Modelo de escoragem de crédito nas operações a participantes de uma EFPC

Abstract

Credit plays an important economic and social role, by enabling companies to increase their level of activity through investment received through credit. This economic mechanism brings benefits to the lender, since the return on the interest rate, embedded in the operation, is higher than that of many investments. The credit granted to the participants of the Closed Complementary Pension Funds (Entidades Fechadas de Previdência Complementar - EFPC) is a profitable and stable investment in different economic cycles, as long as the levels of default are controlled. In this context the objective of this study is to propose a credit bracing model to mitigate the credit risk in transactions with participants in the investment portfolio of a private pension fund (EFPC). Using the logistic regression statistical technique to estimate the probability of credit risk, the model was developed based on a sample of participants who have active loan agreements with EFPC. The explanatory variables of the model were obtained from the participants' registration and financial records, of which three obtained significant results. The logistic regression model showed adequate data adjustment indicators, and can be used in the decision support process for granting credit in operations to participants.