Determinants of Loan Funding Success and Default for a Chinese Microfinance Portfolio

There is extant research on microfinance lending in the Chinese informal financial market focused on data obtained from online lending platforms and microfinance loans within the rural community. However, there is less research output regarding Chinese offline informal lending featuring underbanked borrowers from a wealthier community. Using a unique dataset obtained from a microfinance lending institution in China, we explore the characteristics of loan applicants and investigate the determinants of loan funding success and default in this market. We find that these borrowers are older and less-educated, but are more wealthy than online borrowers. Based on univariate and multivariate analysis, our findings provide evidence of the existence of demographic discrimination in terms of gender, age, and education level in the Chinese offline informal lending market. Furthermore, we find that the main determinants of loan funding success do not show statistically significant association with default, indicating that lenders introduce bias in their lending decisions. In particular, credit score, which significantly affects funding success is only associated with default univariately. In other words, when other variables are included in the model, the information in those variables are sufficient to model default, so that including credit score additionally in the model is unnecessary.