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The goal of this thesis is to model and predict the probability of default (PD) for a mortgage portfolio. In order to achieve this goal, logistic regression and survival analysis methods are applied to a large dataset of mortgage portfolios recorded by one of the national banks. While logistic regression has been commonly used for modeling PD in the banking industry, survival analysis has not been explored extensively in the area. Here, survival analysis is offered as a competitive alternativedoi:10.23860/thesis-zhang-qingfen-2015 fatcat:pvvlilzhkjcedcswbpkn4he2py