Maria Rocha Sousa

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We propose a new dynamic modeling framework for credit risk assessment that extends the prevailing credit scoring models built upon historical data static settings. The driving idea mimics the principle of films, by composing themodel with a sequence of snapshots, rather than a single photograph. In doing so, the dynamic modeling consists of sequential(More)
Traditionally retail banks have supported the credit decision-making on scorecards developed for predicting default in a six-month period or more. However, the underlying pay/no pay cycles justify a decision in a 30-day period. In this work several classification models are built on this assumption. We start by assessing binary scorecards, assigning credit(More)
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