Models mortgage insurance claims using Markov chains and GLMs, indicating implications for forecasting technical liabilities.
This paper covers experiences in modeling mortgage insurance claims. In Section 2, mortgage insurance claims are considered an absorbing state in a Markov chain that involves transitions between the states of healthy, in arrears, property in possession, property sold, loan discharged, and claim. Section 3 considers the representation of this process by a cascade of five frequency generalized linear models (GLMs) and a further GLM for claim size. These models are applied to the forecast of technical liabilities in Section 4 and the estimation of the associated forecast error in Section 5.
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Taylor et al. (2007) studied this question.
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