Fairness of Ratemaking for Catastrophe Insurance: Lessons from Machine Learning

Published Online:https://doi.org/10.1287/isre.2022.1195

References

  • Abbasi A, Li J, Clifford G, Taylor H (2018) Make “fairness by design” part of machine learning. Harvard Bus. Rev. https://hbr.org/2018/08/make-fairness-by-design-part-of-machine-learning.Google Scholar
  • Acerbi C, Tasche D (2002) Expected shortfall: A natural coherent alternative to value at risk. Econom. Notes 31(2):379–388.CrossrefGoogle Scholar
  • Adjerid I, Peer E, Acquisti A (2018) Beyond the privacy paradox: Objective vs. relative risk in privacy decision making. Management Inform. Systems Quart. 42(2):465–488.CrossrefGoogle Scholar
  • Akter S, Mallick B (2013) The poverty-vulnerability-resilience nexus: Evidence from Bangladesh. Ecological Econom. 96(1):114–124.CrossrefGoogle Scholar
  • Alonso-Meijide JM, Álvarez-Mozos M, Fiestras-Janeiro MG, Jiménez-Losada A (2021) Marginality and convexity in partition function form games. Math. Methods Oper. Res. 94(1):99–121.CrossrefGoogle Scholar
  • American Academy of Actuaries (2018) Uses of Catastrophe Model Output (American Academy of Actuaries, Washington, DC).Google Scholar
  • Angst CM, Block ES, D’arcy J, Kelley K (2017) When do it security investments matter? Accounting for the influence of institutional factors in the context of healthcare data breaches. Management Inform. Systems Quart. 41(3):893–916.CrossrefGoogle Scholar
  • Arrow KJ (1978) Uncertainty and the welfare economics of medical care. Uncertainty in Economics (Academic Press, Cambridge, MA).CrossrefGoogle Scholar
  • Artzner P, Delbaen F, Eber JM, Heath D (1999) Coherent measures of risk. Math. Finance 9(3):203–228.CrossrefGoogle Scholar
  • Bachrach Y, Markakis E, Resnick E, Procaccia AD, Rosenschein JS, Saberi A (2010) Approximating power indices: Theoretical and empirical analysis. Autonomous Agents Multi-Agent Systems 20(2):105–122.CrossrefGoogle Scholar
  • Baker T (2002) Risk, insurance, and the social construction of responsibility. Embracing Risk: The Changing Culture of Insurance and Responsibility, (University of Chicago Press, Chicago) 33–51.Google Scholar
  • Baker T (2011) Health insurance, risk, and responsibility after the Patient Protection and Affordable Care Act. Univ. Pennsylvania Law Rev. 159(6):1577–1622.Google Scholar
  • Barrett M, Walsham G (1999) Electronic trading and work transformation in the London insurance market. Inform. Systems Res. 10(1):1–22.LinkGoogle Scholar
  • Bassellier G, Benbasat I, Reich BH (2003) The influence of business managers’ IT competence on championing it. Inform. Systems Res. 14(4):317–336.LinkGoogle Scholar
  • Berman R (2018) Beyond the last touch: Attribution in online advertising. Marketing Sci. 37(5):771–792.LinkGoogle Scholar
  • Bharosa N, Lee J, Janssen M (2010) Challenges and obstacles in sharing and coordinating information during multi-agency disaster response: Propositions from field exercises. Inform. Systems Frontiers 12(1):49–65.CrossrefGoogle Scholar
  • Bourbaki N (2008) Lie Groups and Lie Algebras (Springer Science & Business Media, New York).Google Scholar
  • Bühlmann H (1970) Mathematical Methods in Risk Theory (Springer Science & Business Media, New York).Google Scholar
  • Cahn AL (2008) Our rights are not cast in stone: Post-Katrina environmental red-lining and the need for a broad-based human right lawyering movement. Univ. Pennsylvania J. Law Soc. Change 12(1):37–71.Google Scholar
  • Castro J, Gómez D, Tejada J (2009) Polynomial calculation of the Shapley value based on sampling. Comput. Oper. Res. 36(5):1726–1730.CrossrefGoogle Scholar
  • Charpentier A, Barry L, James MR (2022) Insurance against natural catastrophes: Balancing actuarial fairness and social solidarity. Geneva Papers Risk Insurance-Issues Practice 47(1):50–78.CrossrefGoogle Scholar
  • Colten CE (2006) Vulnerability and place: Flat land and uneven risk in New Orleans. Amer. Anthropologist 108(4):731–734.CrossrefGoogle Scholar
  • Copeland TE, Weston JF, Shastri K (2005) Financial Theory and Corporate Policy, vol. 4 (Pearson, New York).Google Scholar
  • Cormen TH, Leiserson CE, Rivest RL, Stein C (2009) Introduction to Algorithms (MIT Press, Cambridge, MA).Google Scholar
  • Daniels N (1990) Insurability and the HIV epidemic: Ethical issues in underwriting. Milbank Quart. 68(4):497–525.CrossrefGoogle Scholar
  • Deng X, Papadimitriou CH (1994) On the complexity of cooperative solution concepts. Math. Oper. Res. 19(2):257–266.LinkGoogle Scholar
  • Dietz S, Niehörster F (2021) Pricing ambiguity in catastrophe risk insurance. Geneva Risk Insurance Rev. 46(2):112–132.CrossrefGoogle Scholar
  • Dietz S, Walker O (2019) Ambiguity and insurance: Capital requirements and premiums. J. Risk Insurance 86(1):213–235.CrossrefGoogle Scholar
  • Dong W, Shah H, Wong F (1996) A rational approach to pricing of catastrophe insurance. J. Risk Uncertainty 12(2):201–218.CrossrefGoogle Scholar
  • Dwork C (2008) Differential privacy: A survey of results. Proc. Internat. Conf. Theory Appl. Models Comput., 1–19.Google Scholar
  • Embrechts P, Klüppelberg C, Mikosch T (2013) Modelling Extremal Events (Springer, Berlin).Google Scholar
  • Everett RS, Wojtkiewicz RA (2002) Difference, disparity, and race/ethnic bias in federal sentencing. J. Quant. Criminology 18(2):189–211.CrossrefGoogle Scholar
  • Ewald F (2014) L’Etat Providence (Grasset, Paris).Google Scholar
  • Fatima SS, Wooldridge M, Jennings NR (2008) A linear approximation method for the Shapley value. Artificial Intelligence 172(14):1673–1699.CrossrefGoogle Scholar
  • Fothergill A (2006) In the Wake of the Storm: Environment, Disaster, and Race After Katrina (SAGE, New York).Google Scholar
  • Frezal S, Barry L (2020) Fairness in uncertainty: Some limits and misinterpretations of actuarial fairness. J. Bus. Ethics 167(1):127–136.CrossrefGoogle Scholar
  • Fu L, Khury C (2010) Optimal layers for catastrophe reinsurance. Variance 4(2):191–208.Google Scholar
  • Ghorbani A, Zou J (2019) Data Shapley: Equitable valuation of data for machine learning. Proc. Machine Learn. Res. 97(1):2242–2251.Google Scholar
  • Goode S, Hoehle H, Venkatesh V, Brown SA (2017) User compensation as a data breach recovery action: An investigation of the Sony Playstation network breach. Management Inform. Systems Quart. 41(3):703–727.CrossrefGoogle Scholar
  • Grossi P (2005) Catastrophe Modeling: A New Approach to Managing Risk (Springer, New York).CrossrefGoogle Scholar
  • Gul F (1989) Bargaining foundations of Shapley value. Econometrica 57(1):81–95.CrossrefGoogle Scholar
  • Ha J, Kose MA, Ohnsorge F (2021) One-stop source: A global database of inflation. Policy Research Working Paper 9737, World Bank, Washington, DC.Google Scholar
  • Heller D, Advocate C (2015) High price of mandatory auto insurance in predominantly African American communities. Technical Report 2015-11-18, Consumer Federation of America, Washington, DC.Google Scholar
  • Herepath A (2014) In the loop: A realist approach to structure and agency in the practice of strategy. Organ. Stud. 35(6):857–879.CrossrefGoogle Scholar
  • Houston DB (1960) Risk theory. J. Insurance 27(1):77–82.CrossrefGoogle Scholar
  • Huber PJ (1973) Robust regression: Asymptotics, conjectures and Monte Carlo. Ann. Statist. 1(5):799–821.CrossrefGoogle Scholar
  • Jaffee DM, Russell T (1997) Catastrophe insurance, capital markets, and uninsurable risks. J. Risk Insurance 64(2):205–230.CrossrefGoogle Scholar
  • Jia R, Dao D, Wang B, Hubis FA, Gurel NM, Zhang BLC, Song CSD (2019a) Efficient task-specific data valuation for nearest neighbor algorithms. Proc. VLDB Endowment. 12(11):1610–1623.CrossrefGoogle Scholar
  • Jia R, Dao D, Wang B, Hubis FA, Hynes N, Gürel NM, Li B, Zhang C, Song D, Spanos CJ (2019b) Toward efficient data valuation based on the Shapley value. Proc. Machine Learn. Res. 89(1):1167–1176.Google Scholar
  • Kamijo Y, Kongo T (2010) Axiomatization of the Shapley value using the balanced cycle contributions property. Internat. J. Game Theory 39(4):563–571.CrossrefGoogle Scholar
  • Kashmiri S, Nicol CD, Hsu L (2017) Birds of a feather: Intra-industry spillover of the target customer data breach and the shielding role of it, marketing, and CSR. J. Acad. Marketing Sci. 45(2):208–228.CrossrefGoogle Scholar
  • Khan F, Kim JH, Mathiassen L, Moore R (2021) Data breach management: An integrated risk model. Inform. Management 58(1):103392.CrossrefGoogle Scholar
  • Kifer D, Machanavajjhala A (2011) No free lunch in data privacy. Proc. 2011 ACM SIGMOD Internat. Conf. Management Data, 193–204.Google Scholar
  • Kimms A, Kozeletskyi I (2016) Core-based cost allocation in the cooperative traveling salesman problem. Eur. J. Oper. Res. 248(3):910–916.CrossrefGoogle Scholar
  • Kleinberg J, Mullainathan S, Raghavan M (2017) Inherent trade-offs in the fair determination of risk scores. Proc. Eighth Conf. Innovations Theoretical Comput. Sci., 1–23.Google Scholar
  • Kóczy LÁ (2018) Partition Function Form Games, Theory and Decision Library C, vol. 48 (Springer, New York).Google Scholar
  • Kreps R (1990) Reinsurer risk loads from marginal surplus requirements. Proc. Casualty Actuarial Soc. 77:196–203.Google Scholar
  • Krieger N (1992) Overcoming the absence of socioeconomic data in medical records: Validation and application of a census-based methodology. Amer. J. Public Health 82(5):703–710.CrossrefGoogle Scholar
  • Krishna V, Serrano R (1996) Multilateral bargaining. Rev. Econom. Stud. 63(1):61–80.CrossrefGoogle Scholar
  • Landes X (2015) How fair is actuarial fairness? J. Bus. Ethics 128(3):519–533.CrossrefGoogle Scholar
  • Lange JT (1969) Application of a mathematical concept of risk to property-liability insurance ratemaking. J. Risk Insurance 36(4):383–391.CrossrefGoogle Scholar
  • Lee YT, Sidford A (2015) Efficient inverse maintenance and faster algorithms for linear programming. 2015 IEEE 56th Annual Sympos. Foundations Comput. Sci., 230–249.Google Scholar
  • Lehtonen TK, Liukko J (2011) The forms and limits of insurance solidarity. J. Bus. Ethics 103(1):33–44.CrossrefGoogle Scholar
  • Leng M, Luo C, Liang L (2021) Multiplayer allocations in the presence of diminishing marginal contributions: Cooperative game analysis and applications in management science. Management Sci. 67(5):2891–2903.LinkGoogle Scholar
  • Maleki S, Tran-Thanh L, Hines G, Rahwan T, Rogers A (2013) Bounding the estimation error of sampling-based Shapley value approximation. Preprint, submitted June 18, https://arxiv.org/abs/1306.4265.Google Scholar
  • Mango DF (1997) An application of game theory: Property catastrophe risk load. Proc. Casualty Actuarial Soc. 84:33–49.Google Scholar
  • McQuillin B, Sugden R (2016) Backward induction foundations of the Shapley value. Econometrica 84(6):2265–2280.CrossrefGoogle Scholar
  • Mehta S, Dawande M, Janakiraman G, Mookerjee V (2021) How to sell a data set? Pricing policies for data monetization. Inform. Systems Res. 32(4):1281–1297.LinkGoogle Scholar
  • Meyers G (1996) The competitive market equilibrium risk load formula for catastrophe ratemaking. Proc. Casualty Actuarial Soc. 83:563–600.Google Scholar
  • Meyers G, Van Hoyweghen I (2018) Enacting actuarial fairness in insurance: From fair discrimination to behaviour-based fairness. Sci. Culture 27(4):413–438.CrossrefGoogle Scholar
  • Michalak TP, Aadithya KV, Szczepanski PL, Ravindran B, Jennings NR (2013) Efficient computation of the Shapley value for game-theoretic network centrality. J. Artificial Intelligence Res. 46(1):607–650.CrossrefGoogle Scholar
  • Michel-Kerjan EO (2010) Catastrophe economics: The national flood insurance program. J. Econom. Perspect. 24(4):165–186.CrossrefGoogle Scholar
  • Milinski M, Sommerfeld RD, Krambeck HJ, Reed FA, Marotzke J (2008) The collective-risk social dilemma and the prevention of simulated dangerous climate change. Proc. Natl. Acad. Sci. USA 105(7):2291–2294.CrossrefGoogle Scholar
  • Moulin H (1992) An application of the Shapley value to fair division with money. Econometrica 60(6):1331–1349.CrossrefGoogle Scholar
  • Myerson RB (1980) Conference structures and fair allocation rules. Internat. J. Game Theory 9(3):169–182.CrossrefGoogle Scholar
  • Nash JF (1950) The bargaining problem. Econometrica 18(1):155–162.CrossrefGoogle Scholar
  • National Association of Insurance Commissioners (2020) NAIC announces special committee on race and insurance. Accessed January 15, 2022, https://content.naic.org/article/news_release_naic_announces_special_committee_race_and_insurance.htm.Google Scholar
  • National Research Council (2004) Measuring Racial Discrimination (National Academies Press).Google Scholar
  • Nevo A (2001) Measuring market power in the ready-to-eat cereal industry. Econometrica 69(2):307–342.CrossrefGoogle Scholar
  • Nicholson JE, Clark K, Daraskevich G (2018) The Florida insurance market: An analysis of vulnerabilities to future hurricane losses. J. Insurance Regulation 37(3):57–89.Google Scholar
  • Nussbaumer A, Pope A, Neville K (2023) A framework for applying ethics-by-design to decision support systems for emergency management. Inform. Systems J. 33(1):34–55.CrossrefGoogle Scholar
  • Olivieri A, Pitacco E (2015) Introduction to Insurance Mathematics: Technical and Financial Features of Risk Transfers (Springer, New York).CrossrefGoogle Scholar
  • Pager D, Shepherd H (2008) The sociology of discrimination: Racial discrimination in employment, housing, credit, and consumer markets. Annual Rev. Sociol. 34:181–209.CrossrefGoogle Scholar
  • Pichler A (2014) Insurance pricing under ambiguity. Eur. Actuarial J. 4(2):335–364.CrossrefGoogle Scholar
  • Plitt S, Maldonado D (2007) Prohibiting de facto insurance redlining: Will Hurricane Katrina draw a discriminatory redline in the Gulf Coast sands prohibiting access to home ownership. Washington Lee J. Civil Rights Soc. Justice 14(2):199–254.Google Scholar
  • Rai A (2020) Explainable AI: From black box to glass box. J. Acad. Marketing Sci. 48(1):137–141.CrossrefGoogle Scholar
  • Rockafellar RT, Uryasev S (2002) Conditional value-at-risk for general loss distributions. J. Banking Finance 26(7):1443–1471.CrossrefGoogle Scholar
  • Roth AE (1977) The Shapley value as a Von Neumann-Morgenstern utility. Econometrica 45(3):657–664.CrossrefGoogle Scholar
  • Roth AE, Verrecchia RE (1979) The Shapley value as applied to cost allocation: A reinterpretation. J. Accounting Res. 17(1):295–303.CrossrefGoogle Scholar
  • Sen R, Borle S (2015) Estimating the contextual risk of data breach: An empirical approach. J. Management Inform. Systems 32(2):314–341.CrossrefGoogle Scholar
  • Shapley L (1951) Notes on the n-person game-II: The value of an n-person game. The RAND Corporation Research Memorandum 670.Google Scholar
  • Sharapov D, Kattuman P, Rodriguez D, Velazquez FJ (2021) Using the Shapley value approach to variance decomposition in strategy research: Diversification, internationalization, and corporate group effects on affiliate profitability. Strategic Management J. 42(3):608–623.CrossrefGoogle Scholar
  • Short ED (1985) FDIC settlement practices and the size of failed banks. Econom. Rev. Federal Reserve Bank of Dallas, March 1985, 12–20.Google Scholar
  • Shubik M (2002) Game theory and operations research: Some musings 50 years later. Oper. Res. 50(1):192–196.LinkGoogle Scholar
  • Smiley KT (2020) Social inequalities in flooding inside and outside of floodplains during Hurricane Harvey. Environ. Res. Lett. 15(9):0940b3.CrossrefGoogle Scholar
  • Squires GD (2003) Racial profiling, insurance style: Insurance redlining and the uneven development of metropolitan areas. J. Urban Affairs 25(4):391–410.CrossrefGoogle Scholar
  • Tang S, Ghorbani A, Yamashita R, Rehman S, Dunnmon JA, Zou J, Rubin DL (2021) Data valuation for medical imaging using Shapley value and application to a large-scale chest X-ray data set. Sci. Rep. 11(1):1–9.Google Scholar
  • Tarashev N, Tsatsaronis K, Borio C (2016) Risk attribution using the Shapley value: Methodology and policy applications. Rev. Finance 20(3):1189–1213.CrossrefGoogle Scholar
  • Thomas RG (2007) Some novel perspectives on risk classification. Geneva Papers Risk Insurance Issues Practice 32(1):105–132.CrossrefGoogle Scholar
  • Venezian EC (1985) Ratemaking methods and profit cycles in property and liability insurance. J. Risk Insurance 52(1):477–500.CrossrefGoogle Scholar
  • Verma V, Kawaguchi K, Lamb A, Kannala J, Solin A, Bengio Y, Lopez-Paz D (2022) Interpolation consistency training for semi-supervised learning. Neural Networks 145(1):90–106.CrossrefGoogle Scholar
  • Wang SS, Young VR, Panjer HH (1997) Axiomatic characterization of insurance prices. Insurance Math. Econom. 21(2):173–183.CrossrefGoogle Scholar
  • White H (1980) A heteroskedasticity-consistent covariance matrix estimator and a direct test for heteroskedasticity. Econometrica 48(4):817–838.CrossrefGoogle Scholar
  • Xu H, Zhang N (2022) Implications of data anonymization on the statistical evidence of disparity. Management Sci. 68(4):2600–2618.LinkGoogle Scholar
  • Xu Y, Armony M, Ghose A (2021) The interplay between online reviews and physician demand: An empirical investigation. Management Sci. 67(12):7344–7361.LinkGoogle Scholar
  • Zhang X, Du Q, Zhang Z (2022) A theory-driven machine learning system for financial disinformation detection. Production Oper. Management 31(8):3160–3179.CrossrefGoogle Scholar
  • Zhang X, Pérez-Stable EJ, Bourne PE, Peprah E, Duru OK, Breen N, Berrigan D, et al. (2017) Big data science: Opportunities and challenges to address minority health and health disparities in the 21st century. Ethnicity Disease 27(2):95–106.CrossrefGoogle Scholar
  • Zheng XX, Li DF, Liu Z, Jia F, Sheu JB (2019) Coordinating a closed-loop supply chain with fairness concerns through variable-weighted Shapley values. Transportation Res. Part E Logist. Transportation Rev. 126:227–253.CrossrefGoogle Scholar
  • Zhou WX, Bose K, Fan J, Liu H (2018) A new perspective on robust m-estimation: Finite sample theory and applications to dependence-adjusted multiple testing. Ann. Statist. 46(5):1904–1931.CrossrefGoogle Scholar
INFORMS site uses cookies to store information on your computer. Some are essential to make our site work; Others help us improve the user experience. By using this site, you consent to the placement of these cookies. Please read our Privacy Statement to learn more.