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

Financial Innovation

Marko Dávid Vateha¹  Petra Vašaničová²  Štefan Lyócsa²  Branka Hadji Misheva³ 

[1] Department of Banking and International Finance, Faculty of National Economy, University of Economics in Bratislava;Faculty of Management and Business, University of Prešov;ZHAW School of Engineering;

关键词: Profit scoring;    Credit scoring;    Financial intermediation;    P2P;    Fintech;   

DOI  :  10.1186/s40854-022-00338-5

来源: DOAJ

【 摘 要 】

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.

【 授权许可】

Unknown