Can Regulation Affect the Solvency of Insurers? New Evidence from European Insurers

Abstract

Successive crises in the early twenty-first century prompted regulators around the world to ask financial institutions to implement a series of regulations. These measures aimed to increase transparency, improve consumer and investor protection, restructure financial capital, stabilize insurance and pension markets, and improve solvency. The Solvency II framework introduced in the European Union applied these principles to insurance companies. This study attempts to predict the solvency of an insurer within a set of European insurers. The dataset consists of 29 insurance groups that operate across the European Union with a country of origin within the European Union for the period 2016 to 2020. The variables were constructed from annual financial statements retrieved from (Thomson Reuters) DataStream. The solvency capital requirement ratios were obtained manually from the solvency financial condition reports of each group. Regularized linear regression applying a ℓ1/ least-absolute-shrinkage-and-selection-operator penalty showed that the reinvestment rate, cash and equivalents, long term investment, and losses-benefits-and-adjustments expenses have the greatest predictive impact on the solvency of insurers. The contribution of this paper lies in the identification of determinants that allow insurance companies to maintain strong solvency capital requirement ratios so that they can maintain internal operations with minimal interruption.

Keywords: Insurance companies, solvency, machine learning, LASSO regression

JEL Classification: G17, G22, G28