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FRTB Scenario Service

The Fundamental Review of the Trading Book (FRTB) Scenario Service delivers cross-asset historical pricing derivation, from time series gap filling to proxying and configurable scenario generation for FRTB. It comes pre-populated with IHS Markit's historical pricing data, which banks can supplement with proprietary or third-party data.

Summary

FRTB includes new stress testing rules and requirements for pricing data going back to 2007. In order to comply, banks face the challenge of identifying and processing appropriate market data sources, filling time series gaps and making justified proxy decisions. The FRTB Scenario Service, which helps banks meet these challenges, is comprised of two distinct products:

  • Markit Risk Factor Utility (RFU), a cloud-based risk factor modelling environment
  • Markit FRTB Data Service, a repository of historical pricing data and other FRTB-related data

As part of the FRTB Scenario Service, the RFU comes prepopulated with historical pricing data from the FRTB Data Service. Banks have the option of supplementing this time series data with proprietary and third-party data.

The service supports banks by delivering historical time series derivation and producing transparent, scalable, flexible scenarios, which can be consumed by risk engines as part of backtesting, profit and loss attribution (PLA), expected shortfall (ES) and stressed expected shortfall (SES) calculations.

When combined with the FRTB Modellability Service, the FRTB Scenario Service also supports NMRF proxying, which makes FRTB internal models approach (IMA) scenarios fully transparent for ES, SES and PLA.

Key Benefits

  • Unique historical pricing datasets
    The FRTB Scenario Service comes prepopulated with IHS Markit cross-asset historical pricing datasets. Banks can use these datasets in combination with their own or third-party time series. IHS Markit price histories are cleansed and validated, ensuring integrity and consistency over time
  • Flexible Notebooks
    The service includes a flexible, polyglot Notebook interface which end-users can design and configure themselves using a variety of languages, including R, Python, SQL or Scala. Notebooks give end-users the power of analytics and rich visualisations at production scale, creating a financial data scientist capability that dramatically reduces 'time to insight' and 'time to approval'. Notebooks can also be used as the basis for model approval document submissions, further reducing IMA implementation costs
  • Flexible, modular design
    Banks have the flexibility to mix and match the different functionality offered by the FRTB Scenario Service with their existing infrastructure, and to increase their use of the service over time. For example, they may initially choose to only use the FRTB Scenario Service for NMRF proxying and gap filling. However, at a later stage, they may decide to also use the service to generate their scenarios
  • Operational from day one
    Because it is hosted, the FRTB Scenario Service is immediately operational and pre-configured to generate scenarios when implemented. Users have the ability to customise the pre-configured models and develop their own

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IHS Markit Event Jun 21, 2018

IHS Markit Compliance Series - The CRS Editio (...)

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IHS Markit Event Jun 12, 2018

Amsterdam Loan Market Seminar

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IHS Markit Event Jun 12, 2018

The Data and Disruptive Technology Forum

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IHS Markit Event May 25, 2018

Economic Outlook Briefing

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IHS Markit Event Jul 05, 2018

IHS Markit Compliance Series - The CRS Editio (...)

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