Performance Mapping Of Fintech Peer To Peer Lending (P2PL) in Indonesia

Abstract

The development of Peer-to-Peer Lending (P2PL) fintech in Indonesia was growing fast. In the midst of this rapid growth, a volatile pattern shows the dynamics of the P2PL in terms of its performance. This study aims to map the performance of fintech P2PL. The data used are the total disbursement of loans and non-performing loans obtained from each company's website and aggregate data published by the Financial Services Authority (OJK). In this study, a website scraping from 102 fintech companies was obtained from each platform to obtain Non-Performing Loan (NPL) value and accumulated loan distribution. This study also uses the hierarchical clustering method to group each P2PL based on NPL and accumulated loan disbursement. Based on the hierarchical clustering analysis, three clusters distinguish the characteristics of grouping P2PL companies. In first cluster, there are 3 companies with high distribution and low NPL, while in the second cluster consists of 13 companies categorized as poor performance because they related to the low disbursement and high NPL value. In the third cluster there are 71 companies with moderate disbursement and NPL. Based on this mapping several things need to be improved, starting from developing a risk management and monitoring system, lending and operating supervision.

Keywords: Fintech, peer to peer lending, clustering, hierarchical clustering, NPL