W37 - On Adjusting the Judicially Protected Cap for Private Loan Interest Rates
On August 20, the Supreme People’s Court released a newly revised “Provisions of the Supreme People’s Court on Several Issues Concerning the Application of Law in the Trial of Private Lending Cases,” lowering the judicial protection cap for private lending interest rates to 15.4%, a substantial drop from the previous 24% and 36%. The prior “two-line, three-zone” thresholds of annual rates at 24% and 36% are now officially history.
I recently noted an industry development about adjusting the judicial protection ceiling for private lending rates. Considering Jinfu’s business, I reflected on the opportunities and challenges this brings us.
Basic information about lending products:
Revenue: Fintech companies currently engaged in lending generally follow two business models
One model is to leverage their own data and models as a technology service provider, offering anti-fraud, credit assessment, and risk pricing services. It is purely B2B, and revenue comes from technology service fees.
The other model builds on those technical capabilities and partners with banks or other financial institutions for funding. The company develops and operates lending products itself and participates in customer acquisition and post-loan processes. Within this there are two variants: assisted lending (bank provides funds) and joint lending (bank and fintech jointly provide funds).
Most leading companies adopt the second model; the advantage is the ability to earn scalable returns from lending, but deep involvement in lending inevitably attracts regulatory pressure.
Cost composition: funding cost (10%–14%) + bad debts (2%–5%) + customer acquisition, R&D, and operating costs, plus credit checks, payment channel fees, and collection costs (5%) => Industry average annualized rate above 17%
Interest level for business loans. Having experienced loan payment products, fromFrom current business loan pricing, the standard rate is a daily interest of 0.05% (0.0005 per day), equivalent to an annualized rate of 18%.The agreement lists the lender as Chongqing Meituan Sankuai Microloan, which appears to be our own funds and does not involve other fund providers like banks, though it is an assisted or joint lending arrangement.
Impact of adjusting the lending rate cap on the industry:Using changes in judicial protection to force market participants to lower private lending rates,Leading fintech companies will operate with thin margins, most fintechs will incur losses and be forced to exit the market in large numbers.
Challenges:Like other competitors in the industry, this compresses our relative profit margins, making it harder to generate returns.
Opportunities:Industry reshuffling will speed the elimination of weaker players and create intense competition among the strongest. Under compliant conditions,the breakthrough is to leverage advantages in data, technology, and scenarios to pursue activities with decreasing marginal costs; the absolute profits generated by scale still have significant potential.In fact, Ant Microloan’s breakthrough lies in serving small and micro merchants in the retail sector. Traditional financial institutions, such as banks, lack the capacity to penetrate down to broad user bases. For lower-income and non-institutional groups, they lack multidimensional data and advanced models for credit assessment. Joint-stock banks like China Merchants Bank have pushed credit card products to expand customer reach, but after covering the white-collar segment, it’s difficult for them to achieve much wider coverage.Their approach converges with ours; the primary and most important step is to build a sufficiently large account ecosystem. From experience, the users we should serve are small and micro merchants in the catering industry.
Strategy:The first model has limited revenue; continue to deepen the second model,focus on the small and micro customers within our advantageous scenarios, continue expanding the account ecosystem, strengthen intelligent analysis of multidimensional data, reduce bad debt rates, and attract lower-cost funding.
Last updated