The FRTB introduced major changes in the market risk framework targeted to go live in 2019. The implementation of these regulations can’t be achieved by traditional system upgrades and FRTB requires a major overhaul of the system architecture as well as major changes in data integration, processing and management. FRTB also adds the challenge of integrating quantitative models for pricing derivatives in trading and risk management. The combination of functional and nonfunctional challenges makes it difficult for banks to adapt and evolve their system and infrastructure. A large number of calculations resulting in due to the change in the regulations can be solved by just adding hardware. The calculations for Non-Modellable Risk Factors (NMRF) that address the issue of data availability and quality mandates change in data management.

Synechron’s FRTB Accelerator for Financial Services solves these challenges through a reference implementation for standardized approach and works analytics as a services paradigm. It follows a detailed workflow which first identifies the underlying risk classes, based on the risk class identifies sensitivities, group these sensitivities into risk buckets according to factors specified by regulators to calculate the weighted sensitivities and aggregation of these sensitivities with and cross buckets (with all tree correlation scenarios) to calculate the sensitivity based risk charge. The Accelerator is an extensible, multitenant, Spark-based data analytics compute platform that makes it easy to run real-time risk calculations and integrate with quantitative, Java/Scala/python/R-based libraries if required to run an analytics function on top of the data. The processed solution can be set up using Kubernetes to enable scaling and container management of application hosted on-premises or cloud.