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Pricing strategies in BigTech lending: Evidence from China

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  • Lei Lu
  • Jianxing Wei
  • Weixing Wu
  • Yi Zhou

Abstract

This paper analyzes a BigTech lender's pricing strategies in the business‐to‐customer unsecured loan market using a proprietary data set of consumer loans in China. We find that the credit rating constructed by the BigTech lender is informative of the customers' default risk. Moreover, the interest rate decreases and the credit limit increases with the credit rating. Interestingly, the BigTech lender charges different interest rates to its customers based on the customer channel, although it does not provide information about the customers' default risk. Following the passage of the China Banking Regulatory Commission Act, which reduced credit market competition, the BigTech lender increased the current rate and decreased the credit limit. We rationalize these empirical findings in a simple model of credit contract design.

Suggested Citation

  • Lei Lu & Jianxing Wei & Weixing Wu & Yi Zhou, 2023. "Pricing strategies in BigTech lending: Evidence from China," Financial Management, Financial Management Association International, vol. 52(2), pages 333-374, June.
    • Handle: RePEc:bla:finmgt:v:52:y:2023:i:2:p:333-374
    DOI: 10.1111/fima.12416
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    1. Dong, Yingwei & Gou, Qin & Qiu, Han, 2023. "Big tech credit score and default risk ——Evidence from loan-level data of a representative microfinance company in China," China Economic Review, Elsevier, vol. 81(C).

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