We suggest a new dynamic modeling framework for credit rating threat assessment that extends the prevailing credit scoring types crafted on historic details static settings. The driving notion mimics the basic principle of movies, by composing the design using a sequence of snapshots, instead of an individual photograph. In doing this, the dynamic
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Survival types with time-varying covariates (TVCs) are broadly Employed in the literature on credit history chance prediction. Having said that, when these covariates are endogenous, the inclusion treatment has become restricted to practices such as lagging these variables or managing them as exogenous. That results in attainable biased estimators
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