China, credit and seeing unforseen risk

Not all risks are obvious. Some genuinely cannot be foreseen but others are missed because of outdated information, the wrong source of data, poor judgement or inconsistent processes.

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In the financial industry, creditworthiness is the decisive factor which differentiates between good and bad borrowers within the lending business. Credit assessment plays a central role in underwriting loans, aiming to identify potential risks of default.

" Like many things, the internet and social media has changed the [Chinese personal-loan] game."
Greg Au-Yeung, Head of Technology China, ANZ

On these broad terms, China is little different to the developed world. The basic components of credit analysis are the same, the ‘Five Cs’: Capacity to repay the loan; Capital for the individual/corporation; Collateral of the borrower as guarantees in case of default; Conditions that describe the loan purpose; Character of the individual.

The digital world is changing the nature of credit assessment and in China this is happening particularly rapidly, with particularly Chinese characteristics – and plenty of implications for the rest of the world given the massive growth in Chinese e-commerce and financial technology (fintech).


Historically, bankers made credit decisions based on industry analysis and firsthand knowledge of the local economy and would-be borrower. But like many things, the internet and social media has changed the game. More analysis is available but customers want decisions more quickly.

Facebook, for example, has technology that allows lenders to assess borrower’s creditworthiness by checking their friends’ credit scores. Kreditech, a German fintech start-up offers credit and banking products to people with little or no credit history, already analyses keyboard strokes and the browsing history of borrowers applying for loans to determine the prospect’s personality and identity. 

Another fintech start-up, Hong Kong-based Lenddo, targets the underbanked middle-class borrowers and small-business owners with a proprietary algorithm using hundreds of data points collected from social media sites to assess the likelihood of a borrower repaying a loan.

And it’s not just banks. According to the Harvard Business Review, “creative retailers are using the new technologies to innovate just about everything stores do from managing inventory, to marketing, to getting paid.”

The online retail revolution has fostered a marriage of traditional commerce and technology.


In China, many industries, including the banking sector, are highly regulated with strict capital requirements, foreign ownership ceilings and other rules and regulations.

However, the government adopts a more liberal approach towards the technology industry, providing an unparalleled opportunity for hi-tech firms to thrive, especially with e-commerce and internet companies including Baidu, Alibaba, and Tecent. 

About the same time Zopa, the world’s first online peer-to-peer (P2P) lending service was launched in 2006, Ning Tang brought P2P to China, and established CreditEase.   Although CreditEase was initially an offline P2P company relying on physical branches and a sales force to expand, the concept has triggered an evolution in the shadow banking industry. 

Technology start-ups were formed to enter the Chinese online P2P marketplace and compete with non-bank operators already in the lending business.

After 10 years of rapid growth, CreditEase’s loan book today is estimated over $US7.5 billion and employs 25,000 employees.  According to Crowdfund Insider, China’s 2015 P2P market size is $US150 billion, the world’s largest, and roughly four times the US market.

According to the credit ratings agency Moody’s, China’s shadow banking industry has increased by 53 per cent in 2015 and reached RMB 53 trillion ($US7.9 trillion), which equivalents to 79 per cent of the country’s GDP.

Although it’s loosely defined, the shadow-banking industry in general constitute of non-bank operators including trust, microcredit, guaranteed, P2P, and in some cases, underground personal lending market.

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Outside the banking sector in China, technology companies have been busy building their own financial eco systems.  Unlike developed countries, China has the luxury of starting from scratch.  One key advantage for internet companies like Alibaba, Tencent, and Baidu is their user base - almost anything can be sold to these customers. 

Sesame Credit*, a social credit scoring system under Ant Financial Services Group, an affiliate of Alibaba, provides a credit score based on a customer’s transaction data via Alipay (online payment platform and part of Ant) and information gathered through Alibaba.

The data may include spending patterns (retailer) and business transaction activities (merchant) and individual records from government agencies.

Artificial intelligence and machine learning via big data is being deployed to assess a creditor’s willingness to repay versus default risk. Although still under the research stage, Sesame Credit is exploring advance algorithms such as decision tree, random forest, support vector machine (SVN), and neural networks.


The leading US credit decision platform, Zestfinance, uses third party data from vendors (credit information, home moving data, legal record), borrower supplied information (phone and utility bills), and internet data (IP address, online behaviour and social media data).

Unlike conventional credit assessment techniques which use 20 to 50 variables, Zestfinance applies 70,000 variables from the internet.  

In China,, is a start-up that specialise in truck logistics but has a financial service arm that lends money to truck drivers. The prerequisite for the loan approval is to install a device in the truck that collects data (driving behaviour that determines if the he is a good driver that could differentiate good and bad borrower).

The urge to use social media data is similar between western companies and the mainland counterparts.  While foreign financial institutions expand into unbanked populations, China’s creditors see an opportunity in individuals’ with incomplete credit histories.


Regardless of different models, social media data is yet to be heavily utilised by lenders as a source of data for mainstream credit assessment because of a lack of predictability.  Nevertheless, social media data is having an impact and can provide convenience to consumers.

Chinese travellers now need only provide the Sesame Credit report during visa application for Singapore and Luxemburg. Social payment however provides an opportunity for non-banks to move customers outside the mainstream banking ecosystem.

China’s P2P industry has already grown into the world’s largest; new technology has created sophisticated machine learning and complex predictive analysis.

The financial institutions that embrace these social, market and technology changes are the ones that will survive the digital age. 

With the increasing focus of individual’s social media and internet activities, lenders may ultimately master a way that links the right behaviour with good borrowers. 

*Sesame Credit has no relation to Credit Sesame, which is a US-based credit and loan management platform.

Greg Au-Yeung is Head of Technology China at ANZ

The views and opinions expressed in this communication are those of the author and may not necessarily state or reflect those of ANZ.

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