Climate Shock Loans

Climate Shock Loans is a climate-aware lending system that connects real-world climate data to on-chain financial decision-making using Chainlink as the oracle layer.

The system enables pre-qualified smallholder farmers to access loans dynamically based on drought conditions, while ensuring that all lending is capital-backed and governed by transparent rules.

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The architecture consists of three coordinated layers: a web application, an oracle layer, and an on-chain decision engine.

The web application, built in Django, serves both as a user interface and a climate data service. It aggregates satellite rainfall data, such as CHIRPS, and transforms it into structured climate signals, including drought indicators. It also manages farmer onboarding, loan requests, and repayment flows.

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The oracle layer is implemented using Chainlink CRE. It retrieves climate data from the API, verifies it, and determines whether drought conditions are met. This result is written on-chain, ensuring that climate state is externally validated and cannot be manipulated by any single party.

In parallel, Chainlink Proof of Reserve is used to verify that sufficient capital exists in the loan fund before any lending occurs. This ensures that loans are not only condition-triggered, but also fully backed by available liquidity.

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On-chain, the system is governed by a Climate Loan Manager smart contract. This contract acts as a decision engine and manages three key components: • drought state • capital constraints • loan issuance rules

When a farmer submits a loan request, the contract evaluates both the climate condition and available capital. Only if all conditions are satisfied is the loan approved and funds are allocated from the pool.

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The application reads this on-chain state in real time, updating the interface and enabling farmers to access loans immediately when conditions are met.

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This design demonstrates how Chainlink can be used to bridge off-chain climate data and on-chain financial systems, enabling automated, transparent, and capital-secure lending triggered by real-world conditions.

Climate Shock Loans represents a shift from reactive aid to proactive financial infrastructure, where capital becomes available precisely when climate risk occurs.

The backend is a Django application (climate_loans) that serves both a user-facing dashboard and a climate data API. The API aggregates satellite-derived rainfall data (e.g., CHIRPS) and normalizes it into a deterministic rainfall metric for a specified geography and time window. This enables the definition of a reproducible drought condition based on threshold logic.

In addition to data ingestion, the backend manages off-chain responsibilities including farmer onboarding, loan request generation, and repayment tracking.

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On-chain, we deploy a Climate Loan Manager smart contract to Ethereum Sepolia. This contract functions as the system’s decision engine and maintains three core pieces of state: • drought status • available capital constraints • loan issuance rules

Rather than acting as a simple trigger, the contract evaluates loan requests against both climate conditions and capital availability. Loan approvals result in state transitions and capital allocation from the on-chain loan pool.

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The oracle layer is designed using Chainlink CRE primitives. The workflow retrieves climate data from the API, aggregates a drought signal, and writes the result on-chain. This establishes a verifiable bridge between off-chain environmental data and on-chain execution.

For demonstration purposes, we implement a Node.js service (chainlink-trigger) that simulates oracle execution. This service fetches climate data, evaluates the drought condition, and submits a transaction to the smart contract. This mirrors the production model, where Chainlink nodes execute the same logic within a decentralized oracle network.

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In parallel, Chainlink Proof of Reserve is incorporated to enforce capital constraints. Before loans are approved, the system verifies that sufficient funds exist in the loan pool. This prevents over-allocation and ensures that all issued loans are fully backed.

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The Django application continuously reads contract state from the blockchain and reflects it in the UI. When conditions are satisfied, loan requests transition from “pending” to “approved,” enabling immediate access to capital.