GreenCredit AI

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  Data Normalization

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  Financial Risk Profile

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  Lending Decision

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  SDG Alignment & Risk

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  Sustainability Uplift Planner

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  Start Assessment

Inspiration

Access to sustainable and fair financing is a major global challenge. Traditional credit scoring often ignores environmental, social, and governance (ESG) factors, and borrowers rarely know how to improve their sustainability practices. Inspired by the UN Sustainable Development Goals (SDGs), we wanted to build a solution that helps banks make responsible lending decisions while guiding borrowers to improve sustainability, creating a win–win for finance and the planet.

What it does

GreenCredit AI combines financial risk and sustainability assessments into a single, auditable system. It: Calculates financial and sustainability risk scores for borrowers. Suggests actionable steps for improving sustainability and credit terms. Simulates future climate and regulatory scenarios to predict risk changes. Provides human-readable explanations for loan officers, ensuring transparency and ethical decision-making.

How we built it

We used a multi-agent architecture: Data Normalization Agent – Structures borrower financial and sustainability data. Financial Risk Agent – Calculates risk based on cash flow, credit history, and industry factors. Sustainability Risk Agent – Scores SDG indicators like carbon intensity and labor compliance. GreenCredit Decision Agent – Combines scores to produce a clear lending decision. Sustainability Uplift Planner – Recommends improvements with projected score impact. Climate Transition Simulator – Models scenarios like carbon tax increases or regulatory changes. Human Review Assistant – Generates clear, ethical, and auditable explanations for banks.

Challenges we ran into

Integrating financial and sustainability metrics in a realistic, auditable way. Designing forward-looking scenario simulations for climate and policy risks. Keeping outputs explainable for human review, avoiding black-box AI. Ensuring actionable insights for SMEs and underserved borrowers with limited data.

Accomplishments that we're proud of

Built a multi-agent AI system that balances profitability, sustainability, and fairness. Created realistic, actionable recommendations for borrowers to improve credit terms. Designed a scenario simulator for future climate and regulatory risks.

What we learned

Combining financial and ESG data requires careful normalization and weighting. Human-in-the-loop explanations are critical for trust and adoption. Realistic simulations of policy and climate risks make AI outputs credible for banks. Sustainability can be actionable—small changes in operations can measurably improve credit scores.

What's next for GreenCredit AI

Expand to cover more industries and regions. Integrate real-time sustainability and market data for dynamic scoring. Add personalized dashboards for borrowers, tracking progress on SDGs. Explore partnerships with banks and fintech platforms to pilot real-world deployments.

Built With

• frontend:-react
• lucide-react-icons-ai-&-backend:-google-gemini-3-(genai)
• node.js
• recharts
• tailwindcss
• typescript