The inclusion of time-varying covariates into survival analysis has led to raised predictions of time to default in behavioural credit scoring products. However, when these time-varying covariates are endogenous, there are two big troubles: estimation bias from the survival model and deficiency of a prediction framework for potential values of both
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Survival versions with time-varying covariates (TVCs) are extensively used in the literature on credit score hazard prediction. Even so, when these covariates are endogenous, the inclusion process has long been restricted to procedures for instance lagging these variables or managing them as exogenous. That leads to attainable biased estimators (wi