The continued growth of China’s auto sales has relied increasingly on consumer credit, according to the WSJ; but, granular data is hard to come by. So, we created a process to collect, clean, and structure data from online auto loan offerings. Our findings imply that the auto loan market, like many credit markets in China, runs on two parallel tracks, and is woefully inefficient.
The complete data set includes auto loan offers from 71 lenders across 278 cities. The sample covers micro lenders, such as Credit Ease and Hexindai, as well as state-owned mega-banks like Bank of China and the Agricultural Bank of China. The collected data maps total interest payments on 12-month, 100,000 yuan loans to credit requirements like collateral, job status, and monthly wages.
The results show a bimodal distribution of total interest payments between official bank lending and the shadow banking sector. For example, Bank of China’s “Personal Consumption Credit Loan” requires a total interest payment of only 2,700 yuan. Meanwhile, the median for non-bank lenders was an extortionary 22,600 yuan.
Our initial hypothesis was that shadow lenders, free from banking sector regulations, would set auto loan rates via the market mechanism, further study of which would illuminate how credit is priced in China. That was wrong.
The eye-test reveals no obvious connection between total interest payments and the credit requirements posted in loan offerings. Further, we found no evidence in correlation or multiple regression tests that borrower monthly wages, employment status, home value, collateral, days to process, or location offer explanatory power for variations in total interest payments.
We must conclude that either the listed loan requirements are only decorative, or that China’s auto lending market is highly inefficient – which suggests an opportunity for investors.
Contact us for the complete auto-lending data set.