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An ML Approach to IFIs: Determinants of IMF Lending

Project description

New tool to assess IMF deal-making

The International Monetary Fund (IMF) is an organisation of 189 countries working to foster global monetary cooperation, secure financial stability, facilitate international trade, promote high employment and sustainable economic growth, and reduce poverty around the world. What factors influence the terms of an IMF programme? And how do those factors play into shaping the design of the programmes? To answer these questions, the EU-funded MLending project will create a tool to model the programme design and implementation process. Specifically, it will create a machine learning model for predicting the loan size, number of IMF conditions and waivers during a programme. It will also design a natural language processing tool for analysis of the IMF’s Executive Board meeting minutes to capture information like individual board member sentiments, alliances between representatives of different countries and G5 stance.

Call for proposal

See other projects for this call

Funding Scheme

MSCA-IF-EF-RI - RI – Reintegration panel


Rumeli Feneri Yolu Sariyer
34450 Istanbul
Activity type
Higher or Secondary Education Establishments
EU contribution
€ 145 355,52