A Least-Squares Monte Carlo Framework in Proxy Modeling of Life Insurance Companies

Anne-Sophie Krah, Zoran Nikolić and Ralf Korn
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Anne-Sophie Krah: Department of Mathematics, TU Kaiserslautern, Erwin Schrödinger Strasse, Geb. 48, 67653 Kaiserslautern, Germany
Zoran Nikolić: Mathematical Institute, University Cologne, Weyertal 86-90, 50931 Cologne, Germany
Ralf Korn: Department of Mathematics, TU Kaiserslautern, Erwin Schrödinger Strasse, Geb. 48, 67653 Kaiserslautern, Germany

Risks, 2018, vol. 6, issue 2, 1-26

Abstract: The Solvency II directive asks insurance companies to derive their solvency capital requirement from the full loss distribution over the coming year. While this is in general computationally infeasible in the life insurance business, an application of the Least-Squares Monte Carlo (LSMC) method offers a possibility to overcome this computational challenge. We outline in detail the challenges a life insurer faces, the theoretical basis of the LSMC method and the necessary steps on the way to a reliable proxy modeling in the life insurance business. Further, we illustrate the advantages of the LSMC approach via presenting (slightly disguised) real-world applications.

Keywords: Least-Squares Monte Carlo method; proxy modeling; life insurance; Solvency II (search for similar items in EconPapers)
JEL-codes: C G0 G1 G2 G3 K2 M2 M4 (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (19)

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