Séminaire CIMMUL-CIRRELT | Cristián Bravo Roman

Leveraging Deep Learning for Multimodal Data Analysis in Credit Risk Assessment

Cristián Bravo Roman

Professeur

Western University

Résumé

Credit risk assessment is a multifaceted process in which lenders employ various measures to evaluate the risk associated with borrowers, ranging from individual consumers to large-scale companies. To achieve a comprehensive understanding of credit risk, lenders extensively analyze a wide array of data sources, encompassing images, text, social networks, time series data, and traditional financial variables. Deep learning methodologies offer significant advantages in leveraging diverse data from multiple sources to generate accurate predictions and provide valuable insights into the complex relationships inherent in these inputs. This presentation explores different strategies for handling multimodal data in both consumer and corporate lending using deep learning techniques, with a particular emphasis on transformer models. The discussion will encompass the utilization of time series data, ego networks, and textual information, with conventional financial variables. Real-world use…