EconPapers    
Economics at your fingertips  
 

Default or profit scoring credit systems? Evidence from European and US peer-to-peer lending markets

Štefan Lyócsa, Petra Vašaničová, Branka Hadji Misheva and Marko Dávid Vateha
Additional contact information
Petra Vašaničová: University of Prešov
Branka Hadji Misheva: ZHAW School of Engineering
Marko Dávid Vateha: University of Economics in Bratislava

Financial Innovation, 2022, vol. 8, issue 1, 1-21

Abstract: Abstract For the emerging peer-to-peer (P2P) lending markets to survive, they need to employ credit-risk management practices such that an investor base is profitable in the long run. Traditionally, credit-risk management relies on credit scoring that predicts loans’ probability of default. In this paper, we use a profit scoring approach that is based on modeling the annualized adjusted internal rate of returns of loans. To validate our profit scoring models with traditional credit scoring models, we use data from a European P2P lending market, Bondora, and also a random sample of loans from the Lending Club P2P lending market. We compare the out-of-sample accuracy and profitability of the credit and profit scoring models within several classes of statistical and machine learning models including the following: logistic and linear regression, lasso, ridge, elastic net, random forest, and neural networks. We found that our approach outperforms standard credit scoring models for Lending Club and Bondora loans. More specifically, as opposed to credit scoring models, returns across all loans are 24.0% (Bondora) and 15.5% (Lending Club) higher, whereas accuracy is 6.7% (Bondora) and 3.1% (Lending Club) higher for the proposed profit scoring models. Moreover, our results are not driven by manual selection as profit scoring models suggest investing in more loans. Finally, even if we consider data sampling bias, we found that the set of superior models consists almost exclusively of profit scoring models. Thus, our results contribute to the literature by suggesting a paradigm shift in modeling credit-risk in the P2P market to prefer profit as opposed to credit-risk scoring models.

Keywords: Profit scoring; Credit scoring; Financial intermediation; P2P; Fintech (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

Downloads: (external link)
http://link.springer.com/10.1186/s40854-022-00338-5 Abstract (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:fininn:v:8:y:2022:i:1:d:10.1186_s40854-022-00338-5

Ordering information: This journal article can be ordered from
http://www.springer. ... nomics/journal/40589

DOI: 10.1186/s40854-022-00338-5

Access Statistics for this article

Financial Innovation is currently edited by J. Leon Zhao and Zongyi

More articles in Financial Innovation from Springer, Southwestern University of Finance and Economics
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().

 
Page updated 2025-03-20
Handle: RePEc:spr:fininn:v:8:y:2022:i:1:d:10.1186_s40854-022-00338-5