A Post-trade Provider Adds FRTB Data Service to Optimize Balance Sheet Capital

Case Study

A Post-trade Provider Adds FRTB Data Service to Optimize Balance Sheet Capital

The solution provides extendibility, allowing migration of legacy platforms to the new architecture


The client provides post-trade market infrastructure for the financial industry, automating, centralizing, and standardizing the processing of financial transactions to mitigate risk, increase transparency, and drive efficiencies across market participants.


To allow customers to optimize their balance sheet capital, the client wanted to offer a Real-Price Observation service as part of the Fundamental Review of the Trading Book (FRTB) regulation. This service assists financial industry participants with risk factors, allowing positions in their trading book to be capitalized using internal models. The client wanted Ness to partner with them to co-develop a front-to-back solution using scalable aggregation and an agile DevOps-first approach.​

FRTB updates the minimum capital requirements for market risk to address shortcomings of the current Basel III market risk capital framework. The client is uniquely positioned to assist the industry with its FRTB data needs for Over-the-Counter (OTC) derivatives and cash instruments to test models for illiquid instrument classes.


Ness designed and implemented an AWS-based scalable platform for real-price observations. One of the key features was the de-duplication of 1.2 billion transactions across all asset classes. The data transformation layer processed 18 months of anonymized transaction data, including validation of lifecycle events. This data was then made available for consumption by the data aggregation layer. We built a platform for multi-dimensional analysis with an average query response time of five seconds across 150+ users. The platform allowed business-rules-based filtering and drill-down capabilities, enabling regulators to analyze results based on observation across asset classes. Ness also built the alerting capability to notify risk factor eligibility changes.


The client delivered a scalable service that measured the modellability and capital impacts, maximizing risk capital charge efficiencies. Ness built the solution with extendibility, allowing the client to migrate other legacy platforms to the new architecture and provide new revenue-generating opportunities. The client was also able to conduct new ideation workshops using AI/ML to provide advanced analytics around pricing models and P&L attribution.