Program Description
Perry Mehta of Prudential will introduce sound practices in the measurement of credit risk for insurance companies, including the risk drivers for reinsurance firms. The approach by the rating agencies (Moody’s, S&P) has strengths and limitations for the purpose of counterparty risk measurement. This part of the presentation will outline key elements of more risk-sensitive and dynamic approaches to credit risk measurement in the insurance and reinsurance industries.
Stuart Hayes of Towers Watson will present a more specific approach to counterparty credit risk measurement for reinsurance firms. With the subprime credit crisis and ensuing economic crisis, counterparty risk has become a central issue in evaluating financial transactions. For many Property & Casualty insurance and reinsurance organizations, reinsurance counterparty risk represents the largest source of potential bad debt exposure.
Traditional methods of evaluating this risk may fall short of rating agencies and companies’ internal needs. A more sophisticated and credit-based approach is possible using a stochastic simulation approach based on information readily available from the bond market:
• Financial strength ratings (S&P, Moody’s, etc.)
• Transition matrices, which provide probabilistic expectations of the movement in financial strength ratings over time, including default rates
• Recovery rates, or the amount of financial recovery historically available in the case of default
The session will provide an overview of a transition matrix / recovery rate approach to evaluating reinsurance counterparty risk. Assumptions and parameter issues involving base-case and stressed scenarios will be discussed, and a numerical example provided to enhance understanding of the methodology.