HUANG YipingPeking University

Financial Statement Series, Peterson Institute of International EconomicsNovember 24, 2020

Bigtech Credit in China

First Seller: CUI WeipingYokohoma, Japan

First buyer: JIAO ZhenzhongXi’an, China

First customer officer: LIANG BinHangzhou, China

The second-hand Fujifilm Camera

On October 18, 2003, Jiao paid RMB750 to Alipay to buy the second-hand camera from Cui, intermediated by Liang, on Alibaba’s online shopping platform Taobao.

How did Alipay start?Paypal was created in December 1998, and Alipay came online in December 2004. Why did Alibaba need Alipay?

Rapid development

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Alipay WeChat

Active users of Alipay and WeChat pay (million)

Convergence of digital financial inclusion

‡ Peking University Digital Financial Inclusion IndexRed, orange, yellow and green represent, from most to least developed, levels of digital financial inclusion development in relevant municipality.

The Hu HuanyongLine

China leads in some digital financial businesses, especially mobile payment, Big tech credit, online investment, digital insurance and central bank digital currency. And regional gaps narrowed rapidly between 2011 and 2018.

China is the largest Bigtech lender

Fintech lending volumes are diverging1 Big tech credit is booming in Asia, the US and Africa2 Index, Q1 2017 = 100 USD mn, logarithmic scale

CN = China, JP = Japan, KR = Korea, US = United States, KE = Kenya, ID = Indonesia. 1 Data are based on five platforms for Australia and New Zealand, all platforms covered by WDZJ.com for China, 49 platforms for Europe, 34 for the United Kingdom and five for the United States. Volumes are reported in local currency. 2 Figures include estimates.

Source: Cornelli et al (2020), “Fintech and big tech credit: a new database”, BIS WP 887.

Distinction between Fintech lending (P2Ps) and Big tech credit (MYbank, WEBank)

Bigtech credit in China

• Bigtech credit refers to loans extended to SMEs and individuals by Bigtech companies, taking advantage of Bigtech platforms and big data credit risk assessment

• Speed: Alibaba’s micro finance created the “3-1-0” lending model in 2010: it takes no more than 3 minutes to fill online loan application; if approved, the fund is in the account within 1 second; and there is 0 human intervention

• Contact-free: Bigtech credit continued during COVID-19

• Quantity: Each of the three virtual banks, WeBank, MYbank and XWBank, with 1000-2000 employees, can now grant around 10 million loans annually

• Quality: Non-performing loan ratiobefore COVID-19MYbank: 1.6%Banks’ SME loans: 3.2%SME loans (<5 m): 5.5%

MYbank’s NPL ratio (%) in 2020

1.57 1.66 1.72 1.742.01 2.05 2.02 1.98

1.73

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A new credit risk management framework

Customer acquisition Risk identification Repayment management

Predicting ability and willingness to repay loans

Fintech credit risk assessment models

Machine learning models

Central bank credit registry information

Credit history

Digital footprint

Repayment records

Real-time monitoringLong-tail customers

Adverse selection problem Moral hazard problem

Punishing default

BigTech Platform

Big Data

Big data credit risk assessment

Horizontal axis: proportion of normal loans falsely predicted as default loans; vertical axis: proportion of correctly identified default loansSample size: 771594 (training set), 1053748 (test set)

Var12 Var3 Var123 Var1234 Var5 Var12345

ScorecardModel

0.70 0.58 0.72 0.72 0.69 0.76

Machinelearningmodel

0.67 0.54 0.76 0.80 0.76 0.84

Area Under The Curve (AUCs)

Variable groups: (1) Asset and financial information(2) Credit history (information of defaults)(3) Vendor-specific information(4) Local economy information (for provinces and cities)(5) Proprietary information on borrower behavior

Receiving Operating Characteristic (ROC) Curves

Traditional model (A): traditional variables + scorecard model→ Big data model (D): big data information + machine learning model(A) → (B): information advantage; (A) → (C): model advantage

Significance level: ** p<0.05; *** p<0.01.

Macroeconomic implications

• Bernanke, Gertler and Gilchrist (1999) once coined the term “financial accelerator”

• Bigtech credit relying on data instead of collaterals weakens financial accelerator mechanism

• But would this give rise to a new “cash flow accelerator”?

0.055

0.581***

0.209***

0.041** 0.018

0.147***

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Big tech credit Secured bank credit Unsecured bank credit

Elasticity with respect to House PriceElasticity with respect to GDP

Bernanke, Ben S. & Gertler, Mark & Gilchrist, Simon, 1999. "The financial accelerator in a quantitative business cycle framework," Handbook of Macroeconomics, in J. B. Taylor & M. Woodford (ed.), Handbook of Macroeconomics, edition 1, volume 1, chapter 21, pages 1341-1393, Elsevier.

Bigtech credit survived COVID-19?

1.57 1.66 1.72 1.74

2.01 2.05 2.02 1.981.73

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Mybank’s proportion of overdue loans, 2020 (%)

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