MYbank (网商银行), 2015

the problem

Street-stall and small-shop merchants are exactly the borrowers a bank most needs collateral, audited financial statements and credit history from to underwrite a loan safely — and exactly the borrowers who structurally cannot produce any of it, locking an entire tier of otherwise creditworthy small business out of formal lending

background

Traditional bank underwriting requires documentation — audited books, collateral, a credit history — that verifies a borrower's ability to repay without the bank having to watch the business operate directly. Street vendors, small shop owners and micro-merchants running cash-and-QR-code businesses have none of this: no formal accounting, nothing to pledge as collateral, and often no prior borrowing history at all, which is precisely why traditional banks treat them as unbankable regardless of how healthy their actual cash flow is. A human loan officer manually underwriting a small loan this size also costs the bank roughly the same fixed cost as underwriting a much larger loan, at roughly ¥2,000 in labor per loan — making tiny loans structurally unprofitable to process by hand no matter how creditworthy the applicant.

MYbank, an online bank founded within Alibaba's Ant Financial ecosystem, built its '310' lending model around a different evidence source entirely: the transaction data already flowing through a merchant's payment QR code every time a customer paid them. Instead of asking for documents these merchants could never produce, MYbank read their actual cash-flow history directly from the payments infrastructure they already used daily.

the move

The '310' model — 3 minutes to apply, 1 second to approve and disburse, 0 human loan officers in the loop — runs loan decisions through an automated system built on more than 100,000 data indicators, over 100 predictive models and more than 3,000 risk-control strategies, replacing manual document review entirely with algorithmic analysis of transaction-data patterns the bank could already observe.

the payoff

The automated model cut average per-loan operating cost from roughly ¥2,000 under manual underwriting to approximately ¥2.30, while serving more than 40 million small merchants cumulatively, with an average loan size of ¥36,000, average loan duration under 120 days, and over 80% of borrowers receiving their first-ever formal bank business loan; the bank has maintained a 30-day non-performing loan rate around 1–1.5%, comparable to or better than conventional small-business lending despite serving borrowers traditional banks had excluded entirely.

what came after

MYbank's '310' model is widely studied in Chinese fintech and inclusive-finance literature as a template for algorithmic microlending built on transactional data rather than traditional collateral and documentation, and the bank has since licensed the underlying risk model to partner financial institutions under its 'Fanxing' (凡星) program specifically to extend the same underwriting approach to small merchants outside its own direct customer base.

references

[1]界面新闻 (Jiemian) — 网商银行发布'凡星计划'：开放'310'能力，服务3千万小商家Jiemian News, 2018jiemian.com
[2]中证网 (China Securities Journal) — 网商银行：科技让金融更好服务小微企业China Securities Journal, 2019cs.com.cn

A bank stopped asking small merchants for paperwork they could never produce and read their QR code trail instead