Blockchain unlocks bank lending for smallholder farmers

Smallholder farmers, burdened by narrow profit margins, volatile crop yields, and restricted access to institutional credit, are frequently excluded from the formal financial system. Despite advances in supply chain finance, traditional banking remains reluctant to extend credit, citing weak guarantees and high default risk, impacting not only livelihoods but also the broader agricultural supply chain, creating ripple effects across retail markets, food security planning, and rural development initiatives.

In a study published in SAGE Open, researchers present a detailed analytical model of how blockchain, the technology behind digital currencies, can resolve chronic coordination issues and financial constraints in agricultural supply chains. Titled “Research on Agricultural Supply Chain Coordination Considering Financial Constraints Under Blockchain Technology,” the paper investigates how decentralized agricultural ecosystems can be realigned through strategic contract design, with significant implications for China’s agri-finance landscape.

How do financial constraints impede agricultural supply chains?

The study sheds light on the long-standing bottlenecks in agricultural production, particularly in China. Due to the unpredictability of crop yields and high production risks, farmers often face severe financial constraints. Banks, wary of limited collateral and default risks, are reluctant to issue loans, thereby stifling the development of the agricultural supply chain. Traditional supply chain finance solutions that use the credit of core enterprises offer partial relief but come with their own vulnerabilities, such as information asymmetry and coordination failures.

Blockchain technology, with its characteristics of immutability, transparency, and decentralization, offers a potential antidote to these risks. By allowing real-time monitoring and validation of transactions and supply chain data, blockchain can increase trust among stakeholders and reduce instances of fraud. The study builds on this foundation to explore how blockchain can be systematically integrated into decision-making frameworks to not only address financing hurdles but also improve coordination among supply chain actors.

Can blockchain enhance coordination in decentralized agricultural systems?

The researchers employ a single farmer–single seller model under both centralized and decentralized decision-making paradigms to examine coordination dynamics. They find that decentralized decisions, where each party acts independently, fail to achieve Pareto optimality, a benchmark where no party can be better off without making someone else worse off. The misalignment stems from the asymmetry in cost and revenue sharing, particularly since the seller bears the cost of implementing blockchain, while the farmer primarily benefits through improved financing access.

To address this imbalance, the study evaluates two contractual solutions: the cost-sharing contract and the cost-sharing-revenue-sharing contract. Under the cost-sharing contract, both farmers and sellers share the costs of blockchain implementation. However, this model still fails to achieve coordination. Although it raises the purchase price of agricultural products, this increase compresses the seller’s margins, making the contract less attractive and unsustainable in practice.

In contrast, the cost-sharing-revenue-sharing contract proves to be a breakthrough. This contract allows farmers to share not just the costs but also a portion of the sellers’ revenue. This dual-sharing mechanism optimizes profit distribution, balances incentives, and motivates both parties. Crucially, the model shows that if the revenue-sharing coefficient remains within a specific range, both farmers and sellers achieve higher returns compared to the decentralized scenario, and the overall supply chain reaches a coordinated, Pareto-optimal state.

What variables influence the effectiveness of blockchain-enabled contracts?

To validate the theoretical findings, the researchers conducted numerical simulations using MATLAB. Several key insights emerged:

• Agricultural Output Rate: A higher output rate initially increases farmer investment and returns, but beyond a threshold, returns diminish due to market oversaturation. This underlines the importance of maintaining optimal production levels.

• Blockchain Value Addition: Increased value addition per unit of agricultural product positively correlates with all major metrics, farmer inputs, purchase price, and both parties' revenue. This acts as a strong incentive for technology adoption.

• Blockchain Application Costs: As the per-unit cost of blockchain implementation rises, all key performance indicators, farmer inputs, purchase prices, and revenues, decline. The decentralized model is particularly vulnerable here since the seller shoulders all the cost, prompting downward adjustments in purchase prices.

• Cost-Sharing Coefficient: While this has no effect on production inputs or revenue, it significantly affects the purchase price. A higher cost-sharing burden on farmers compels sellers to increase the purchase price as compensation.

• Revenue-Sharing Coefficient: A higher coefficient, indicating a larger share of the seller’s income passed to the farmer, leads to a decrease in purchase price but improves the seller’s return. This balancing act makes the cost-sharing-revenue-sharing contract particularly potent.

What's next?

The study also offers actionable insights for stakeholders across the agricultural finance spectrum. For policymakers, the findings support the need to incentivize blockchain adoption through subsidies and financial instruments tailored for rural economies. Encouraging digital trust frameworks and enhancing the creditworthiness of farmers can boost financial inclusion and supply chain efficiency.

Retailers and agri-businesses are advised to actively adopt blockchain not just for traceability but also for reengineering contract structures with upstream partners. Farmers, in turn, should work on maintaining optimal output levels and forming strategic alliances to strengthen their bargaining position.

Moreover, the study also acknowledges certain limitations. It does not incorporate variables such as trust dynamics or farmer bankruptcy risk, which are highly relevant in real-world settings. Future research could expand the model to include these factors, further refining the coordination mechanisms and making the solution more resilient to operational shocks.