Loan Payment Prediction Using Adaptive Neuro Fuzzy Inference System

Emha Taufiq Luthfi (Universitas AMIKOM Yogyakarta, Indonesia); Ferry Wahyu Wibowo (Universitas Amikom Yogyakarta, Indonesia)

The financial data in banks or other financial institution are needed for checking, credit, transaction, etc. In this case, the data must be accurate, complete, and high quality. The analysis of data could be used to predict a loan repayment and customer credit plan. Meanwhile data can also be used to perform the classification or clustering to customers, so it is useful for bank or other financial institution to check the ability of customer to make a loan payments. In this paper aims to establish a predictive model based on Adaptive Neuro Fuzzy Inference System (ANFIS) as an analysis of loan payments financing plan of the customer. It provides an assessment of the possibility of the smooth financing proposed by the customer. The system built is expected to help for the finance officer to taking a decisions on the approval of the financing plan by the customer. Implementation of the overall system is implemented using MATLAB application utilizing Fuzzy Logic Toolbox. Implementation carried out into two parts, namely the function of ANFIS modeling systems and the assessment systems of the customer financing plans.

Journal: International journal of simulation: systems, science & technology V18

Published: Dec 30, 2017

DOI: 10.5013/IJSSST.a.18.04.09