Public Credit Registries contain data about borrowers' behaviour in the financial system and are, therefore, a valuable source of credit information. This paper examines the utility of different sets of information available at the Public Credit Register of the Central Bank of Brazil for predicting default of corporate credit exposures. It measures the quality increase in the estimates of probabilities of default in the situation where nonnegative information is included in the modelling or when financial institutions share information through the PCR. In both cases, not only discrimination and adjustment of the logistic regression models are improved, but also effects on credit extension and reduction of default rates in the economy are pointed out.
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Paper provided by Central Bank of Brazil, Research Department in its series Working Papers Series with number
119.