Case Study: Banche Popolari Unite achieves fast, precise VaR analysis of 700,000+ credit-risk positions with MathWorks (MATLAB)

Banche Popolari Unite Analyzes Credit Risk

Banche Popolari Unite (UBI Banca) faced the challenge of identifying and analyzing portfolio credit risk across rapidly growing customer and market data, requiring large-scale Monte Carlo simulations and visual reporting that would be too time-consuming to build in low-level languages. They engaged MathWorks and used MATLAB together with the Statistics and Machine Learning Toolbox to create a computationally efficient, visually accessible VaR framework.

Using MathWorks' MATLAB and Statistics and Machine Learning Toolbox, Banche Popolari Unite implemented a Merton-based VaR and loss-distribution model with sector regressions, factor modeling (systematic vs. specific risk), and large-scale Monte Carlo simulations, plus clear graphical outputs for management. The MathWorks solution enabled fast, precise analysis of more than 700,000 credit-risk positions, reduced algorithm development time, delivered a reliable analytical model, and supported strategic decisions such as portfolio rebalancing.

Banche Popolari Unite

Roberto Modafferi

Quantitative Analyst