Pioneering hedging-based commercial credit debt resolution, leveraging mud plate data to solve the triangular debt dilemma
Against the backdrop of China's domestic economic transformation and adjustment, accumulated debt issues of all types of market entities have become increasingly prominent. The interlocked "chain debts" where multiple parties owe each other money not only clog the cash flow of micro, small and medium-sized enterprises (MSMEs), but also pose many practical challenges for local governments in their debt resolution efforts. Traditional debt clearance methods usually rely on one-way fund settlement, which features long procedures and high coordination costs, making it difficult to break the interlocking debt chains in batches. Targeting this unmet real demand, the team of Niban Data (Niban Cloud Chain Data Service Co., Ltd., hereinafter referred to as "Niban Data") has developed a prototype debt resolution platform with the core logic of "using commercial credit to hedge debts", aiming to allow the stock of accounts settled in debt chains to be resolved autonomously within a closed-loop network.
The Trillion-yuan Chain Debt Dilemma: Overdue Accounts Turn into "Dead Knots", New Paths for Debt Resolution Are Urgently Needed
Data from the National Bureau of Statistics shows that by the end of 2025, the accounts receivable of industrial enterprises above designated size across China reached 27.43 trillion yuan, with an average collection period of 67.9 days; data from the Ministry of Finance shows that by the end of 2025, the balance of local government debts nationwide reached 54.82 trillion yuan. Intertwined corporate accounts receivable and government payable payments form a complex and tangled debt network. For enterprises, delayed receivables mean sustained pressure on cash flow: poor repayment from upstream suppliers and delayed payment to downstream partners leave many enterprises trapped in capital turnover difficulties, and even lead to production suspension.
Traditional debt clearance methods rely on one-way fund settlement, and one chain debt usually requires multiple rounds of capital turnover to be resolved, with long processes and high coordination costs. The history of nationwide centralized chain debt clearance in the 1990s also illustrates this problem: the Chinese government injected 52 billion yuan of bank credit funds over two years, plus 3.5 billion yuan raised by local governments and enterprises, clearing a total of 219 billion yuan in overdue payments, achieving the effect of "clearing about 4 yuan of overdue payments by injecting 1 yuan of funds". However, overdue payments are prone to rebound after the clearance campaign ends. The crux of the problem is that both administrative coordination and monetary injection focus on the settlement of individual debts and single entities, failing to utilize the network correlation between creditor's rights and liabilities to allow the debt to shrink structurally on its own.
Pioneering "Commercial Credit Hedging": Allowing Stock Debts to Be Resolved Autonomously in a Closed-Loop Network
The solution proposed by Niban Data replaces the inherent idea of "settling debts with currency" with "hedging debts with commercial credit". The team maps mutually confirmed and undisputed receivables and payables to a directed weighted debt network, uses big data analysis to quickly locate closed debt loops with end-to-end connections that can be offset, and then all participants sign a multilateral offset agreement to perform synchronous netting of equal parts of creditor's rights and liabilities within the closed loop: if A owes B, B owes C, and C owes A, when the three debts mature at the same time, they are hedged by the equal amount of the smallest edge, and the receivables and payables of all parties are reduced simultaneously without any new capital injection. As more accounts are included in the network, the density of nettable closed loops rises, and the resolution efficiency of stock debts is significantly improved compared with manual coordination.
The technical infrastructure supporting this mechanism is not complicated: the team has designed a Standardized Digital Receipt Certificate (SDRC), which registers confirmed accounts as structured digital certificates as a unified carrier for debts to enter the computable network; it records netting events with a permissioned debt data chain to achieve traceability and auditability; the entire system is built on a four-layer architecture of "account docking - confirmation registration - closed-loop algorithm - debt data chain", which can be embedded in the existing financial systems of enterprises for operation, so that enterprises do not need to replace their accounting software.
This mechanism has clear legal and business boundaries. Legally, multilateral offset is implemented through multi-party agreement arrangements in accordance with the rules of statutory offset in Article 568 and agreed offset in Article 569 of the Civil Code; the mechanism does not create currency, does not replace the monetary payment system, the closed-loop netting only writes off the equal part, the remaining difference debt is still settled according to the original path, and does not eliminate the net position of any party. The team emphasized that there is no directly comparable product on the market at present, and this platform is the first prototype of an innovative service platform in China targeting full-domain chain debt resolution, which belongs to the exploration from 0 to 1.
From 0 to 1: The Prototype Is Completed, Only An "Admission Ticket" For Implementation Is Needed
In terms of business model, the platform charges corresponding settlement service fees by providing debt hedging and settlement services, and is open to all enterprises in need of debt resolution, with a straightforward and clear profit logic. As the project has not yet been put into operation, there is no actual revenue and profit generated at present; the team has completed prototype development with self-raised funds, and financing information has not been disclosed for the time being, nor has it connected with implementation pilots and potential users.
From conception to prototype, the core R&D team consists of three members, who are responsible for system design, big data analysis and program development respectively. At present, the 1.0 version of the system prototype has been developed, and the Internet service filing has been successfully completed. However, the project also faces multiple practical challenges: it has not been officially put into operation, lacking operation data in real scenarios and referable cases; as a start-up innovative project, it lacks sufficient credibility endorsement, and there is no public team background and financing information, so the project is temporarily in a stagnant state.
"From conceiving to building the prototype, every step is exploratory, because there are no comparable references," the team stated. For this innovative model to be truly implemented, credibility endorsement is indispensable, so the team looks forward to obtaining top-level design support from relevant government departments, or resource docking from central SOEs, local state-owned enterprises and large Internet manufacturers. "Only by getting the admission ticket can this innovative model be truly tested by the market and help more market entities untie the dead knot of debt." In the next step, the team plans to prioritize the promotion of the project to land in pilots, accumulate real operation data and cases, and then gradually open up to the whole market. The long-term goal is to become a professional debt resolution service platform covering all market entities across the country.