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We suggest a fresh dynamic modeling framework for credit history risk evaluation that extends the prevailing credit score scoring products developed upon historic facts static settings. The driving strategy mimics the theory of movies, by composing the product which has a sequence of snapshots, rather than a single photograph. In doing this, the dy

Survival models with time-varying covariates (TVCs) are broadly used in the literature on credit rating threat prediction. On the other hand, when these covariates are endogenous, the inclusion course of action has been limited to procedures which include lagging these variables or treating them as exogenous. That causes achievable biased estimator