Assessing statistical bias in credit markets, an application to SMEs

This research project aims to evaluate whether members of minority groups or women face higher barriers to access credit in the small and medium-sized enterprises credit market. The intern will analyze loan-level data provided by the business partner to evaluate whether these biases are detectable in the portfolio of SME loans of the business partner. Discrimination in credit allocation prevents efficient credit allocation, besides being demeaning for the individual subject to discrimination. Notably, the business partner is committed to providing fair access to credit to all its clients, independently from gender or minority membership. Unfortunately, biases may still influence the applicant screening methodology, due to the use of variables that are highly correlated with group characteristics. This research project aims thus to contribute to the effort of the business partner to insure that its clients face fair access to credit.

Faculty Supervisor:

Valentina Galvani

Student:

Yuqing Wang

Partner:

ATB Financial

Discipline:

Economics

Sector:

Finance, insurance and business

University:

University of Alberta