FRTB Technology Infrastructure

An FRTB-compliant IT infrastructure must cover three core areas: a high-performance risk calculation engine for sensitivity computations and Expected Shortfall calculations, a data platform for aggregating market data, positions and risk factors, and a reporting system for regulatory submissions. ADVISORI designs this architecture in a modular way so that existing banking systems connect through standardised interfaces. The risk calculation engine must compute thousands of sensitivities per risk class within tight time windows, placing high demands on computing power and data throughput.

The Standardised Approach (SA) requires computing weighted sensitivities across seven risk classes with subsequent aggregation using prescribed correlation matrices. The Internal Models Approach (IMA) demands Monte Carlo simulations for Expected Shortfall across multiple liquidity horizons, supplemented by P&L Attribution tests and daily backtesting. The computational effort for IMA is estimated at roughly nine times that of SA. ADVISORI sizes the IT infrastructure so that both approaches can run in parallel, since banks must always maintain SA as a fallback.

Data quality is the critical success factor for any FRTB implementation. Missing granularity in sensitivities causes positions to fall into the Residual Bucket, eliminating hedging benefits and materially increasing capital requirements. For fund positions, look-through data down to ISIN level must be available, otherwise punitive risk weights apply. ADVISORI therefore structures the data architecture on three levels: source data validation, real-time enrichment and continuous quality monitoring, ensuring that flawed data does not enter the risk calculation pipeline.

For growing trading portfolios, ADVISORI uses horizontal scaling: calculations are distributed across independent compute nodes that scale up or down automatically based on load. GPU-accelerated computation significantly reduces the time needed for Monte Carlo simulations and Expected Shortfall calculations compared to CPU-only processing. In-memory aggregation avoids writing intermediate results to disk. This architecture ensures that daily risk calculations complete within regulatory time constraints even as instrument counts increase.

Integration with existing legacy systems runs through an API gateway that serves as the central interface between trading systems, risk databases and the FRTB calculation engine. Data virtualisation allows querying data sources from different systems without physically migrating them. Event-driven architecture ensures that position changes from front-office systems are forwarded to the risk calculation in real time. ADVISORI has deployed this integration approach across multiple banking projects and can adapt it to different system landscapes.

Under CRR III and the accompanying technical standards, regulators require the IT infrastructure to guarantee full traceability of all calculations, including complete audit trails. Backtesting and P&L Attribution must run daily in an automated fashion, and results must be reproducible. Additional requirements cover IT security under frameworks like DORA and national supervisory standards, mandating access controls, encryption and contingency planning. ADVISORI ensures that the technical architecture addresses these regulatory requirements from the outset.

The timeline depends on the starting condition of existing systems. For a bank that already has a modern risk system, ADVISORI estimates six to nine months from architecture planning to production. Where comprehensive legacy migration is required, twelve to eighteen months may be needed. ADVISORI divides the project into phases: first the core infrastructure with calculation engine and data pipeline, then integration of existing systems and finally performance and reporting optimisation. This means initial regulatory calculations are possible after the first phase.