Big data and automated credit scoring in rural finance: the case of MYBank



According to China’s State Administration for Market Regulation, as of 2017 there were 73 million small and medium-sized enterprises (SMEs) in China. Only 14 percent of these, though, had access to a loan or line of credit. These low levels of financial access can be explained by the traditional set of constraints affecting SMEs (especially in rural areas), such as lack of conventional collateral, high costs for obtaining loans, insufficient loan sizes, and complex application processes.

Published: 19 November 2020
READING TIME: 4 minutes
Author: Niclas Benni

The experience of  MYBank, a fully digital bank that was created in 2015 by Ant Financial[1], shows how the rising levels of digital penetration in China’s rural areas, the leveraging of “big data”, and the automation of the credit approval and provision processes, have made it possible to overcome several of the traditional barriers to financing rural enterprises, including customers’ fragmentation, scarce collateral, and a lack of granular knowledge on customers’ financial behavior and creditworthiness, MYBank’s experience has showcased a new, groundbreaking approach towards digital financial services provision for small enterprises in rural areas, which has shown enormous potential -as well as its own unique set of risks and challenges.

As a completely digital bank, MYBank resides entirely on the cloud and does not manage any physical branches, offering its services only online and via mobile.  The key to its strategy to manage credit risk is its  ability to track and analyse a vast amount of data about its rural SME clients -and all the other actors that these clients interacts with- that is generated by the ecosystem of different digital services that belong to ANT Financial and the Alibaba Group.

How does this work? Those small business owners that are clients of MYBank make use of a combination of several of different e-services through their phones and computers, as part of their daily activities: for example, they use AliPay to transfer their funds and store them in a mobile wallet, as well as the online market platform Taobao to sell their products. The triangulation of the data generated on their financial behavior –and trustworthiness with their money- allows MYBank to make very precise and insightful predictions on their capability to repay MYBank’s loans, by employing proprietary AI and risk management technologies.

MYBank uses an automatized, AI-powered credit scoring system (the “Zhima credit evaluation system”) to analyze this massive amount of information (i.e. big data) it has on every loan applicant, to screen for creditworthy clients. Furthermore, the use of big data –and the very precise client evualation process it enables- allows MYBank to eschew the need to ask for conventional collateral to its clients, thus lowering the threshold for loan disbursement and helping to provide credit to rural clients who previously had no chance of receiving it.

Rural SMEs can submit a loan application to MYBank entirely online, with average loans provided of US$ 4400. In terms of the timing for loan approval, MYBank follows the “3-1-0 model”: 3 minutes to apply from a mobile phone, 1 second to approve, and 0 seconds of human intervention.  Although loan purposes can be quite varied, MYBank mainly provides credit to satisfy working capital and short-term investment needs for agricultural activities.

Since mid-2015, MYBank has provided loans to more than 15 million SMEs for business loans of over US$ 290 billion, with competitive interest rates -ranging from 6 to 16%- that are substantially lower than those offered by brick-and-mortar branches (20 to 40%). Furthermore, the non-performing loan ratio of MYBank’s lending to small businesses has been considerably low –around 1 percent- which is a testament to the effectiveness of the bank’s screening system. The kind of unsecured lending that MYBank provides to small rural enterprises can also be very profitable, considering the higher amount of risk involved: the bank’s net interest margin is 3 to 5 percent, which is considerably higher than those of China’s biggest commercial banks.

MYBank’s approach to rural lending also carries its own sets of challenges and risk. The first, and most important, has to do with data privacy. MYBank’s model is effective because it is able to leverage massive amounts of data on a wide variety of aspects of the loan applicant’s professional and personal life. The bank’s structure, completely “on the cloud”, also implies some constraints. Given that it does not have any physical branches to accept its clients’ deposits, MYBank has to rely on borrowed funds from other lenders on the interbank market, which are substantially more expensive compared to normal deposits. In fact, 60 percent of the MYBank’s total liabilities are due to interbank funding.

Although MYBank’s model is hardly replicable at the moment in the majority of emerging contexts around the world, given the wide combination of enabling aspects that allow its strategy to be successful (e.g. high levels of digital penetration, a constellation of e-services all belonging to the same group, still evolving regulation), it is interesting to analyze this case as an example of what the future could hold in terms of innovative solutions to overcome the traditional financing gap affecting small enterprises in rural areas -provided that adequate regulatory, political and financial oversight is developed around these new, groundbreaking models for financial

[1] Ant Financial is the world’s largest fintech company, affiliated to the AliBaba Group of e-services. It provides to its client base of 870 million people a wide host of digital financial services, which include online lending, e-insurance, mobile wallets, fund management, financial risk management, infrastructure-as-a-service (IaaS), payment processing, and several others.  It is the highest valued fintech company in the world, as well as the world’s most valuable unicorn start-up,  with a valuation of US$150 billion as of mid-2018. It manages Alipay, the world’s largest mobile and online payments platform, as well as Yu’e Bao, the world’s largest money-market fund.