Green Finance and Sustainable Credit Scoring
| EU & Industry Partners | EUR 400K | 2021–2024 |
Overview
Research initiative developing AI-powered green credit-scoring models for retail and commercial customers, integrating sustainability factors into traditional credit-evaluation processes.
Role
Partner — leading the machine learning and AI components for green credit-score development.
Research Objectives
- Develop green credit scores integrating ESG factors.
- Apply machine learning to sustainability-linked lending.
- Bridge traditional credit risk with environmental metrics.
- Support the global transition to sustainable finance.
Methodology
| Approach | Application |
|---|---|
| Machine learning | Green credit-score prediction |
| NLP | ESG-report analysis |
| Network analysis | Supply-chain sustainability |
| Explainable AI | Regulatory compliance |
Impact
The project encourages environmentally responsible practices and aligns with the global push towards sustainability in economic activities, supporting banks and financial institutions in their green transition.
Collaborations
- European financial institutions
- Sustainability rating agencies
- Academic partners across Europe
- Industry practitioners in ESG analytics
Related Projects
See also: ASEAN Green Finance — Advancing Higher Education for Sustainable Growth in Southeast Asia (Erasmus+ CBHE, 2025–2028).