Supporting OPC development: Multiple regions implement a combination of financial service policies

Ask AI · What hidden industrial strategy lies behind the policy differences for OPC across different regions?

Economic Observer reporter Fan Hongmin, Beijing report

Since the beginning of 2026, “one person + AI” OPCs (one-person companies) have become a micro-level carrier of new quality productive forces, thanks to their advantages in lightweight operations and efficient innovation. Governments across different regions have introduced dedicated support policies one after another to provide security for OPC development.

After reviewing related information, a reporter from China Business News found that financial instruments have become an important lever for local governments to support OPC development. In local OPC special support policies, local government guidance funds, industry funds, bank credit, insurance, and other financial tools are frequently mentioned. In addition, innovative financial forms such as “Data-easy Loans,” “Compute Power Loans,” “insurance-linked cooperation,” and “coverage-on-investment” are also constantly brought up.

Industry research professionals interviewed by the reporter said that the core of the financial measures related to local support for OPC development lies in using a “government guidance + market tools” combination—a precise one-two punch—to solve the financing difficulties faced by OPC companies, which are characterized by light assets, no collateral, high growth, and high risk. At the same time, compared with traditional science-and-technology innovation enterprises, OPC also has clearly different needs for financial services. Against the backdrop of new business models in the AI era, local authorities are exploring entirely new ways of policy support.

A dual-wheel drive of “government guidance + market operation”

According to the reporter’s review, at the provincial and the city/district levels, many regions—including Hubei, Jiangsu, Guangdong, Beijing, Shanghai, and others—have already issued dedicated special support policies for OPC development, and most of them include financial-related measures.

According to the “Several Measures on Supporting the New Model of OPC (One-Person Company) to Accelerate Development” (hereinafter referred to as “Hubei’s ‘Several Measures’”), recently issued by Hubei’s Department of Data, it encourages the provincial data industry development fund to increase investments in OPC, steers data-asset-based credit loans such as “Data-easy Loans” toward OPC, promotes models such as “investment-and-loan linkage” and “investment-and-insurance linkage,” and guides banks, insurance companies, and venture capital/VC institutions to jointly provide diversified financing services.

On March 12, Guangdong’s Development and Reform Commission issued the “Action Plan of Guangdong Province to Support Innovative Development of Artificial Intelligence OPC (2026–2028)” (hereinafter referred to as the “Guangdong Action Plan”). It mentions giving full play to the investment role of national venture capital investment guidance funds in the Guangdong–Hong Kong–Macao Greater Bay Area, the provincial strategic emerging industry investment guidance fund, venture capital funds of local city governments, and various other funds such as corporate venture capital (CVC) and asset investment companies (AIC). The plan aims to broaden funding channels in multiple dimensions and focus investment on high-growth enterprises within AI OPC communities, forming an effective coordinated “fund matrix” to help support the innovative development of AI OPCs in an ongoing relay. It also proposes a series of measures to optimize credit services across the entire life cycle.

Regarding the financial measures related to local support for OPC development, Liu Bin, Director of the Finance Research Office at the China (Shanghai) Pilot Free Trade Zone Research Institute, said in an interview with the reporter that, in terms of common characteristics: first, they mainly use local SOE-backed industry funds, guidance funds, and seed funds as key tools to build a full-chain investment relay from the seed stage to the industrialization stage. Second, they step outside the traditional collateral-based logic to match OPC’s features of light assets and no collateral. Centering on intangible assets such as data, compute power, knowledge, talent, and orders, they launch credit products such as “Compute Power Loans” and “Data Asset Loans.” Third, they integrate credit, insurance, guarantees, and risk compensation to build a risk-sharing mechanism of “investment–lending–insurance linkage,” solving the problem of financial institutions “not daring to lend.”

“However, different regions are also forming different support emphases by combining their own industrial endowments. For example, in Guangdong, the focus is on ecosystem building. Through multi-level fund matrices, it is building high-growth OPC communities and industrial clusters. Hubei focuses on data elements, with emphasis on data-industry funds and compute-infrastructure foundations, cultivating data-driven OPCs. Beijing and Shanghai, on the other hand, focus on frontier hard technology, using large funds and compute power warrants to support innovative individuals in AI R&D and high-end service areas,” Liu Bin said.

Ding Bokang, chairman of Modern Consulting Group and chief economist of China City Investment Network, told the reporter: “The logic behind local financial support policies for OPCs is to completely remove the worries OPCs face during the entrepreneurship process and address the problems of difficult and expensive financing. Under the dual-wheel drive of ‘government guidance + market operation,’ efforts are accelerating to build a new local emerging-industry development pattern featuring ‘funds taking the lead, credit as a supplement, and a range of measures working together.’”

It is worth noting that among local financial support measures for OPC development, local government guidance funds, local industry funds, and other local SOE-backed funds are mentioned most frequently, becoming the main lever for local governments to support OPC development.

In Liu Bin’s view, SOE-backed funds have become the main lever for local governments to support OPC development for three reasons: first, SOEs can align their investments with the overall strategic plans of local governments in key areas. Second, since OPC has no collateral, funds look at technology, people, the future, and growth—matching OPC’s “soft value.” Third, OPC faces high early-stage risks, with a high mortality rate and strong explosiveness. Purely market-oriented capital is unwilling to enter the early stage, so SOE-backed funds are needed to provide “risk backstopping.” In addition, they can also play a guiding and supportive role, prompting banks, insurance companies, and venture capital to follow up.

Promote innovation in financial service models to fit OPC characteristics

In addition, in various regions’ financial policies supporting OPC, banking credit and insurance are repeatedly mentioned as financial instruments, and local authorities are also encouraging support for innovative credit and insurance models such as “Data-easy Loans,” “Compute Power Loans,” “insurance-linked cooperation,” “seed project investment and insurance,” and “coverage-on-investment.”

For example, Hubei’s “Several Measures” proposes to push data-asset-based credit loans such as “Data-easy Loans” toward OPC and promote models such as “investment-and-loan linkage” and “investment-and-insurance linkage.” The “Several Measures on Supporting Worker Intelligent OPC Innovation and Development” for Wuhan mentions encouraging insurance companies to develop products such as “seed project investment and insurance.” For OPC seed projects that receive investment, “coverage-on-investment” is applied to reduce risks in early-stage R&D activities; eligible OPCs are included in the scope of support for knowledge-value credit loans for technology-based enterprises. Working with banks, they launch “Compute Power Loans” to ease companies’ funding pressure when purchasing high-performance compute power services. For each individual loan, the maximum amount is 10,000,000 yuan. For losses of the loan principal that occur, up to 80% risk compensation is provided.

“From the perspective of innovative insurance models, it achieves a leap from traditional protection to scenario-based and linkage-based services,” Guo Jinlong, Director of the Research Center for Insurance and Economic Development at the Chinese Academy of Social Sciences, told the reporter. “‘Seed project investment and insurance’ focuses on losses from early R&D activities, providing dedicated protection for investment institutions and entrepreneurial entities. ‘Coverage-on-investment’ is a disruptive optimization of the insurance service process—it breaks the limitations of traditional insurance underwriting procedures being cumbersome and approval cycles being long. It enables investment and underwriting to be implemented simultaneously, greatly improving protection efficiency. This allows OPC seed projects to obtain risk protection at the very first time they receive investment, seamlessly connecting with the entrepreneurship process, fully reflecting the policy’s fit with OPC’s lightweight and high-efficiency operational characteristics. ‘Insurance-linked cooperation’ is collaborative innovation in financial resources, promoting deep integration between insurance and banks and venture capital institutions to form a diversified financing service system of ‘investment + loans + insurance.’ Through risk sharing and complementary advantages, it provides OPC with comprehensive, one-stop financial support.”

“Compared with traditional science-and-technology innovation enterprises that have financing needs in the range of tens of millions to hundreds of millions or even billions, with lengthy approval processes and credit models dominated by collateral and guarantees, OPC needs to build a dedicated financial service system tailored to its light-asset profile, fast turnover, and high-growth characteristics,” Liu Bin said.