Price War vs. Technological Breakthrough: What Does AI Mean for Small and Medium-Sized Banks?
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In the current complex and ever-changing economic environment and fierce industry competition, small and medium-sized banks are facing unprecedented pressures and challenges—
Narrowing interest margin, increasing difficulty in risk control, increasingly diversified and digital customer demands, and the traditional operating model can no longer adapt to the rapidly changing market needs.
Since 2025, the average net interest margin of corporate and retail loans among listed banks has been 1.43%, already lower than the industry-wide non-performing loan rate of 1.51%; meanwhile, the Matthew effect in the industry is intensifying—18 state-owned banks, with only 0.38% of the total number of institutions in China, account for nearly 73% of total industry net profits.
The large banks sinking into local regions amid cyclical difficulties have brought new predicaments for small and medium-sized banks:
Should they engage in price wars directly, or take alternative paths and seek differentiated positioning? If pursuing differentiation, should they use “partnership” as an anchor, and what path should they follow?
Against this backdrop, technological empowerment is increasingly emphasized, and investment in technology has transitioned from a “nice-to-have” to a core breakthrough vital for survival and development.
At the “Future Banking Conference 2025,” a number of small and medium-sized banks, including local Sichuan banks, are actively demonstrating that with the deep application of AI technology in areas such as credit risk control and customer service, regional banks now have the possibility to escape the homogenized competition of “interest rate battles” and “scale expansion,” and to explore differentiated development paths.
Wang Xiaolong, Deputy Director of the Economic Committee of the Zhejiang Provincial Political Consultative Conference and former Chairman of Zhejiang Rural Commercial Bank, pointed out at the conference that small and medium-sized banks still face triple challenges—structural, staged, and technical—from a macro perspective, and suggested that these banks should be regionally focused, building competitive barriers through “differentiated positioning + ecological co-construction.”
Lü Wenyong, Co-founder and Executive President of New Hope Financial Technology, emphasized the importance of technology in cyclical times, noting that after the disappearance of the demographic, monetary, and economic dividends, technological dividends have become the only breakthrough for banks to survive market cycles.
In Lü Wenyong’s view, regional commercial banks do not need to obsess over price wars or chase interest rates when confronting large banks head-on; more important are the accessibility and convenience of digital lending products.
“The strength and advantage of regional banks lies in their flexibility—they can quickly steer, design various scenario-based projects flexibly, and use differentiated, multi-dimensional marketing methods to compete with the standardized products of large commercial banks,” Lü Wenyong said.
XU Zhihua, CEO of New Hope Financial Technology, shared common misconceptions about current retail lending from the perspective of functional deduction and mathematical modeling.
XU pointed out that risk release in retail lending is intrinsically “non-uniform,” characterized by the following: among assets distributed under a single-model dimension, approved clients show left-skewness, bad debts progress linearly from low to high scores, and there is a stable and monotonously decreasing relationship between the final bad debt rate over the entire lifecycle of the approved client group and the model score.
The final mathematical result deduced shows that, over time, the cumulative bad-debt rate will exhibit the following characteristics: "slow accumulation of risk in the early stage, followed by a rapid climb, and finally settling into stability."
“Risk change naturally has a phase of rapid growth,” Xu Zhihua pointed out. “Historically, many banks, upon seeing monthly risk indicators rise continuously at this stage, have hurriedly slammed on the brakes and suspended business, ultimately missing out on development opportunities. This is in fact an objective pattern, not a problem with risk management ability.”
In facing today’s banking sector cyclical difficulties, New Hope Financial Technology’s approach is to integrate data, risk control, operations, systems, and practical consulting into a full-process resource to provide banks with an “end-to-end delivery” solution that is “quickly implementable in the short term, risk-free for trial and error, and productive.”
The value of technology lies not only in improving efficiency, but also in helping small and medium-sized banks deeply understand and follow the objective laws of risk evolution, avoiding misjudgment and missing opportunities amid cyclical fluctuations.
By leveraging AI-related one-stop solutions, regional banks can rapidly acquire market-tested digital capabilities, transforming their flexibility (“small boats turn quickly”) into unique competitive advantages in building localized ecosystems and scenario-based projects.
The road ahead is tough, but the direction is clear. Today, breaking through with technology is no longer just a forward-looking discussion, but the inevitable choice for small and medium-sized banks to survive amidst current stock competition and achieve a new round of growth.
Those who can first turn technological dividends into tangible productivity and competitiveness may well accumulate greater potential in the future banking landscape.
Risk Disclosure and DisclaimerThe market has risks, investment requires caution. This article does not constitute personal investment advice, nor does it take into account the specific investment objectives, financial situation, or needs of individual users. Users should consider whether any opinions, views, or conclusions in this article fit their own situation. Investments based on this are at your own risk. ```