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Open AccessArticle

Credibility Methods for Individual Life Insurance

1
BlueCrest Capital, New York, NY 10022, USA
2
PayPal, Inc., San Jose, CA 95131, USA
3
Unum, Chattanooga, TN 37402, USA
4
Department of Mathematics, University of Michigan, Ann Arbor, MI 48109-1043, USA
5
Mutual of Omaha Insurance Co., Omaha, NE 68175-1004, USA
*
Author to whom correspondence should be addressed.
Risks 2018, 6(4), 144; https://doi.org/10.3390/risks6040144
Received: 17 September 2018 / Revised: 5 November 2018 / Accepted: 15 November 2018 / Published: 11 December 2018
(This article belongs to the Special Issue Young Researchers in Insurance and Risk Management)
Credibility theory is used widely in group health and casualty insurance. However, it is generally not used in individual life and annuity business. With the introduction of principle-based reserving (PBR), which relies more heavily on company-specific experience, credibility theory is becoming increasingly important for life actuaries. In this paper, we review the two most commonly used credibility methods: limited fluctuation and greatest accuracy (Bühlmann) credibility. We apply the limited fluctuation method to M Financial Group’s experience data and describe some general qualitative observations. In addition, we use simulation to generate a universe of data and compute Limited Fluctuation and greatest accuracy credibility factors for actual-to-expected (A/E) mortality ratios. We also compare the two credibility factors to an intuitive benchmark credibility measure. We see that for our simulated data set, the limited fluctuation factors are significantly lower than the greatest accuracy factors, particularly for low numbers of claims. Thus, the limited fluctuation method may understate the credibility for companies with favorable mortality experience. The greatest accuracy method has a stronger mathematical foundation, but it generally cannot be applied in practice because of data constraints. The National Association of Insurance Commissioners (NAIC) recognizes and is addressing the need for life insurance experience data in support of PBR—this is an area of current work. View Full-Text
Keywords: credibility; principle-based reserving; simulation credibility; principle-based reserving; simulation
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Gong, Y.M.; Li, Z.; Milazzo, M.; Moore, K.; Provencher, M. Credibility Methods for Individual Life Insurance. Risks 2018, 6, 144.

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