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

Ajay Byanjankar, Markus Viljanen

Research output: Chapter in Book/Conference proceedingConference contributionScientificpeer-review

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.

Original languageUndefined/Unknown
Title of host publicationIntelligent Decision Technologies 2019
PublisherSpringer
Pages15–26
ISBN (Print)978-981-13-8311-3
DOIs
Publication statusPublished - 2019
MoE publication typeA4 Article in a conference publication
EventInternational Conference on Intelligent Decision Technologies - International Conference on Intelligent Decision Technologies
Duration: 1 Jan 2019 → …

Conference

ConferenceInternational Conference on Intelligent Decision Technologies
Period01/01/19 → …

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