Nature

Causal impact evaluation of occupational safety policies on firms’ default using machine learning uplift modelling

Public policies on occupational safety and health (OSH) aim primarily at improving working conditions. Usually, this objective is set at constitutional level and through other regulatory sources, both ...
International Monetary Fund

Monitoring Privately-held Firms' Default Risk in Real Time: A Signal-Knowledge Transfer Learning Model

We develop a mixed-frequency, tree-based, gradient-boosting model designed to assess the default risk of privately held firms in real time. The model uses data from publicly-traded companies to ...
Nature

Enhancing transparency and fairness in automated credit decisions: an explainable novel hybrid machine learning approach

Credit risk assessment is one of the main activities within the financial services industry, influencing the dynamics of lending and the broader economic landscape. Machine learning (ML) models have ...
National Academies of Sciences%2c Engineering%2c and Medicine

Making Machine Learning Safer in High-Stakes Settings

Machine learning, a key enabler of artificial intelligence, is increasingly used for applications like self-driving cars, medical devices, and advanced robots that work near humans — all contexts ...