Network based credit risk models
- Quality Engineering
- April 2020
- Volume 32 Issue 2
- pp. 199-211
- Giudici, Paolo, Hadji-Misheva, Branka, Spelta, Alessandro
The copyright of this article is not held by ASQ.
Peer-to-Peer lending platforms may lead to cost reduction, and to an improved user experience. These improvements may come at the price of inaccurate credit risk measurements, which can hamper lenders and endanger the stability of a financial system. In the article, we propose how to improve credit risk accuracy of peer to peer platforms and, specifically, of those who lend to small and medium enterprises. To achieve this goal, we propose to augment traditional credit scoring methods with “alternative data” that consist of centrality measures derived from similarity networks among borrowers, deduced from their financial ratios. Our empirical findings suggest that the proposed approach improves predictive accuracy as well as model explainability.