Análise de risco de crédito com o uso de regressão logística

Abstract

The objective of this study was to apply the logistic regression technique in the development of a model for predicting credit scoring using data from a financial institution. From a sample of 20,000 data, three sub-samples were defined: one sample for model construction (8,000 data) and two other ones for validation, each one with 6,000 data. In the three sub-samples, there was an equitable distribution of good and bad clients, classified into these categories according to institutional standards. The logistic regression model presented adequate indicators of data adjustment in the results, which can be used in the decision-making process of bank credit concessions.

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