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Phase 2 (From Research to Industrialization): Application of Transformer Models to Raw Credit Bureau Files for Improved Credit Risk Modelling Performance
We are developing a new system to help banks and financial institutions better assess credit risk—the chance that a borrower might not repay a loan. Traditional methods use standard data like credit scores, but they often miss valuable information hidden in detailed credit reports. Our project aims to use advanced artificial intelligence, specifically transformer models, to analyze raw credit bureau data more effectively. By doing this, we can create a more accurate and efficient way to evaluate credit risk. This will benefit our partner organization by improving their lending decisions, reducing financial risk, and increasing overall efficiency in their operations.
Faculty Supervisor:
Vahab Khoshdel
Student:
Partner:
Wealthsimple Technologies
Discipline:
Computer science
Sector:
Information and cultural industries; Mining
University:
University of Manitoba
Program:
Accelerate
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Mitacs is funded by the Government of Canada, the Government of Alberta, the Government of British Columbia, Research Manitoba, the Government of New Brunswick, the Government of Newfoundland and Labrador, the Government of Nova Scotia, the Government of Ontario, Innovation PEI, the Government of Quebec, the Government of Saskatchewan, and the Government of Yukon.