About a-team Marketing Services
The knowledge platform for the financial technology industry
The knowledge platform for the financial technology industry

A-Team Insight Blogs

IHS Markit and Oliver Wyman Detail Risk Factor Modellability Service for FRTB

Subscribe to our newsletter

The collaboration between IHS Markit and Oliver Wyman that is developing a risk factor modellability service to help banks determine whether risk factors can be modelled in line with the requirements of the Fundamental Review of the Trading Book (FRTB) will deliver a validated methodology that banks can use in the regulatory approval process around internal and standard models.

This will remove the need for banks within the scope of FRTB to prove individually that they have enough data to use an internal model for capital calculations, and help them avoid the capital penalties of using FRTB’s standard model that is required when a bank does not have data from at least 24 transactions in a given year, with a maximum of one month between two consecutive trades of a particular risk factor.

The risk factor modellability service will be developed within Markit’s Risk Factor Utility (RFU), which provides a flexible risk factor modelling environment and at proof of concept stage with banks in Asia Pacific and Europe. A proof of concept will start soon in North America.

The methodology underpinning the risk factor modellability service is designed to reduce the amount of time and money spent by banks on risk factor analysis, and instead help them understand which risk factors are modellable and which are non-modellable. Management consultancy Oliver Wyman is defining the methodology within the utility and IHS Markit will provide data from its FRTB data service, which combines trade data from the MarkitSERV platform with trade data contributed by partner banks.

Oliver Wyman decided to collaborate with Markit on the service to offer the banks it works with a mutualised solution to modellability. Barrie Wilkinson, co-head of finance and risk practice, EMEA at Oliver Wyman, explains: “We usually work with individual banks, but it makes sense here for banks to pool their data in a utility model and be able to show enough data for modellability. The banks are all doing the same analysis on the same data, so the risk factor service methodology should ease bank costs and reduce efforts on duplicate data.”

Yaacov Mutnikas, executive vice president of financial market technologies at IHS Markit, points out that the service is dedicated to identifying risk factors that are and are not modellable, and leaves banks to develop internal models were appropriate and handle capital calculations. He says: “If a bank can’t prove it has enough data available to use an internal model for capital calculations under FRTB, it must use the regulation’s standard model, which is punitive in terms of having to hold more capital.”

Working with Oliver Wyman, the company is planning to produce the first round of results from its risk factor modellability service early next year, showing which elements of the risk factor universe are modellable and which are not.

Subscribe to our newsletter

Related content

WEBINAR

Upcoming Webinar: The Data-First Enterprise: Fuelling Modernisation in Capital Markets

7 October 2025 10:00am ET | 3:00pm London | 4:00pm CET Duration: 50 Minutes In the face of relentless pressure for speed, cost efficiency, and mandates like T+1 settlement, financial institutions know their biggest risk isn’t a market crash – it’s bad data. When data is fragmented or untrusted, every investment in technology, from hybrid...

BLOG

PE Deal Failures Highlight Importance of Private Data, Says JMAN Group

The critical importance of data to the private equity and alternatives markets sector is starkly underlined by an observation from Anush Newman, chief executive and co-founder of JMAN Group. “In the past 18 months, I know of at least 20 acquisition deals that have fallen through because the target companies didn’t have enough data to...

EVENT

AI in Capital Markets Summit New York

The AI in Capital Markets Summit will explore current and emerging trends in AI, the potential of Generative AI and LLMs and how AI can be applied for efficiencies and business value across a number of use cases, in the front and back office of financial institutions. The agenda will explore the risks and challenges of adopting AI and the foundational technologies and data management capabilities that underpin successful deployment.

GUIDE

AI in Capital Markets: Practical Insight for a Transforming Industry – Free Handbook

AI is no longer on the horizon – it’s embedded in the infrastructure of modern capital markets. But separating real impact from inflated promises requires a grounded, practical understanding. The AI in Capital Markets Handbook 2025 provides exactly that. Designed for data-driven professionals across the trade life-cycle, compliance, infrastructure, and strategy, this handbook goes beyond...