PENILAIAN KREDIT UNTUK UKM MENGGUNAKAN HYBRID BWM DAN TOPSIS PADA BANK SYARIAH DI INDONESIA

Abstract

This research develops and validates a SME credit risk prediction system by applying a multi-criteria credit scoring model. The model was built using the best-worst method (BWM) and the preferred order of similarity to ideal solution (TOPSIS) technique. BWM first sets the weighting criteria and TOPSIS is applied to evaluate SMEs. Real-life case studies are examined to demonstrate the effectiveness of the proposed model. The results showed that that collateral can be bound in accordance with the provisions, history of credit, and current ratio were the most important factors in lending, followed by customer business sector category, continuity of supply of raw materials, and collateral adequacy requirements. This model can help financial institutions provide an easy way to identify potential SMEs for loans and encourage further research into alternative approaches.