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Predictive Modeling and Expectable Loss Analysis for Borrower Defaults of Mortgage Loans
Omer L. Gebizlioglu, A. Belma Ozturkkal
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DOI:10.17265/1548-6583/2018.05.001
Home mortgage loan lending firms are exposed to many business risks. This paper focuses on the mortgage loan borrower risks and proposes a prospective loss analysis approach in regard to loan repayment defaults of borrowers. For this purpose, a predictive modeling is presented in three stages. In the first stage, occurrence of borrower defaults in a mortgage loans portfolio is modeled through the generalized linear models (GLMs) type regressions for which we specify a logistic distribution for default events. The second stage of modeling develops a survival analysis in order to estimate survival probability and hazard rate functions for individual loans. Ultimately, an expectable loss amount model is presented in the third stage as a function of conditional survival probabilities and corresponding hazard rates at loan levels. Throughout all modeling stages, a large and real data set is used as an empirical analysis case by which detailed interpretations and practical implications of the obtained results are stated.
mortgage loan, borrower default, default loss, risk measurement, GLMs, logistic and log-logistic distributions, survival and hazard rate functions