Predicting Expected Profit in Ongoing Peer-to-Peer Loans with Survival Analysis-Based Profit Scoring

A4 Conference proceedings


Internal Authors/Editors


Publication Details

List of Authors: Ajay Byanjankar, Markus Viljanen
Publication year: 2019
Book title: Intelligent Decision Technologies 2019
Title of series: Intelligent Decision Technologies 2019: Proceedings of the 11th KES International Conference on Intelligent Decision Technologies (KES-IDT 2019)
Volume number: 142
Start page: 15
End page: 26
ISBN: 978-981-13-8311-3
ISSN: 2190-3018


Abstract

The growing popularity of P2P lending has attracted more borrowers and lenders to the sector. With the growth in the popularity of P2P lending, there have been many studies focusing on analyzing credit risk in P2P lending. However, the credit risk is only a part of the story. The higher interest rates are allocated to the riskier loans, and the higher interest rates may or may not in fact compensate for the defaults expected. Therefore, the profit of a loan depends on both the interest rate and the default probability. Since investors are ultimately concerned with return on investment, models should help investors to predict the profit as accurately as possible. We develop a model that predicts the expected profit of a loan using survival analysis-based monthly default probability. Our approach extends previous profit scoring approaches, since it can be applied to any loan data set, including current data sets with many ongoing loans.


Last updated on 2020-06-06 at 04:12