A Multistate Analysis of Policyholder Behaviour in Life Insurance—Lasso-Based Modelling Approaches

Lucas Reck (), Johannes Schupp and Andreas Reuß
Additional contact information
Lucas Reck: Institute for Finance and Actuarial Sciences (ifa), 89081 Ulm, Germany
Johannes Schupp: Institute for Finance and Actuarial Sciences (ifa), 89081 Ulm, Germany
Andreas Reuß: Institute for Finance and Actuarial Sciences (ifa), 89081 Ulm, Germany

Risks, 2025, vol. 13, issue 4, 1-28

Abstract: Holders of life insurance policies can exercise various options that lead to contract modifications, e.g., full surrender, partial surrender, and paid-up and dynamic premium increase options. Transitions between these contract states materially affect (current and future) cash flows and thus represent a serious source of uncertainty for an insurance company. It is common practice to determine best-estimate assumptions for these transitions independently, i.e., without considering joint determinants of the different aspects of policyholder behaviour. The recent literature also incorporates multistate classical statistical models. Our paper shows how consistent best-estimate transition rates for multiple status transitions can be derived using data science methods. More specifically, we extend existing multivariate approaches based on established statistical models (generalised linear models) with the Lasso method, such that the key drivers for each transition can be identified automatically. We discuss the performance, the complexity and the practical applicability of the different modelling approaches based on data from a European insurer.

Keywords: multistate; multi-class; lapse rate; paid-up; life insurance; Lasso (search for similar items in EconPapers)
JEL-codes: C G0 G1 G2 G3 K2 M2 M4 (search for similar items in EconPapers)
Date: 2025
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2227-9091/13/4/73/pdf (application/pdf)
https://www.mdpi.com/2227-9091/13/4/73/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jrisks:v:13:y:2025:i:4:p:73-:d:1631150

Access Statistics for this article

Risks is currently edited by Mr. Claude Zhang

More articles in Risks from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().