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Regulatory solvency prediction in property-liability insurance: risk-based capital, audit ratios, and cash flow simulation

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Author Info

  • J. David Cummins
  • Martin F. Grace
  • Richard D. Phillips

Abstract

This paper analyzes the accuracy of the principal models used by U.S. insurance regulators to predict insolvencies in the property-liability insurance industry and compares these models with a relatively new solvency testing approach--cash flow simulation. Specifically, we compare the risk-based capital (RBC) system introduced by the National Association of Insurance Commissioners (NAIC) in 1994, the FAST (Financial Analysis and Surveillance Tracking) audit ratio system used by the NAIC, and a cash flow simulation model developed by the authors. Both the RBC and FAST systems are static, ratio-based approaches to solvency testing, whereas the cash flow simulation model implements dynamic financial analysis. Logistic regression analysis is used to test the models for a large sample of solvent and insolvent property-liability insurers, using data from the years 1990-1992 to predict insolvencies over three-year prediction horizons. We find that the FAST system dominates RBC as a static method for predicting insurer insolvencies. Further, we find the cash flow simulation variables add significant explanatory power to the regressions and lead to more accurate solvency prediction than the ratio-based models taken alone.

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File URL: http://www.philadelphiafed.org/research-and-data/publications/working-papers/1998/wp98-20.pdf
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Bibliographic Info

Paper provided by Federal Reserve Bank of Philadelphia in its series Working Papers with number 98-20.

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Date of creation: 1998
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Handle: RePEc:fip:fedpwp:98-20

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Related research

Keywords: Insurance industry;

References

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  1. J. David Cummins & Scott E. Harrington & Robert Klein, 1995. "nsolvency Experience, Risk-Based Capital, and Prompt Corrective Action in Property-Liability Insurance," Center for Financial Institutions Working Papers 95-06, Wharton School Center for Financial Institutions, University of Pennsylvania.
  2. Lamm-Tennant, Joan & Starks, Laura T, 1993. "Stock versus Mutual Ownership Structures: The Risk Implications," The Journal of Business, University of Chicago Press, vol. 66(1), pages 29-46, January.
  3. Cummins, J. David & Harrington, Scott E. & Klein, Robert, 1995. "Insolvency experience, risk-based capital, and prompt corrective action in property-liability insurance," Journal of Banking & Finance, Elsevier, vol. 19(3-4), pages 511-527, June.
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Cited by:
  1. Udaibir S. Das & Richard Podpiera & Nigel Davies, 2003. "Insurance and Issues in Financial Soundness," IMF Working Papers 03/138, International Monetary Fund.
  2. Eling, Martin & Gatzert, Nadine & Schmeiser, Hato, 2009. "Minimum standards for investment performance: A new perspective on non-life insurer solvency," Insurance: Mathematics and Economics, Elsevier, vol. 45(1), pages 113-122, August.
  3. Carson, James & Hoyt, Robert, 2000. "Evaluating the risk of life insurer insolvency: implications from the US for the European Union," Journal of Multinational Financial Management, Elsevier, vol. 10(3-4), pages 297-314, December.
  4. P. Picard, 2000. "Les nouveaux enjeux de la régulation des marchés d'assurance," THEMA Working Papers 2000-53, THEMA (THéorie Economique, Modélisation et Applications), Université de Cergy-Pontoise.
  5. Berry-Stölzle, Thomas R. & Koissi, Marie-Claire & Shapiro, Arnold F., 2010. "Detecting fuzzy relationships in regression models: The case of insurer solvency surveillance in Germany," Insurance: Mathematics and Economics, Elsevier, vol. 46(3), pages 554-567, June.
  6. Kessler, Denis, 2008. "Insurance market mechanisms and government interventions," Journal of Banking & Finance, Elsevier, vol. 32(1), pages 4-14, January.
  7. Benjamin Lorent, 2010. "Insurance Solvency Regulation: Regulatory Approaches Compared," Working Papers CEB 10-041, ULB -- Universite Libre de Bruxelles.
  8. Leverty, J. Tyler & Grace, Martin F., 2010. "The robustness of output measures in property-liability insurance efficiency studies," Journal of Banking & Finance, Elsevier, vol. 34(7), pages 1510-1524, July.
  9. J. Cummins & Gregory Nini, 2002. "Optimal Capital Utilization by Financial Firms: Evidence from the Property-Liability Insurance Industry," Journal of Financial Services Research, Springer, vol. 21(1), pages 15-53, February.
  10. Steven Pottier & David Sommer, 2002. "The Effectiveness of Public and Private Sector Summary Risk Measures in Predicting Insurer Insolvencies," Journal of Financial Services Research, Springer, vol. 21(1), pages 101-116, February.
  11. Reisz, Alexander S. & Perlich, Claudia, 2007. "A market-based framework for bankruptcy prediction," Journal of Financial Stability, Elsevier, vol. 3(2), pages 85-131, July.

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  1. Deterministische Simulationsmodelle als Insolvenzprognoseverfahren in Wikipedia (German)

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