximum amount that will be paid out for pet insurance claims during the policy period. Common annual maximum coverage amounts include $5,000, $10,000 and unlimited.
  • Deductible. This is the amount you’ll pay toward vet bills before your coverage kicks in. Common deductible choices include $100, $250 and $500.
  • Reimbursement percentage. This is the reimbursement you’ll get back if you make a pet insurance claim. Common reimbursement levels include 70%, 80% and 90%.

Compare What’s Covered by Company

We recommend comparing coverage benefits like behavioral therapy, alternative therapy, microchipping and end-of-life expenses among pet insurers. Some insurers include these coverage types in their base policies or have the option to buy extra coverage.

Company Covers behavioral therapy? Covers alternative therapy? Covers microchipping? Covers euthanasia or end-of-life expenses?

Waiting Periods

A waiting period is the time between the policy purchase date and when the coverage begins. If you have a dog, we recommend taking a hard look at any special waiting periods, such as those for cruciate ligament issues. Many policies have a six-month waiting period for this but some insurers will waive this waiting period if you have an orthopedic exam done.

Special waiting periods for orthopedic conditions like hip dysplasia or cruciate ligament issues can range from six to 12 months, but you can find pet insurance with no waiting period for orthopedic conditions. If a long waiting period is a concern, I recommend looking at insurers like ASPCA, ManyPets, Pumpkin, Spot and Trupanion.

– Jason Metz, Lead Editor

Compare Waiting Periods by Company

Company Accident waiting period Illness waiting period Special waiting period

Pet Insurance Discounts

Pet insurance discounts are a good way to save. Here are discounts we found in our analysis, but they will vary by company:

  • Multipet discount . Many insurers offer a discount if you insure more than one pet .
  • Spay/neuter discount . Some insurers offer discounts to pet owners who have their pet spayed or neutered .
  • Annual pay discount . You can often reduce costs if you pay your annual premium in one lump sum.
  • Military discount . Some insurers offer discounts for military members and veterans.
  • Group discount at work . Some employers offer pet insurance as a voluntary benefit, which could get you a 5% to 10% discount.
  • Bundle discount . You can get up to a 10% discount when you bundle Lemonade pet insurance with a Lemonade renters or homeowners insurance policy.

Pet Insurance Discounts by Company

Company Multipet discount Military member discount Annual payment discount Other discounts

Other Pet Insurance Comparison Factors

Here are two more factors we would look at when buying a pet insurance plan:

  • Exam fees. When you take your pet to the veterinarian for an accident or illness, you pay an exam fee, costing $100 or more depending on your veterinarian and visit type. Make sure the policy covers these exam fees because not all do.
  • Benefits. Look for extra benefits like a 24-hour vet helpline in case your pet gets sick at night. As another example, Nationwide pet insurance members have access to preferred pricing on pet prescriptions at any Walmart pharmacy.

Case Study: Finlay’s Cancer Battle

When my 5-year-old dog Finlay was diagnosed with stage four nasal sarcoma, I was devastated. It began with a severe nosebleed, followed by a CT scan and biopsy. In just a week and a half, our lives were turned upside down. The expenses piled up quickly, from imaging procedures to targeted radiation therapy and countless follow-up visits. In total, we racked up over $10,000 in medical costs. Thankfully, our pet insurance has reimbursed us $8,565 so far. Each approved claim brings a wave of relief because we know we can focus on Finlay instead of the financial stress.

– Mitchell G., Michigan

Pet insurance costs an average of $50 for a dog and $26 per month for a cat , according to our analysis of pet insurance costs . That’s for a policy with $5,000 of annual coverage, a $250 deductible and 80% reimbursement level. A policy with unlimited annual coverage, a $250 deductible and 80% reimbursement level costs an average of $73 per month for a dog and $40 per month for a cat.

Your own pet insurance costs will be determined by factors such as:

  • Annual maximum, deductible and reimbursement levels.
  • Pet’s age, breed and gender.
  • Your location.

Ask an expert

Dr. Sarah Reidenbach

Advisory Board Member

Is Pet Insurance Worth It?

As a veterinarian, people often express concern to me about the cost of veterinary medicine compared to human medicine. The truth is that human medical services are exponentially more expensive, but most of us are used to having the benefit of health insurance for medical needs. Taking the time to get pet insurance in place can save the stress of large emergency veterinary bills that are so difficult to manage.

These simple steps will get you to the best policy for your situation.

ASK THE EXPERT

We Answer Your Questions

Insurance Lead Editor

Michelle Megna

Les Masterson

Insurance Editor

My pet was injured while we were on vacation and treated by a vet in a different state. Will pet insurance cover my vet bills?

Arnie S., Jamestown, Rhode Island

Yes, pet insurance covers vet bills for accidents and illnesses with any licensed vet in the U.S. That includes specialty clinics and emergency services.

Will pet insurance pay for prescription food?

Samantha B., Angola, Indiana

Yes, some pet insurers cover prescription food and supplements if it’s prescribed by your vet for a problem covered by your policy, like skin allergies. But some pet insurance companies do not cover prescription food and medication, such as Lemonade.

Can I still buy pet insurance for a senior dog?

Jake M., New Paltz, New York

Yes, you can buy pet insurance for a senior dog . Since older dogs are more likely to develop health problems, it can be a good way to help offset major vet bills. Some pet insurers have an “upper age limit” for buying a new policy, such as age 14. But if you buy the policy before the insurer’s upper age limit, your dog can have lifetime coverage.

To find the best pet insurance, we collected data and scored each pet insurance company for several categories. Only pet insurers offering annual maximum coverage of $100,000 or Unlimited were scored, so that comparisons were fair among companies.

  • Pet insurance rates (40% of score): We calculated average rates for medium sized mixed breed dogs age 3 months, 2 years, 5 years and 7 years for plans with unlimited coverage, a $250 deductible and a 80% reimbursement level, or the closest options available.
  • Special waiting period (10% of score): Many pet insurance companies have a special waiting period for problems such as cruciate ligament issues and hip dysplasia. Plans that had no waiting period , a waiting period of fewer than six months or the ability to have the waiting period waived scored higher.
  • Direct payment to vet (10% of score): Pet insurance companies that have the ability to pay a vet directly earned points.
  • 24/7 vet health line (10% of score): Insurers that provide access to a 24/7 vet health line earned points.
  • Routine wellness plans (10% of score): Insurers that offer optional wellness plans earned points.
  • Pays veterinary exam fees (10% of score): Plans that cover the vet exam fee received points. Not all insurers cover exam fees, even if the fee is for an illness or accident-related visit.
  • Euthanasia or end of life expenses (5% of score): Insurers that cover end of life expenses, such as euthanasia, cremation or burial fees, received points.
  • Multipet discount (5% of score): Many pet insurance companies offer a discount if you insure more than one pet. Insurers that offer a multipet discount earned points.

Compare Pet Insurance Plans

research paper auto insurance

Read more: How Forbes Advisor Rates Pet Insurance Companies

Should I get pet insurance?

We found the best way to determine if pet insurance is worth it is to consider how an unexpected vet bill could impact your personal finances. For example, if you’ve been paying about $50 per month for dog insurance for three years, you’ve paid $1,800 in pet insurance premiums.

Let’s say your dog swallowed a tennis ball and surgery cost $3,500. If you have a $250 deductible and 80% reimbursement level, your out-of-pocket cost for treatment would be $900 ($250 deductible + 20% of $3,250 = $900). Adding up the premium for three years and what you’ve paid toward treatment, you’ve paid $2,700 and avoided paying $800 by having pet insurance.

What is the best dog insurance?

We found that Pets Best is the best dog insurance company because of its solid coverage options and low prices for unlimited annual coverage among the companies we evaluated. Dog owners will find a 24/7 vet telehealth line, the option to add a wellness plan and the ability to pay the vet directly, which can help keep out of pocket expenses low.

Other pet insurance companies that scored well in our analysis include Embrace, ManyPets, Figo, AKC pet insurance and Healthy Paws.

What is the best cat insurance?

We found that Pets Best is the best cat insurance due its competitive prices and coverage options. These include access to a 24/7 vet telehealth line, an optional wellness plan and the ability to pay the vet directly.

Other insurers that were among our winners for best cat insurance companies include Embrace, Spot, Figo and Healthy Paws.

Do all vets take pet insurance?

All vets take pet insurance in the sense that pet insurance is generally reimbursement-based, meaning you’ll pay the veterinarian bills up-front and then submit a claim to your pet insurance company for reimbursement. So in most cases the veterinarian does not interact at all with the insurance company.

Some pet insurance companies pay the vet directly , which can reduce your out-of-pocket costs and you won’t have to wait for an insurance claims check.

Next Up In Pet Insurance

  • Cheapest Pet Insurance
  • Best Pet Insurance For Cats And Kittens
  • Best Pet Insurance For Older Dogs

Jason Metz

As a former claims handler and fraud investigator, Jason Metz has worked on a multitude of complex and multifaceted claims. The insurance industry can be seemingly opaque, and Jason enjoys breaking down confusing terms and products to help others make well-informed decisions.

Dr. Sarah Reidenbach

Dr. Sarah Reidenbach is a veterinarian and co-founder of Ruthless Kindness, a nonprofit that works with human service partners, such as district attorneys offices, family justice centers, women’s shelters, rape crisis centers and victim advocacy organization to remove barriers for abuse victims seeking safety. About 50% of people in crisis will not seek safety unless they can bring their pets with them.   Dr. Reidenbach worked in human factor research at NASA Ames Research Center and has since worked exclusively in the nonprofit sector. She has held positions as a veterinary fellow at San Francisco SPCA, Medical Director at Berkley Humane, Veterinary Director at the Humane Society of Sonoma County and Executive Director of Sonoma Community Animal Response Team.   She lives in Sonoma County with her family, including farm and companion animals. Dr. Reidenbach’s vision is to prevent suffering and heal trauma for the most vulnerable animals and people. She hopes to help all animals and people access fundamental services through systemic changes, innovative programs, and through navigating systems such as pet insurance. Her work is grounded in the belief that empathy and justice are antidotes to the challenges we currently face.  

Your pet’s age, breed and health history can affect what kind of coverage you want. Consult with your vet about your pet’s susceptibility to certain illnesses or injuries common to the breed. Also consider the pet’s risk of injury if they spend a lot of time outdoors.

Consider what types of problems should be covered by your ideal policy, especially when it comes to potentially expensive problems. For example, if you want coverage for serious illnesses such as cancer, make sure you buy an accident and illness plan rather than an accident-only plan. 

It’s also a good idea to look for coverage perks like a 24/7 pet healthline, coverage for vet exam fees and the option to add a wellness plan.

are generally two to 14 days for accident coverage and 14 days for illness coverage. Some pet insurers have special waiting periods for orthopedic conditions (such as cruciate ligament issues) that can range from six to 12 months. You can find pet insurance with no special waiting periods, such as .

Your coverage levels will impact your pet insurance cost. If you want to pay less out-of-pocket, you can choose a lower deductible and a higher reimbursement amount, but it’ll cost you more in premiums because your insurer will pay out more if you .

Some pet insurers have age limits to buy a policy. Most insurers will insure puppies and kittens around the age of six to 10 weeks. But some insurers have upper age limits (such as age 14) to buy a policy. The do not have upper age limits and have good coverage perks like a 24/7 pet healthline and the option to add a wellness plan.

The best way to find a policy within your budget is to among multiple insurers. You can get free quotes online or you can contact an insurance agent that sells pet insurance.

| |

Download ID = 212560
in AVSIM File Library and below.
   

Jump to page:   

  -->  


UUEE MOSCOW SHEREMETYEVO X V2 DEMO is a new scenery of UUEE Sheremetyevo airport in Moscow, Russia, fully compatible with FSX/FSX:SE/P3Dv1/P3Dv2/P3Dv3/P3Dv4. This product is a fully functional DEMO version of the commercial payware product. Most objects are modelled as in the full version but covered with low resolution textures, non-animated jetways and generally much less details. Using this free demo ensures no problems with online (VATSIM, IVAO, multiplayer etc.) flying in case some users use the payware scenery and some don't. Sheremetyevo International Airport (SVO/UUEE) is an international airport located in Khimki, Moscow Oblast.Sheremetyevo serves as the main hub for Russian flag carrier Aeroflot and its branch Rossiya Airlines, Nordwind Airlines or Ural Airlines. The product is equipped with an automatic installer, which means that the scenery will be automatically added to the Flight Simulator Scenery Library. Please uninstall all previous versions of this airport you may have installed before. Please also make sure that no duplicated AFCAD files are installed. Enjoy your virtual flying with Drzewiecki Design!

No Prev Page

AVSIM Library System Version 2.00 -- 2004-May-01 © 2001-2024 AVSIM Online All Rights Reserved

Plan Your Trip to Suponevo: Best of Suponevo Tourism

Suponevo, russia, essential suponevo.

research paper auto insurance

Small Business Productivity, Tools and Tips – Android and iPhone Sync

How to easily buy india car insurance online in 2024.

In today’s digital age, purchasing car insurance in India has become more convenient than ever before. With just a few clicks, you can buy car insurance online , ensuring that your vehicle is protected with the convenience of anytime, anywhere access.

research paper auto insurance

In this guide, we at Chola MS General Insurance take you through the steps to easily buy car insurance online in 2024 and discuss the factors affecting car insurance price in India.

1. Research and Compare Policies

The first step to buy car insurance online is thorough research. Start by visiting the websites of various insurance companies and using comparison tools to evaluate different policies. These tools allow you to compare coverage options, benefits, and premiums side-by-side, making it easier to find a policy that suits your needs and budget. Look for reputable insurance providers with good customer reviews and a track record of reliable service.

2. Understand Coverage Options

When you buy car insurance online in India, it’s important to understand the different types of coverage available:

  • Third-Party Liability Insurance : This is the minimum legal requirement in India and covers damages to third parties in the event of an accident.
  • Comprehensive Insurance : This provides extensive coverage, including third-party liability, damage to your vehicle, theft, and natural calamities.
  • Standalone Own-Damage Insurance : This covers damages to your vehicle but does not include third-party liability.

Choose a policy that offers adequate coverage based on your vehicle’s age, condition, and your driving habits. Comprehensive insurance is often recommended for new or high-value cars, while third-party insurance may suffice for older vehicles.

3. Calculate the Premium

The car insurance price in India is influenced by several factors, including the make and model of your car, its age, location, and your driving history. Most insurance websites offer online premium calculators that help you estimate the cost of your policy. Input accurate details to get a realistic quote. Keep in mind that while a lower premium might seem attractive, it could mean reduced coverage. Balancing cost and coverage is key to finding the best policy.

4. Check for Discounts and Offers

Many insurers provide discounts and offers when you buy car insurance online. These can include no-claim bonuses (NCB) for claim-free years, discounts for installing anti-theft devices, and loyalty discounts for long-term customers. Take advantage of these offers to reduce your premium. Additionally, some insurers offer promotional discounts for online purchases, further lowering the car insurance price in India.

research paper auto insurance

5. Read the Policy Document Carefully

Before finalising your purchase, read the policy document thoroughly. Ensure you understand the terms and conditions, exclusions, and claim procedures. Pay attention to the fine print to avoid any surprises in the future. If you have any doubts or questions, contact the insurer’s customer service for clarification.

6. Complete the Online Application

Once you’ve selected a policy, the next step to buy car insurance online is completing the application. Most insurers have user-friendly websites that guide you through the process. You’ll need to provide details such as your personal information, vehicle details, and previous insurance (if any). Ensure all information is accurate to avoid issues during the claim process.

7. Make the Payment

After filling out the application, you can proceed to make the payment. Insurance companies offer multiple payment options, including credit/debit cards, net banking, and digital wallets. Choose a secure payment method that suits you. Upon successful payment, you’ll receive a confirmation email with your policy document and payment receipt.

8. Download and Print Your Policy

Once you’ve made the payment, you can download and print your policy document. Keep a digital copy for easy access and a printed copy in your vehicle. Your policy document serves as proof of insurance and contains important information, including your policy number, coverage details, and contact information for claims and support.

If you want to buy car insurance online in 2024, you will find it is a straightforward and efficient process. By researching and comparing policies, understanding coverage options, calculating the premium, and taking advantage of discounts, you can find a policy that offers the best value. Reading the policy document carefully and ensuring accurate information during the application process further simplifies the experience. With these steps, you can easily buy car insurance online, ensuring peace of mind and protection for your vehicle at an optimal car insurance price in India.

This device is too small

If you're on a Galaxy Fold, consider unfolding your phone or viewing it in full screen to best optimize your experience.

  • Insurance-auto

Is a Low Deductible Car Insurance Policy Worth It?

Published on July 27, 2024

Kristi Waterworth

By: Kristi Waterworth

  • Low deductible car insurance policies allow you to use the policy with very little out-of-pocket cost per claim, sometimes as little as $0.
  • These policies are generally best for experienced drivers with older lower-value cars, but they're not exclusively for this set.
  • There are other benefits a low deductible policy brings, like low out-of-pocket protection if your car is crushed by a tree in a storm or an uninsured motorist hits you.

I am often asked by friends and family about things like insurance policies because of my financial expertise and my work here at The Ascent. A common question I get is about low deductible car insurance policies and whether or not they're "scams."

First of all, any legitimate insurance product that is offered by a legitimate insurance company is not a scam. But it can certainly feel as if you're paying a lot for nothing, if you don't consider everything you're getting with your policy.

Who is a low deductible car insurance policy for?

I'm the kind of person for whom a low deductible car insurance policy makes a lot of sense.

I'm a middle-aged driver with no recent accident or ticket history, I own an older car, and I would otherwise have a roadside assistance package. So, the very best car insurance , even with all the bells and every stinking whistle in the store, doesn't cost much more than the minimum coverage for my state, plus what I'd pay to AAA.

I am also currently trying to come out of a serious financial upset (recent divorce), and I'm paying off a lot of debt without a lot of savings. So, if I did have a major accident with liability only, that would put me at serious risk of being without a car in a city where you very much need a car to survive. Even a high deductible full coverage policy would put me in that same risk due to my current lack of savings and divorce-damaged credit.

This is why I chose a low deductible car insurance policy. It was inexpensive compared to the potential cost of having to handle an accident out of pocket, and it offers me a great deal of peace of mind.

That extra few dollars I pay each month has gotten my car unlocked when I locked my keys (AND MY DOG!) inside one April day in 2023, a jumpstart on a frozen and windy January day in 2024, and a window replacement in my own driveway in April 2024, along with the medical bills that the aforementioned dog had related to the incident that caused the need for a window replacement. It's been a rough policy year.

Choosing the right insurance coverage for your car

Sometimes, we need the best car insurance, but other times, we just need cheap car insurance , and you can't always have both. Younger drivers, or drivers with a lot of accidents or tickets will probably fall over dead when they see the cost for a full-coverage policy with a low deductible, so they may have to compromise on what kind of coverage they get.

Other drivers, like those with cars that are on their last legs, or cars that they can easily replace should the need arise, may find that putting the difference between what they'd pay for a low deductible policy and the high deductible policy into an account just for car repairs makes the most sense. For me, that's about $20 a month. So, if I had an accident and my sainted Chevy HHR was totaled, I'd need to go 18.75 years without a problem before I'd save enough money to buy another one in today's dollars.

Drivers have to be really honest with themselves about insurance policies, and not just hope for the best (I love to approach life this way, but it's a toxic financial trait). Here are some questions for drivers to consider:

  • Can I afford to replace my car if I cause an accident?
  • Am I able to pay for an accident caused by an uninsured motorist?
  • Would the difference between base-level car insurance and low deductible car insurance add up quickly enough to pay for a repair if I cause an accident?
  • Do I get roadside assistance with the level of insurance I have now? Many low deductible policies come with unlimited roadside assistance for free.
  • Will my current auto policy cover my car if it's damaged in a storm?

Only you can decide what your budget should be for car insurance, but keep asking your insurance agent every year for the price difference between whatever you're getting and the absolute top tier offerings.

When you hit that magical spot where there's a relatively small difference between a low and high deductible, you may feel like it's not really significant enough cash to justify having to pay $1,000, $2,500, or even $5,000 out of pocket should you cause an accident or a tree happens to fall on your car.

Our best car insurance companies for 2024

Ready to shop for car insurance? Whether you’re focused on price, claims handling, or customer service, we've researched insurers nationwide to provide our best-in-class picks for car insurance coverage. Read our free expert review  today to get started.

Our Research Expert

Kristi Waterworth

Kristi Waterworth is a financial journalist located in the Missouri Ozarks. When she’s not writing about real estate or personal finance, she’s committing shenanigans with her four dogs.

Share this page

We're firm believers in the Golden Rule, which is why editorial opinions are ours alone and have not been previously reviewed, approved, or endorsed by included advertisers. The Ascent, a Motley Fool service, does not cover all offers on the market. The Ascent has a dedicated team of editors and analysts focused on personal finance, and they follow the same set of publishing standards and editorial integrity while maintaining professional separation from the analysts and editors on other Motley Fool brands.

Related Articles

Cole Tretheway

By: Cole Tretheway | Published on June 7, 2024

Lyle Daly

By: Lyle Daly | Published on June 5, 2024

Christy Bieber

By: Christy Bieber | Published on June 5, 2024

By: Lyle Daly | Published on June 4, 2024

The Ascent is a Motley Fool service that rates and reviews essential products for your everyday money matters.

Copyright © 2018 - 2024 The Ascent. All rights reserved.

  • White Collar Crime
  • Criminal Law
  • Fraud Detection

Automobile Insurance Fraud Detection

  • October 2021
  • Communications in Statistics Case Studies Data Analysis and Applications

Mark Anthony Caruana at University of Malta

  • University of Malta

Liam Grech at University of Malta

Abstract and Figures

Neural Network with one hidden layer and one output unit

Discover the world's research

  • 25+ million members
  • 160+ million publication pages
  • 2.3+ billion citations
  • INT STAT REV

David Hand

  • B. D. Ripley

David Barber

  • NEURAL NETWORKS
  • Kurt Hornik

George Cybenko

  • DECIS SUPPORT SYST
  • E.W.T. Ngai

Yong Hu

  • Richard J. Bolton

Pedro Domingos

  • Recruit researchers
  • Join for free
  • Login Email Tip: Most researchers use their institutional email address as their ResearchGate login Password Forgot password? Keep me logged in Log in or Continue with Google Welcome back! Please log in. Email · Hint Tip: Most researchers use their institutional email address as their ResearchGate login Password Forgot password? Keep me logged in Log in or Continue with Google No account? Sign up

IMAGES

  1. (PDF) Car Insurance Plans Could Make a Society Safer

    research paper auto insurance

  2. Progressive Auto Insurance Template

    research paper auto insurance

  3. Research A car insurance policy Suggestions Also Content

    research paper auto insurance

  4. (PDF) A Study on Customer Awareness on Car Insurance Policies with

    research paper auto insurance

  5. (DOC) Vehicle Insurance Policy Format

    research paper auto insurance

  6. Car Insurance Paper Pdf

    research paper auto insurance

COMMENTS

  1. Bibliometric review of telematics-based automobile insurance: Mapping

    Furthermore, as reported in this research, the analysis of keyword co-occurrence and its subsequent network visualisation contributed to highlighting the knowledge framework relevant to telematics-based automotive insurance. The knowledge structure of car insurance studies using telematics was mapped using keyword co-occurrence analysis, and ...

  2. (PDF) Prediction of automobile insurance fraud claims using machine

    This study explored machine learning algorithms to det ect fraudulent. vehicle insurance claims. The r esearch evaluated AdaBoost, XGboostNB, SVM, LR, D T, ANN, and RF. AdaBoost and XGBoost classi ...

  3. Research on the Features of Car Insurance Data Based on Machine

    Abstract. With the continuous development of machine learning, enterprises using machine learning methods to mine potential data information has become a hot topic in the research of major insurance companies. In this paper, the features of auto insurance data are analyzed, and the most important features affecting auto renewal are mined.

  4. Car Insurance Plans Could Make a Society Safer

    DOI: 10.4236/gep.2016.412002 December 1, 2016. Car Insurance Plans Could Make a Society Safer. Mohammad Zand, Amir Samimi, Khashayar Khavarian. Civil Engineering Department, Shar if University of ...

  5. Claim Amount Forecasting and Pricing of Automobile Insurance Based on

    Denneberg first proposed the Poisson-gamma model to study the frequency of nonhomogeneous insurance policy claims and obtained good fitting results in empirical research on auto insurance . The generalized linear model (GLM) is a widely accepted model for premium ratemaking of automobile insurance in recent decades.

  6. Automobile insurance fraud detection in the age of big data

    The purpose of this paper is to survey the automobile insurance fraud detection literature in the past 31 years (1990-2021) and present a research agenda that addresses the challenges and opportunities artificial intelligence and machine learning bring to car insurance fraud detection.,Content analysis methodology is used to analyze 46 peer ...

  7. Machine Learning Approaches for Auto Insurance Big Data

    The growing trend in the number and severity of auto insurance claims creates a need for new methods to efficiently handle these claims. Machine learning (ML) is one of the methods that solves this problem. As car insurers aim to improve their customer service, these companies have started adopting and applying ML to enhance the interpretation and comprehension of their data for efficiency ...

  8. Exploring Industry-Level Fairness of Auto Insurance Premiums by ...

    The study of actuarial fairness in auto insurance has been an important issue in the decision making of rate regulation. Risk classification and estimating risk relativities through statistical modeling become essential to help achieve fairness in premium rates. ... University of Texas Law, Law and Econ Research Paper No. E574. Available online ...

  9. A data science approach to risk assessment for automobile insurance

    Many past papers have focused on recommender systems for insurance companies where one of a small number of insurance products is offered. In [17, 18], they used historical data of existing and past customers to determine the most suitable policy for a new customer.In this case, a relatively small number of insurance products are available, and hence, the number of customers who have been ...

  10. Automobile insurance fraud detection in the age of big data

    Purpose The purpose of this paper is to survey the automobile insurance fraud detection literature in the past 31 years (1990-2021) and present a research agenda that addresses the challenges ...

  11. Auto Insurance Trends Report

    Top 5 Auto Insurance Trends To Watch. The annual LexisNexis® Risk Solutions U.S. Auto Insurance Trends Report explores key trends from the previous year and offers insights to help insurers make more informed business decisions. This year, we identified five trends impacting U.S. consumer auto insurance shopping, claims, driving violations and ...

  12. PDF Implications of Evolving Technology in Auto Insurance Expert Panel

    1.1 IMPACT OF TECHNOLOGICAL ADVANCES IN AUTO INSURANCE CLAIMS. Auto insurance claims will be impacted by two distinct forms of technological advances: enhanced safety features, and autonomous vehicles. Regarding the development of enhanced safety measures, the panel members noted:

  13. PDF Trends Indicate Auto Insurance is Becoming More ...

    Insurance Research Council (IRC). In addition to documenting that auto insurance has become more affordable for both the nation as a whole and across states, the study also showed that the ... Auto Insurance Expenditure to Income Ratio - Decade Average 1990s average 2000s average 2010s average. Author:

  14. PDF A practical model for pricing optimization in car insurance

    the insurance policy and the outcome of applying optimal premium rates in several customer segments are shown. I. Introduction The sensitivity of car insurance customers to price and how this affects their retention has been a subject of intense analysis in the insurance market research literature. Different

  15. PDF A Proposed Model to Predict Auto Insurance Claims Using Machine ...

    most insurance companies experience great loss as far as car insurance as shown in Figure 1, one of the main challenges face the insurance companies nowadays, is to define a proper premium for each risk represented by those customers [4], the majority of insurance companies keep the data on the history of its operations in a data warehouse

  16. PDF Cas Research Paper Series on Race and Insurance Pricing Defining

    yers.Defining Discrimination in InsuranceBy Kudakwashe F. Chibanda, FCASExecutive SummaryThis research paper is designed to introduce various terms used in defining discrimination by stakeholders in. the insurance industry (regulators, consumer advocacy groups, actuaries and insurers, etc.). The paper defines protected class, unfair discriminat.

  17. A Study on Customer Awareness on Car Insurance Policies with Special

    IJIRST -International Journal for Innovative Research in Science & Technology| Volume 5 | Issue 5 | October 2018 ISSN (online): 2349-6010 A Study on Customer Awareness on Car Insurance Policies with Special Reference to United India Insurance, Shivamogga Dr (HC) D. M. Arvind Mallik Assistant Professor PGDMS, PESITM, Shivamogga-577201 ...

  18. Here Are the 10 Most Reliable Car Brands

    Whether you're focused on price, claims handling, or customer service, we've researched insurers nationwide to provide our best-in-class picks for car insurance coverage. Read our free expert ...

  19. Math Expert Recommends These 3 Ways to Get Cheaper Car Insurance

    See how to save on car insurance. ... The Motley Fool Ascent's research recently found that 20% of drivers have never shopped for cheaper car insurance, and only 26% shop for price quotes every ...

  20. This Way to Save Money on Car Insurance Has 3 Big Drawbacks. Here's Why

    Car insurance costs went up by over 20% per year, according to recent survey data. Many drivers are reeling from the rapid increase in car insurance premiums.

  21. Revealing the Post-2020 Car Insurance Pricing Crisis Across the US

    A recent study from Pew Research reveals goods and services that have seen the highest price increases since 2020. Car insurance makes the top 10 list of highest price increases since 2020. From ...

  22. (PDF) Motor Insurance Claim Status Prediction using ...

    Accuracy, Precision, Recall, and F - measure. The prediction. accuracy of t he model is capable of predicting the motor. in surance claim status with 98.36% and 98.17% by RF and SVM. classifiers ...

  23. Beyond bundling: How to rein in rising auto insurance rates

    Even as inflation has eased, car insurance rates are rising by double digits. But drivers have some options for reining in premiums. According to the Bureau of Labor Statistics, auto insurance ...

  24. Best Pet Insurance Companies Of August 2024

    How to choose the best pet insurance for your furry friends? Compare Pets Best, Embrace and Paw Protect, the top-rated plans by Forbes Advisor, and see how they cover accidents, illnesses, and more.

  25. AVSIM Library

    Sheremetyevo International Airport (SVO/UUEE) is an international airport located in Khimki, Moscow Oblast.Sheremetyevo serves as the main hub for Russian flag carrier Aeroflot and its branch Rossiya Airlines, Nordwind Airlines or Ural Airlines. The product is equipped with an automatic installer, which means that the scenery will be ...

  26. Suponevo, Russia: All You Must Know Before You Go (2024 ...

    Traktir. 10. $$ - $$$. Suponevo Tourism: Tripadvisor has reviews of Suponevo Hotels, Attractions, and Restaurants making it your best Suponevo resource.

  27. How to Easily Buy India Car Insurance Online in 2024

    The first step to buy car insurance online is thorough research. Start by visiting the websites of various insurance companies and using comparison tools to evaluate different policies. These tools allow you to compare coverage options, benefits, and premiums side-by-side, making it easier to find a policy that suits your needs and budget. ...

  28. Is a Low Deductible Car Insurance Policy Worth It?

    Low deductible car insurance policies allow you to use the policy with very little out-of-pocket cost per claim, sometimes as little as $0. ... Research has found a correlation between credit ...

  29. Public transport stop: Старая Руза, Moscow and ...

    Public transport stop: Старая Руза, Moscow and Moscow Oblast. Public transport that stops here: buses: 21, 21/62 and 3 more — Yandex Maps.

  30. (PDF) Automobile Insurance Fraud Detection

    Automobile Insurance F raud Detection. Mark Anthony Caruana 1 and Liam Grec h. 1 Department of Statistics and Operations Research, Faculty of Science, University. of Malta, Msida, Malta. (E-mail ...