The research was conducted by the Canada Research Chair in Risk Management at HEC Montréal and the Department of Economics at the University of Montréal, led by Georges Dionne, full Professor, Department of Finance, HEC Montréal.
Duration of the project: 2014-2017
The project’s objective was to measure the various risks faced by American Non-Life insurers and infer their demand for reinsurance, considering the risk management alternatives available. Reinsurance supply parameters were taken into account to assess the equilibrium of the reinsurance market.
Firstly, the researchers studied the insurer’s risk exposure and hedging of different risks – mainly underwriting risk, asset-liability matching risk, counterparty risk, market risk, operational risk and liquidity risk. There was a particular focus on the measurement of systemic risk during the latest financial crisis, because expert opinions diverge greatly on this subject. The drivers behind the demand for reinsurance were analyzed by monitoring for different factors and simultaneously considering other concurrent hedging activities. Through this analysis, the researchers were able to identify the causes of weaker demand for reinsurance. The results point to a trade-off between getting higher returns on risky investments and being able to compensate clients at a low cost when unexpected claims happen. Unexpected claims can be protected by reinsurance, which introduces a second trade-off between reinsurance demand and liquidity creation. This trade-off can be more significant for insurers with fewer diversification opportunities. The main empirical results, from regularized GMM (Generalized Method of Moments) and ML-SME (the Maximum Likelihood estimation of Structural Equation Modeling) methods of estimation, show similar positive bi-causal effects between liquidity creation and reinsurance demand for small insurers (22% of insurance activity). The link between the two activities is not significant for large insurers (60% of insurance activity). Mixed results were obtained for medium insurers. In all estimations, the standard GMM model was rejected.
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