This paper shows how to improve the measurement of credit scoring by means of factor clustering. The improved measurement applies, in particular, to small and medium enterprises (SMEs) involved in P2P lending. The approach explores the concept of familiarity which relies on the notion that the...

Peer to peer (P2P) lending in Indonesia has been growing rapidly, therefore there is the potential for disruptive innovation processes in the financial sector. The aim of this study is to examine the impact of the growth of P2P lending on the growth of bank lending for micro, small and medium...

This study aims to examine the impact of the growth of peer-to-peer (P2P) lending on the growth of rural bank lending. Further, this study investigates the outcome of the partnership agreement between the Rural Bank Association and Financial Technology (FinTech) Association in the last quarter...

The purpose of this study is to examine the effect of P2P lending on bank credit in each type/segment of banking credit consisting of working capital credit, investment credit, and consumer credit in the period before and during the occurrence of the Covid-19 exogenous shock. Examining the...

Fintechs are believed to help expand credit access to underserved consumers without taking on additional risk. We compare the performance efficiency of LendingClub's unsecured personal loans with similar loans originated by banks. Using stochastic frontier estimation, we decompose the observed...

Although psychometric features have been considered for alternative credit scoring, they have not yet been applied to peer-to-peer (P2P) lending because such information is not available on platforms. This study proposed an alternative credit scoring model for P2P lending by extracting typical...

In the peer-to-peer (P2P) lending market, current studies focus on two categories of approaches to evaluate the loans, thus providing investment suggestions to the investors: credit scoring (i.e., predicting the credit risk) and profit scoring (i.e., predicting the profitability). However,...

Purpose The purpose of this paper is to compare nine different models to evaluate consumer credit risk, which are the following: Logistic Regression (LR), Naive Bayes (NB), Linear Discriminant Analysis (LDA), k-Nearest Neighbor (k-NN), Support Vector Machine (SVM), Classification and Regression...