Big Data-Based Peer-to-Peer Lending Fintech: Surveillance System through Utilization of Google Play Review
26 Pages Posted: 16 Oct 2019
Date Written: April 12, 2019
Peer-to-peer lending (P2PL) FinTech is growing rapidly in Indonesia. With its flexibility and simplicity, P2PL reduces the financing gap that cannot be fulfilled by banks. However, the rapid development of P2PL also raises a number of problems that burden users such as unethical debt collection methods and the imposition of excessive interest rate and other costs that potentially threaten national financial system stability. Therefore, by utilizing big data, which in this case is 40,650 reviews from 110 P2PLs obtained from Google Play from March 2016 to August 2018, we build a big data-based P2PL surveillance system based on four aspects: legality, review rating, debt collection methods, and level of interest rates and other costs. By using relational database, structured query language (SQL), and text analysis, we found that (i) the majority of P2PL in Google Play are unauthorized; (ii) on average, authorized P2PL receives a better review rating; (iii) there are a lot of negative reviews related to unethical debt collection methods and excessive imposition of interest rate; and (iv) four P2PLs required special supervision from the Indonesia Financial Service Authority (OJK). Furthermore, the OJK should not passively wait for official reports to be filed by the public regarding violations of P2PL businesses. Through this big data-based system, the OJK can find these violations proactively because the system can act as an early warning system for the OJK in terms of P2PL surveillance.
Keywords: fintech, peer to peer lending, big data, review, Google Play
JEL Classification: G23, G24, G28
Suggested Citation: Suggested Citation