How Automated Data Lineage Simplifies FRTB Regulatory Compliance

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FRTB Regulatory Compliance

How much money should you set aside for a rainy day?

Well, the answer to that depends on whether you live in Buenaventura, Columbia (with an average of 131 rainy days per year) or Las Vegas (which has only 4 rainy days per year).

If you live in Las Vegas, it would be a shame to have your financial resources sitting around doing nothing in your rainy-day fund (especially when there are so many other things you could do with some cash in Vegas…).

If you’re a Buenaventura resident, too little in your rainy-day fund could easily leave you high and… dry.

If you’re wondering where we’re going with this, it’s to the question of: How much capital reserve should banks set aside for financial dips?

Well, the answer to that depends on what kind of activities they involve their funds in. 

Banking vs. Trading

One major activity banks are involved in is… get ready for it… banking! 

Lending money. Borrowing money. Interest. You know, what bankers have done since before there were banks.

Banking activities certainly have their risks, like credit risk (e.g. borrowers defaulting on loans) and operational risk (e.g. fraud), that need to be taken into account when calculating capital reserve. But they are by no means the riskiest activities engaged in by banks.

Stocks. Bonds. Forex. Commodities. Fixed income. Equities.

Trading is a much more risky activity for banks (or for anyone!).

When a bank wants to answer the “how much should we have in our rainy day fund?” question, the question needs to be asked separately for the banking desk and the trading desk.

That distinction is the thrust of Fundamental Review of the Trading Book (FRTB) regulations, the last piece of Basel III, slated to go live on January 1st, 2023.

If Basel IV defines how to measure credit and operational risk for the purposes of capital reserve requirements, FRTB defines how to measure market risk for the same purpose.

And just like data intelligence was critical for your financial institution’s success with Basel IV, so it is critical for FRTB regulatory compliance and all BCBS 239 compliance.

Standardized vs. Internal Models

Basel III sets out a standardized model for capital requirements for banking and trading activities. This model (predictably) demands higher amounts of capital reserve than the models banks were accustomed to using.

No bank wants to be forced to hide cash under the bed. A bank wants the lowest possible amount of required capital reserve, so the maximum amount of their money can be active making more money!

While the legislators of Basel III wanted to do away altogether with internal models for capital requirements, they were only partially successful. Internal models are much more restricted and regulated than before. For Basel IV, for example, output floor stipulations ensure that even where internal models are used, the result can be no lower than 72.5% of the standardized result.

Some of the requirements for FRTB regulatory compliance for approving internal models include:

  • Separate data aggregation for the banking and trading desks
  • Forecasting simulated profits and losses using their model’s calculated capital reserves 
  • Backtesting their model with real pricing and holdings data dating back to 2007
  • Modeling expected shortfall calculations to address worst-case scenarios in their investment strategies


For a financial institution that has never had to deal with this level of data precision and granularity, it can be overwhelming. 


You’ve Got a Friend in Automated Data Lineage!

Data lineage is the process of tracing your data throughout your BI landscape and seeing visually exactly how it all fits together.

Automatic data lineage is when you don’t have to go through your BI systems with a magnifying glass, a fine-tooth comb, and twenty cups of coffee in order to do it.

Need a Refresher on Data Lineage and Its Use Cases?
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With an automated data lineage tool, you can:

  • see exactly which source system the data came from
  • see how numerous data silos were combined into a unified dataset, for instance, integrating risk (past) and finance department (future) data
  • easily conduct impact analysis: if this data point or condition changes, what will be affected?
  • know what data your reports are based on to help ensure that ALL your risk reporting is aligned and based on trustworthy data

Automated data lineage for FRTB gives you visibility into your data with the clarity, granularity and precision that you need to have your internal models accepted by FRTB requirements regulators. 


The time is right. The time is now. 

Automated data lineage management would be a financial institution’s best friend even without the looming specter of FRTB regulatory compliance reports.

But sometimes you need a little push. FRTB is here to give you that gentle – or not so gentle – nudge.

Take care of it now; don’t put it off for a rainy day. Especially not if you’re the First National Bank of Las Vegas. 

Automated Data Lineage Simplifies and Streamlines Compliance
See for yourself how you can leverage Octopai for compliance and other day-to-day BI challenges.
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