Case Study: PZU achieves Solvency II compliance and up to 85% faster market risk modeling with MathWorks' MATLAB

PZU Group Develops Market Risk Model for Solvency II Directive Compliance

PZU Group, one of the largest financial institutions in Poland and the biggest insurance group in Central and Eastern Europe, needed to comply with the EU Solvency II Directive’s market risk and solvency capital requirements. Facing heterogeneous data from about a dozen internal systems and limitations with commercial packages and VBA, PZU required a development environment nonprogrammers could use to go from data collection and cleaning to Monte Carlo simulation and VaR calculation. They turned to MathWorks and its MATLAB platform (with Statistics and Machine Learning Toolbox, Financial Toolbox, and Parallel Computing Toolbox) to build a compliant internal market risk model.

Using MathWorks’ MATLAB, PZU implemented data-import and cleaning routines, calibrated a GARCH‑based time‑series market risk model, fitted risk‑neutral densities with nonlinear optimization, and ran Monte Carlo simulations to price instruments and compute VaR; Parallel Computing Toolbox sped optimizations on an eight‑core processor. The MATLAB solution includes a user interface for nonprogrammers and is now in production, accelerating development, enabling a nonprogrammer to deliver the system, and cutting calculation times by up to 85% (from over a minute to under 10 seconds), while supporting Solvency II compliance and improved risk insight.

PZU

Adam Nowicki

Expert Coordinator in the Department of Risk Management