Credit scoring for Cooperative of financial services using logistic regression estimated by genetic algorithm - Mustafa, Mamat; Sukono, Firman; Asep, Sholahuddin (2014)
One of the Cooperative of Financial Services is disbursed loans to debtors (members and prospective members). In lending (provision of credit) is likely to arise the problem, namely the possibility of debt default by the debtor. To anticipate the risk of default (credit risk), to prospective debtors applying for credit risk analysis was performed using credit scoring. In this paper the analysis of credit scoring is done using logistic regression model, which is estimated using genetic algorithms. As a numerical illustration, the method used to analyze the credit scoring on a cooperative of financial services in Indonesia. Of the eight factors were analyzed, it was only six factors that significantly influence to the risk of default. Six of these factors include: number of dependents, the amount of savings, the value of collateral, monthly income, credit limit is realized, and the loan repayment period.