Florian Schreiber

Portfolio Optimization Under Solvency II: Implicit Constraints Imposed by the Market Risk Standard Formula

We consider the issue of optimizing an insurance companys asset allocation in the context of portfolio theory when the firm needs to adhere to the market risk capital requirements of Solvency II. The discussion starts with a brief review of the standard formula and the introduction of a parsimonious partial internal model. Subsequently, we estimate empirical risk-return profiles for the main asset classes held by insurers and run a quadratic optimization program to derive nondominated frontiers with budget, short-sale, and investment constraints. We then compute the respective capital charges under both solvency models and identify those efficient portfolio compositions that are permitted for an exogenously given amount of equity. Finally, we consider a systematically selected set of inefficient portfolios and check their admissibility, too. Our results document that the standard formula is unable to distinguish investments on the basis of risk-return profiles and does hence not produce economically sensible results. Therefore, the introduction of Solvency II in its current form might cause severe asset management biases in the European insurance sector.

On consumer preferences and the willingness to pay for term life insurance

We run a choice-based conjoint (CBC) analysis for term life insurance on a sample of 2017 German consumers using data from web-based experiments. Individual-level part-worth profiles are estimated by means of a hierarchical Bayes model. Drawing on the elicited preference structures, we then compute relative attribute importances and different willingness to pay measures. In addition, we present comprehensive simulation results for a realistic competitive setting that allows us to assess product switching as well as market expansion effects. On average, brand, critical illness cover, and underwriting procedure turn out to be the most important nonprice product attributes. Hence, if a policy comprises their favored specifications, customers accept substantial markups in the monthly premium. Furthermore, preferences vary considerably across the sample. While some individuals are prepared to pay relatively high monthly premiums, a large fraction exhibits no willingness to pay for term life insurance at all, presumably due to the absence of a need for mortality risk coverage. We also illustrate that utility-driven product optimization is well-suited to gain market shares, avoid competitive price pressure, and access additional profit potential. Finally, based on estimated demand sensitivities and a set of cost assumptions, it is shown that insurers require an in-depth understanding of preferences to identify the profit-maximizing price.

Identification of Customer Groups in the German Term Life Market: A Benefit Segmentation

We run a benefit segmentation of 2017 insurance consumers in order to analyze the structure and heterogeneity of the German term life insurance market. The consumers’ preference information has been obtained through a choice-based conjoint (CBC) experiment and a subsequent hierarchical Bayes (HB) estimation routine. Drawing on their part-worth utility profiles, we first construct a diverse cluster ensemble, comprising a total of 1624 hierarchical and k-means solutions based on different linkage criterions and sensibly drawn starting points. Then, final group memberships are determined by means of consensus clustering. Our empirical results indicate that the market divides into three segments characterized by substantially different consumer types with distinct demands and needs. While the first group is clearly driven by the premium, the opposite holds true for the brand-loyal group. Additionally, the market is completed by a third segment with in-between preference structures. Hence, both brand insurers and companies with a lower reputation face consumer groups that almost perfectly fit their provider profiles. More specifically, by offering segment-oriented products, an efficient resource allocation is fostered and the basis for long-term business relationships is laid. This is becoming increasingly important, because ongoing regulatory efforts, low interest rates, and market entrances from InsuranceTech start-ups and tech giants aiming to utilize the market’s enormous hidden potential are changing the competitive environment significantly. A consequent alignment of important strategic decisions related to product innovations, pricing, and distribution channels to our identified consumer segments enables incumbents to maintain a stable and sustainable market share and profitability.