Grant: Canada Research Chairs

One key issue in risk management for Small and Medium Businesses (SME) is their evaluation processes, which are cumbersome, inefficient, and bias-prone. This program aims to design fair and transparent models for the probability of default of SME based on multimodal data (images, text, and traditional structured data). These models will satisfy legal requirements regarding unfair discrimination regulations and model explainability. It will do so by exploring counterfactual fairness, i.e. fair models with a known unfair impact variable, and also by creating propagation methods that focus on studying how the models learn what they learn and visualizing these effects.