Estimating Extreme Cancellation Rates In Life Insurance

Munich Risk and Insurance Center Working Paper 33

36 Pages Posted: 3 Jun 2019

See all articles by Francesca Biagini

Francesca Biagini

Ludwig Maximilian University of Munich (LMU) - Faculty of Mathematics

Tobias Huber

Ludwig-Maximilians-Universität München

Johannes Gerd Jaspersen

Ludwig Maximilian University of Munich (LMU) - Faculty of Business Administration (Munich School of Management)

Andrea Mazzon

Ludwig-Maximilians-Universität München

Date Written: May 12, 2019

Abstract

Extreme cancellation rates can severely distort life insurers' liquidity and profitability. Due to the rarity of the event and the complexity of policyholder behavior, the risk assessment of such a scenario is difficult. We introduce an estimation method that can utilize panel data on the company level to estimate the probability distribution function of a mass cancellation event as long as this function is continuous. The panel structure is taken into account by including annual fixed effects and company-level covariates. We demonstrate the method using cancellation rates from U.S. life insurers. We also apply it to German data and reveal difficulties in the European insurance regulation framework Solvency II. Our method allows risk managers and regulators to estimate extreme cancellation rates. In particular, we discuss the (in-)adequacy of the mass lapse scenario assumed in Solvency II, which can lead companies to have solvency capital requirements in the hundreds of millions.

Keywords: Extreme Value Theory, Dynamic Peaks Over Threshold, Life Insurance, Mass Cancellation

JEL Classification: C14, G18, G22, G32

Suggested Citation

Biagini, Francesca and Huber, Tobias and Jaspersen, Johannes Gerd and Mazzon, Andrea, Estimating Extreme Cancellation Rates In Life Insurance (May 12, 2019). Munich Risk and Insurance Center Working Paper 33. Available at SSRN: https://ssrn.com/abstract=3387043

Francesca Biagini

Ludwig Maximilian University of Munich (LMU) - Faculty of Mathematics ( email )

Theresienstrasse 39
Munich
Germany

Tobias Huber (Contact Author)

Ludwig-Maximilians-Universität München ( email )

Johannes Gerd Jaspersen

Ludwig Maximilian University of Munich (LMU) - Faculty of Business Administration (Munich School of Management) ( email )

Kaulbachstr. 45
Munich, DE 80539
Germany

Andrea Mazzon

Ludwig-Maximilians-Universität München ( email )

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