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Abstract
Credit risk prediction is very beneficial for the bank or financing institution in making credit decisions. In the decisionmaking, a decision maker in a banking must be able to take the right decision to accept or reject the credit application. If the decision maker is right in making a decision, then the bank will get customers who support the health and sustainability of the banking business, and vice versa. In this study, Support Vector Machien (SVM) is implemented to predict the crediting risk. The data used is data obtained from one of the financing institutions. By using different activation functions, 80.9524% accuracy is obtained or there are 51 precisely predictable data from 63 existing data