Sustainable Architecture for Finance in Europe (SAFE)
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- Economics of Information (1)
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- Interest Rate Risk (1)
- Lapse Risk (1)
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Different insurance activities exhibit different levels of persistence of shocks and volatility. For example, life insurance is typically more persistent but less volatile than non-life insurance. We examine how diversification among life, non-life insurance, and active reinsurance business affects an insurer's contribution and exposure to the risk of other companies. Our model shows that a counterparty's credit risk exposure to an insurance group substantially depends on the relative proportion of the insurance group's life and non-life business. The empirical analysis confirms this finding with respect to several measures for spillover risk. The optimal proportion of life business that minimizes spillover risk decreases with leverage of the insurance group, and increases with active reinsurance business.
This paper investigates the effects of a rise in interest rate and lapse risk of endowment life insurance policies on the liquidity and solvency of life insurers. We model the book and market value balance sheet of an average German life insurer, subject to both GAAP and Solvency II regulation, featuring an existing back book of policies and an existing asset allocation calibrated by historical data. The balance sheet is then projected forward under stochastic financial markets. Lapse rates are modeled stochastically and depend on the granted guaranteed rate of return and prevailing level of interest rates. Our results suggest that in the case of a sharp increase in interest rates, policyholders sharply increase lapses and the solvency position of the insurer deteriorates in the short-run. This result is particularly driven by the interaction between a reduction in the market value of assets, large guarantees for existing policies, and a very slow adjustment of asset returns to interest rates. A sharp or gradual rise in interest rates is associated with substantial and persistent liquidity needs, that are particularly driven by lapse rates.
We study the impact of estimation errors of firms on social welfare. For this purpose, we present a model of the insurance market in which insurers face parameter uncertainty about expected loss sizes. As consumers react to under- and overestimation by increasing and decreasing demand, respectively, insurers require a safety loading for parameter uncertainty. If the safety loading is too small, less risk averse consumers benefit from less informed insurers by speculating on them underestimating expected losses. Otherwise, social welfare increases with insurers’ information. We empirically estimate safety loadings in the US property and casualty insurance market, and show that these are likely to be sufficiently large for consumers to benefit from more informed insurers.