Pricing strategies in BigTech lending: Evidence from China

IF 2.9 3区 经济学 Q2 BUSINESS, FINANCE Financial Management Pub Date : 2023-01-24 DOI:10.1111/fima.12416
Lei Lu, Jianxing Wei, Weixing Wu, Yi Zhou
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引用次数: 1

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.

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大科技贷款的定价策略:来自中国的证据
本文利用中国消费者贷款的专有数据集,分析了一家大型科技银行在企业对客户无抵押贷款市场的定价策略。我们发现,大科技银行构建的信用评级可以反映客户的违约风险。而且,随着信用等级的提高,利率降低,信用额度增加。有趣的是,BigTech银行根据客户渠道向客户收取不同的利率,尽管它没有提供有关客户违约风险的信息。随着《中国银行业监督管理委员会法》(China Banking Regulatory Commission Act)的通过,信贷市场竞争减少,这家大型科技银行提高了目前的利率,并降低了信贷额度。我们用一个简单的信用契约设计模型来合理化这些实证发现。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Financial Management
Financial Management BUSINESS, FINANCE-
CiteScore
6.00
自引率
0.00%
发文量
27
期刊介绍: Financial Management (FM) serves both academics and practitioners concerned with the financial management of nonfinancial businesses, financial institutions, and public or private not-for-profit organizations.
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