Case Study: UniCredit Bank Austria achieves 50% faster development and enterprise-wide market data consistency with MathWorks

UniCredit Bank Austria Develops and Rapidly Deploys a Consistent, Enterprise-Wide Market Data Engine

UniCredit Bank Austria faced inconsistent market and derived data across business units, high operational risk, and slow model deployment in volatile markets. To build a consistent, enterprise‑wide market data repository and processing engine, the bank turned to MathWorks and its products (including MATLAB, MATLAB Compiler SDK, Optimization Toolbox, Financial Instruments Toolbox, and Financial Toolbox).

Using MathWorks tools, UniCredit Bank Austria developed the Unified Market Data (UMD) engine to clean up to 100 million daily tick records, compute on‑the‑fly and end‑of‑day derived data (credit spread curves, volatility surfaces, zero‑coupon yield curves, etc.), calibrate models, and expose MATLAB‑based Java classes through a J2EE layer. The MathWorks‑based solution halved development time, improved risk management and data consistency, reduced manual data work from several hours to under 30 minutes, cut operational and audit costs, and is now used by hundreds of managers and traders across the bank.

UniCredit Bank Austria

Peter W. Schweighofer

Senior Market Risk Manager