Financial supervision: SupTech with machine learning in an early warning system

What it is about

A conversation about the research paper “Empowering financial supervision: a SupTech experiment using machine learning in an early warning system” and its conclusions. For financial supervisors, information encoded in text is a valuable complement to the balance sheet data routinely used to assess the soundness of institutions.

The study uses natural language processing (NLP) techniques and network analysis to detect anomalies in the Spanish corporate system and identify idiosyncratic and systemic risks. Sentiment analysis detects anomalies in the behavior of specific companies, while network metrics monitor system risks. In supervisory technology (SupTech), these systems are a proactive tool for financial authorities and can give early warnings of possible financial stress or systemic risks.