Bank explores OPC Finance: Why are some rushing to get ahead while others "let the bullets fly"?

Ask AI · How Can Banks Balance Innovation and Risk in the OPC Finance Boom?

Reporter: (21st Century Business Herald) @E1@ @E2@

A person, a computer, and a set of AI tools can support an entire company.

In spring 2026, as AI agents such as OpenClaw burst into popularity, the startup model known as OPC (One Person Company) is moving from concept to reality. In places such as Longgang in Shenzhen, Suzhou, and Yuhang in Hangzhou, supportive policies have been rolled out in clusters. A wave of startups driven by “individuals + AI” is quietly taking shape.

Financial institutions with sharp instincts have smelled the opportunity. Mid-sized banks such as Jiangsu Bank, Nanjing Bank, and Changshu Rural Commercial Bank have been among the first to enter the space, launching exclusive financial products such as “OPC Suzhi Chuang,” “OPC Tongxin Plan,” and “OPC Chuangyi Loan.”

Up to RMB 5 million in credit limits, with funds arriving in as fast as 6 hours—these kinds of financial services that used to be available only to established enterprises are now opening the door to “one-person companies.”

But on the other side of the boom, some banks are choosing to wait and watch.

A technology-finance负责人 at a city commercial bank said bluntly that a one-person company is only one form. If a bank’s current financial product system can meet the needs of these businesses, there is no need to set up a separate product category.

A person from a city commercial bank in East China believes that, in essence, OPC finance is a niche inclusive finance business. The market size may not be large. In addition, OPC’s own operations involve significant uncertainty, and regulators’ stance has not yet been clearly defined. Before product innovation, banks can “let the bullets fly for a while.”

On one side, some mid-sized banks are racing to get in. On the other, more banks are standing still. In this round of financial exploration around OPC, different institutions have given radically different answers—some view it as grabbing strategic ground for the future, while others see it as a whirlwind that will blow over quickly.

“From applying to determine the credit amount, to approval, to the RMB 2 million funds arriving—it only took 6 hours.” Mr. Wang, founder of Suzhou Dufeng Technology, did not expect that a company with no fixed assets—only a core R&D team and digital platform orders—could get a bank loan this fast.

This is the first real-world case of Jiangsu Bank’s Suzhou branch’s专项贷款 under “OPC Suzhi Chuang.” The core logic of the bank’s OPC financial service solution is a shift from “making a loan” to “serving a company”—integrating eight major functions, including account management, payment and settlement, VAT/invoice/tax services, and financing support, to form an end-to-end support system of “opening an account is equivalent to receiving service, operations generate data, and turnover becomes credit.”

Nanjing Bank launched the “OPC Tongxin Plan,” with the first deal implemented in the “Quality & Energy · Workshop” OPC community in Yuhuatai District, Nanjing. The plan focuses on two core elements—“human resources + computing power.” Relying on a product matrix including “computing-power loans” and “Xin Talent,” it aims to unblock financing bottlenecks during the OPC growth process through “integrated investment-and-lending + ecosystem empowerment.”

Changshu Rural Commercial Bank conducted industrial research around OPC, focusing on three tracks: “AI + industrial manufacturing,” “AI + e-commerce new retail,” and “AI + professional services.” It rolled out an exclusive product called “Chuangyi Loan” for OPC, with a maximum credit approval of RMB 5 million. It enables loan disbursement in as fast as the same day, and also provides dedicated preferential interest rates, with key tilts toward groups such as highly educated entrepreneurial talent.

According to incomplete statistics, more than 10 banks and their branches—including Industrial and Commercial Bank of China, Bank of Communications, SPDB, and Bank of Qingdao—have recently rolled out OPC-dedicated financial products and comprehensive service solutions in sequence. Even county-level financial institutions such as Shuyang Rural Commercial Bank and Yuhang Rural Commercial Bank have joined the fray. Shuyang Rural Commercial Bank issued the first county-wide RMB 200k OPC loan to an entrepreneurship main entity under “Shuzhi Workshop.” Yuhang Rural Commercial Bank set up a专项授信 pool of RMB 200 million to provide targeted support for “AI + OPC” projects within its jurisdiction.

Regarding the core reason banks are positioning themselves for the OPC market, a relevant business负责人 at Jiangsu Bank told reporters that the OPC market is a blue ocean for banks to find high-quality customers in the future. A one-person company today may become a unicorn tomorrow—early positioning allows banks to cultivate customers early and bind them deeply. On the other hand, OPC has characteristics such as light assets, high-frequency settlement, and end-to-end demand. This helps banks expand into diversified business scenarios such as settlement, tax, wealth management, and ecosystem connections.

Zhong Guowei, General Manager of the Investment Banking Department at Changshu Rural Commercial Bank, said in an interview that the bank views OPC as a small micro entrepreneurship entity in the AI era. It not only innovatively launched “OPC Chuangyi Loan,” but also built a dedicated service platform to meet various needs in OPC enterprises’ operations and management. “On this platform, OPC can find support from multiple angles, such as financing, learning about policies, signing orders, signing contracts, and paying taxes. OPC enterprises can also publish services they can provide, and even Changshu Bank’s 650k customers can publish their needs, enabling precise matching among all parties.”

Zhang Hua, Deputy Director of the Institute of Finance and Research at Zhejiang University, believes that financial institutions that closely follow industry trends and launch targeted financial products are a sign of a high degree of marketization. This shows that they have the capability to precisely capture the latest market needs and respond quickly to changes in industrial development.

But beneath the lively surface, a deeper question emerges: why do banks dare to lend money to OPC companies that have no employees, no property, and whose operating situation may not be stable either?

Under traditional credit-lending logic, OPC is almost “not lendable”—there is no fixed asset collateral, no standardized financial statements, and not even continuous operating cash-flow records.

However, the attitude of some banks is reversing. Jiangsu Bank proposes “operations are equivalent to data, and turnover is equivalent to credit.” It replaces collateral with real-time operating data such as corporate account transaction flows, tax invoices, and digital platform orders. Nanjing Bank focuses on “human resources + computing power,” using the technical background, education, and industry experience of the core R&D team as the basis for credit assessment. Changshu Rural Commercial Bank focuses on “AI + three major tracks,” using industrial research to judge a company’s growth potential in niche areas rather than looking at assets alone.

Behind this reversal is a major change in credit logic. Liu Yong, Director of the Institute of Internet Finance Research at Zhongguancun and Secretary-General of the Zhongguancun Financial Technology Industry Development Alliance, told reporters that OPC’s core feature is “light assets, no collateral.” This forces banks to abandon traditional “collateral-based thinking” and explore a new risk-control model based on “data credit” and “capability credit.”

Liu Yong believes that Jiangsu Bank’s “shifting from making one loan to serving one company” is precisely an attempt to validate a company’s value through engagement across its entire lifecycle using dynamic data. Nanjing Bank’s “computing-power loans” and Changshu Rural Commercial Bank’s “Chuangyi Loan” also demonstrate deep integration between financial products and industrial scenarios. They no longer provide generic funds. Instead, they embed funds into the production factors that OPC needs most (computing power, talent). In his view, this “financing + financing wisdom” innovation model enhances the irreplaceability of financial services.

A person from a city commercial bank that has not yet entered OPC finance told reporters candidly that although the bank remains cautious about risk control for this kind of business, seeing some innovations by peers still feels enlightening. “For example, the bank signs an agreement with a cloud service provider, and the money the customer borrows can only be used to purchase computing-power services from the designated platform. In this model, risk from a risk-control perspective is relatively more controllable. For the platform provider, it can also drive its own business through the bank’s credit products.”

Another close-to-regulatory source told reporters that while banks are actively innovating, they should build a risk-control firewall that matches OPC’s characteristics. This involves changing from “credit grantors” to “governors of the digital ecosystem,” establishing assessment models for entities with light assets, high computing power, and reliance on data assets, and building an embedded, dynamic, end-to-end (penetrating) risk-control system.

At the level of practical implementation, a business负责人 at Jiangsu Bank told reporters that in practice they mainly assess four dimensions of OPC. First, innovation capability—whether they have core technologies, intellectual property rights, or exhibit pattern innovation and scenario application capabilities in a specific sub-sector. Second, growth potential—whether their industry is part of the emerging sectors such as the digital economy, artificial intelligence, or hard tech, and whether they have commercialization orders or equity financing endorsements. Third, subject qualifications—whether the actual controller has industry experience, technical capability, or industry resources, and whether they have a compliant operations system. Fourth, ecosystem fit—whether they can integrate into the regional innovation ecosystem, and whether there is collaboration potential with universities, research institutes, and upstream and downstream players in the industry chain.

This wave of financial innovation around OPC reflects that some banks’ credit-lending logic is undergoing profound changes. They no longer ask, “What collateral do you have?” Instead, they shift to, “Is your technology really valuable, is your data truly authentic, and does your track have a future?”

However, not everyone is cheering this OPC finance boom.

“This is, in essence, a relatively niche inclusive finance business.” A city commercial bank person in East China said directly. In his view, many banks have already built relatively mature inclusive finance service systems, and the existing system can cover more than 90% of customers. Adjusting credit mechanisms separately for a small portion of the OPC customer base may not be worth it from an input-output ratio perspective.

This person further pointed out that although OPC business is dressed in the “one-person company” exterior, in essence it is still inclusive finance—only with one additional entry threshold. If a bank already has a dozen or so mature products that can cover the vast majority of customers’ needs, there is no need to create something new for OPC just to grab attention.

Another city commercial bank person from North China told reporters that a one-person company is only a form, and the products banks provide are also only a form. What customers care about is whether they can get funding, not which product they use. The key for banks’ service is to look at the company’s actual production and operating situation. If one person can legally register a company, the bank provides services based on their business license as an enterprise legal person identity, rather than deliberately checking whether it is “a one-person company.”

The aforementioned East China city commercial bank person also calculated it from a more practical angle: “If a city commercial bank’s inclusive business reaches a scale of several hundred billion, the relative incremental contribution from OPC business may not be very large, and future market space may be relatively limited.” He believes it’s not ruled out that some banks will try these initiatives from the perspective of innovation, but the timing to advance across the whole industry may not be mature yet.

A business负责人 from a city commercial bank in Shandong said that the bank has just started engaging with OPC companies, and it still needs to gradually understand the differences between this customer segment and traditional small micro enterprises during the engagement process. A credit relationship manager at a city commercial bank in Hebei said that in our small cities, businesses like OPC are almost nonexistent; they are mostly found in major cities with strong economic vitality.

A more realistic consideration is risk. The aforementioned East China city commercial bank person also told reporters that although their bank is highly focused on the development of OPC, at present it still maintains an overall wait-and-see stance. From the perspective of credit risk, OPC often has uneven quality, and identifying risk points remains one of the challenges. Today they launch a product; tomorrow, a large number of competitors may flood in. The value-preserving ability of patents and market acceptance can change overnight, making it difficult for banks to control.

These concerns are not without reason. Tian Lihui, Dean of the Institute of Finance Development and Research at Nankai University, analyzed that the rise of OPC has deep industrial logic, but operating “one-person companies” highly depends on the founder’s personal abilities, and they have weaker operational resilience and anti-risk capacity. There may also be hidden risks of mixing public and private assets.

This division is also reflected in data. According to information reporters obtained, although more than 10 banks have launched OPC-dedicated products, the vast majority are concentrated in economically developed regions such as Jiangsu and Zhejiang, mainly involving city commercial banks and rural commercial banks. State-owned large banks have also gotten involved to a certain extent, but more as localized pilots by branches, without forming a full-bank strategic layout.

If the discussion earlier was about the operational difficulty of whether banks “dare to lend,” then after OPC becomes deeply bound to AI, OPC’s own risks are also taking on new forms. Specifically, Li Gengnan, a specially invited senior researcher at the Central University of Finance and Economics Green Finance Research Institute, broke down four major risk dimensions in detail:

First, mismatch risks between the legal subject and the acting subject. If AI agents have independent authority to make transaction decisions, and an algorithm makes a major mistake causing asset losses, under the current Company Law and the Civil Code it is hard to clearly define whether liability belongs to the “individual shareholder” or to the “defect of the AI tool.” Banks may face the risk of liability attribution becoming an “empty seat.”

Second, risks related to valuation of data assets and privacy compliance. At present, there is no widely recognized valuation standard for OPC data assets. This could lead to scenarios like overvaluing data assets to cash out, or using false model pledges. Meanwhile, the sources of AI training data are complex. If they involve copyrighted data or personal information without authorization, banks may also face joint compliance risks during service.

Third, risks related to technology application and operational safety. OPC business decisions rely heavily on output from large models, and AI may generate content that appears reasonable but is actually wrong—the risk of “AI hallucinations.” If banks base credit decisions on such “hallucination” data, it will directly cause decision errors.

Fourth, risks of technical failure and commercial sustainability. The AI industry’s technology iterates extremely fast. Once a technical route is overturned or a product fails to gain market acceptance, the product lifecycle of an OPC-developed offering will be extremely short. After failure, it can directly evolve into non-performing loans for the bank.

Liu Yong also added a key risk point from an operational standpoint: the OPC lifecycle depends highly on a single founder’s time and technical capacity. Once the founder faces health crises, burnout, or makes errors in the technical route, the company will face a survival crisis.

These risk dimensions form a brand-new set of challenges that OPC finance in the AI era must address. How to identify real risks by penetrating through the technical façade while supporting innovation tests banks’ ability to adapt, and also raises new requirements for existing regulatory frameworks.

So should banks follow this wave of OPC finance boom—or not? Perhaps the answer is not simply “yes” or “no.”

Multiple banking industry observers believe that banks pushing into OPC are not only to provide credit support, but also to lock in customers with explosive potential and capture the resulting comprehensive business dividends such as deposits, settlement, and investment banking. Under current conditions where growth in traditional corporate banking is under pressure and competition in retail banking is intensifying, OPC customer segments with both “enterprise settlement” and “personal credit” attributes are indeed a blue ocean market that urgently needs to be developed.

But in reality, OPC finance is still in the stage of exploration and verification. Dong Shimiao, Chief Economist of 招联, reminded that banks must remain clear-eyed about the special risks of “one-person companies” and build effective risk-control strategies. The traditional loan approval approach centered on fixed assets and financial statements almost fails for OPC. Banks should build an entirely new multi-dimensional credit image model.

For institutions like Jiangsu Bank and Nanjing Bank that entered early, this could be a strategic layout aimed at the future—today’s one-person company may be tomorrow’s unicorn. For more banks still waiting, it may also be a rational market choice to follow once the model runs successfully.

The aforementioned East China city commercial bank person added that currently OPC financial business is still in its early development stage. Banks that enter first might choose to exit due to insufficient returns, while banks that wait might choose to follow after seeing the model run successfully. These are normal market behaviors.

No matter how the financial exploration around OPC ultimately turns out, it has already revealed an important trend: in an era where AI is reshaping business models, the credit logic of financial institutions is undergoing a profound transformation—from “looking at assets” to “looking at capabilities,” from “looking at history” to “looking at the future.” If every individual who is creative and understands technology can receive appropriate financial empowerment, the stimulation of micro-level vitality can be transformed into strong resilience at the macroeconomic level.

As for how far this exploration can go, the answer may not be found in banks’ product manuals, but in the entrepreneurship stories built by one person, one computer, and a set of AI tools.