What Is the International Climate Finance Database?

Developed and produced alongside climate finance researchers and machine learning engineers, this dataset is the first global project-level climate-related financial data collection covering multilateral development finance institutions (MDFIs) and multilateral climate funds (MCFs) over a 23-year period (2000–2023).

Developed and produced together with climate finance researchers and machine learning engineers, this is the first time there is a global project-level climate-related financial data collection of the multilateral development finance institutions (MDFIs) and multilateral climate funds (MCFs) for a specified 23-year period (2000-2023).

Available through Figshare, the database includes:

• 295 project records
• Detailed classifications (e.g. mitigation vs. adaptation)
• Subcategories (e.g. solar, wind, hydro, bioenergy, environment)
• Funding modalities (grants, loans, equity, guarantees)
• Institutional breakdowns (e.g. EBRD, IFC, IDB)
• Country-level distributions

The project is documented in a peer-reviewed article published in Nature Scientific Data in June 2025.

Why the International Climate Finance Database Matters: Context and Challenges

Global climate finance is a $600+ billion ecosystem, but transparency is still a big issue. Much of the data publicly available is siloed, inconsistent, or paywalled data. Until now, it has been a nightmare to navigate how macro-scale international lenders have been sup- porting the implementation of climate goals, or goals related to climate action, like ramping solar energy in Morocco, or resilience infrastructure in Bangladesh.

This dataset provides a remedy. It systematically maps who funded what, where, how much, and why.

The Technical Backbone: Machine Learning with MLCF-BERT

The database relies on a machine learning model called MLCF-BERT, trained to classify projects into “adaptation” and “mitigation” categories using natural language processing (NLP). The result is a reproducible, scalable method of climate finance categorization that minimizes human bias and enables large-scale tracking.

Example: A 2015 wind farm development in Egypt funded by EBRD is tagged as Mitigation > Wind Energy, along with its grant and loan structure. This allows climate analysts to easily surface all wind-related investments in North Africa over two decades.

Inside the International Climate Finance Database: How to Navigate the Files

Upon downloading the .zip file from Figshare, you’ll find a Code and data folder. This breaks down into two core parts:

• /Data/Climate_finance_data_2000_2023.xlsx — master dataset with 295 entries
• /Data/Climate_finance_data_by_institution/ — institutional breakdown (e.g., IFC, IDB)
• /Data/Climate_finance_data_by_recipient_country/ — country-specific records

Each record includes:

This structure allows highly customizable queries: e.g., you can filter for solar energy loans between 2010–2020 in Latin America.

Key Trends Observed (2000–2023)

Using exploratory analysis, several insights emerge:

• Mitigation dominates: Over 70% of projects fall under mitigation (renewables, energy efficiency).
• Top sectors: Solar and hydro energy are the most commonly funded subcategories.
• Diversified funding: While grants are common in lower-income countries, loans and equity dominate in middle-income regions.
• Regional skew: South and Southeast Asia received a disproportionate share of adaptation projects.

These patterns offer critical input for evaluating past decisions and planning future climate financing.

Who Should Use the International Climate Finance Database (and How)

This is not just a research tool. It’s a strategic resource for:

1. Policy makers and NGOs

Understand historic allocations and identify underserved regions or sectors.

2. ESG Analysts

Benchmark climate fund flows and validate reporting metrics in sustainability assessments. Relevant if you’re auditing or rating climate portfolios.

3. Journalists and Investigators

Follow the money: trace financing from major institutions to on-the-ground climate projects.

4. Academic Researchers

Use the raw Excel files in regression models, spatial mapping, or historical policy impact studies.

How It Adds Value to ESG and Open Data Ecosystems

At The Database Search ESG section, we track public datasets that improve transparency in sustainability. The International Climate Finance Database does exactly that. It embodies open access principles and shows how data science can improve institutional accountability.

It also fills a major gap: while private finance gets much media attention, public multilateral climate finance is the bedrock of many national climate strategies. This dataset makes that bedrock visible.

Limitations of the International Climate Finance Database to Keep in Mind

No dataset is perfect. Notably:

• The database contains only 295 entries — it’s a curated subset, not a full census.
• It focuses solely on multilateral finance, excluding bilateral or private flows.
• Project descriptions vary in quality, depending on original source documents.

Still, its methodological rigor and open access format make it a cornerstone for future research.

Final Thoughts: Small Dataset, Big Potential

While 295 rows may seem modest, their depth, consistency, and categorization unlock powerful insights. Whether you’re building dashboards, crafting ESG reports, or advising policy, this resource gives you a clean, trusted dataset to work from.

If transparency, accountability, and impact are more than buzzwords for you, the International Climate Finance Database is worth your time.

For a closer look at how climate disinformation can distort the public understanding of data like the International Climate Finance Database, explore our article on the Hot Air Tool and climate disinformation — and see how initiatives like the Coffee Sustainability Support Database help advance transparency and accountability in sustainability reporting.

Sources

• Nature Scientific Data: https://www.nature.com/articles/s41597-025-05308-x
• Dataset on Figshare: https://figshare.com/articles/dataset/International_Public_Multilateral_Climate_Finance_Dataset_from_2000_to_2023/28171535/1

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