FRTB Data Model
A data model is provided to support the SA and IMA approaches. This is the default data model for all data required, and incorporates the following features:
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Trades with economic and organisational attributes
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Trades, Positions and Sensitivities per Risk Factor and other granular data for SA
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Trade Historical P&Ls, Historical Simulations and other granular data for IMA
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Classifications, Books, Desks, Risk Categories, etc.
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Correlations and other constants imposed by regulators
FRTB Accelerator components
The FRTB Accelerator comprises six components, each with its own cube. Each component is also associated with one or more Input File Formats and Datastore Definitions. The following table lists these cubes, and provides links to their associated schemas, datastore definitions and input file formats.
| Cube | Cube schema | Datastore definition | Input file formats |
|---|---|---|---|
| SA Cube | Standardised Approach Cube Schema | SA Datastore Definition Global Datastore Definition |
SA Input Files |
| IMA Cube | Internal Models Approach Cube Schema | IMA Datastore Definition Global Datastore Definition |
IMA and IMA Summary Input Files |
| IMA DRC Cube | Internal Models Approach DRC Cube Schema | IMA Datastore Definition | DRC Files |
| P&L Cube | Profit & Loss Cube Schema | IMA Datastore Definition | P&L Attribution Tests and Backtesting File Formats |
| P&L Summary Cube | Profit & Loss Summary Cube Schema | IMA Datastore Definition | PL Summary |
| FRTB Combined Cube | FRTB Combined Cube Schema | Not backed by any datastore.See note below | Input file formats the same as for all the other cubes put together |
The FRTB Combined Cube is a query node that is built from the other cubes. As such, it contains the union of all the hierarchies and measures from the other cubes.
Input Data File Formats
Input data file formats using a CSV style are provided.
Customer Override for the Data Model
Pre-defined data model is available, but it is possible to easily adapt this to the bank’s own source formats. Each bank will then own their own data model and be able to change classifications etc. that are not fully defined by the regulators. This means a customer implementation can override the ‘out of the box’ functionality so that input data can be sourced from other systems and database technologies.
For further information, see FRTB Input File Formats.
Datastore Definitions
For further information, see FRTB Datastore Configuration .
Pre-defined Cubes
It is possible to have pre-defined cubes (for each of the FRTB Accelerator Components) with all Measures set in advance or to let users dynamically select Measures and instantiate them on-the-fly in the cubes (ActiveMeasures).
A flexible set of attributes and dimensions (hierarchies, dimensions, levels of the cube structure) is supplied for each of the Accelerator components (cubes).
For further information, see FRTB Cube Configuration .
ETL (Extract, Transform and Load)
As part of the data loading process, the ETL layer handles data manipulation between the file format and the internal datastore structure. For the various files, this can include Vectorization, Interpolation, and Normalization.
For further information, see FRTB ETL (Extract/Transform/Load).