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.