Liquidity risk analysts need more refined tools to calculate ECB metrics

Liquidity Risk Analysts Need More Refined Tools to Calculate ECB MetricsLast month the European Central Bank (ECB) outlined plans to implement a liquidity sensitivity analysis on the largest banks it oversees. This is the latest in a series of stress tests aimed at measuring the stability of the financial system while acknowledging the potential for unforeseen liquidity shocks.

Banks’ traditional approach to measuring risk for earlier regulatory requirements like the Liquidity Coverage Ratio and Net Stable Funding Ratio is a months-long process. It requires gathering and collating troves of data from disparate parts of the balance sheet then applying the risk model(s) and stressed scenarios. All of the results are then stored in a data warehouse. This process incurs huge effort from both business and IT and ultimately it cannot easily measure exigent risk.

The ECB’s liquidity test sets out to gauge a bank’s “Survival Period” over different time ranges. Computing the cumulative net cash flow (inflows and outflows) over various time buckets and counting the number of days a bank can survive without access to funding beyond its existing cash and collateral is not a difficult chore. However, under the ECB test, regulators will expect a bank to present data on cash flows over a six-month period which means it will need to be able to compare the survival period of each shock as well as combinations of multiple shocks.

The real issue is not the stress test, since the ECB will continue to derive new ways of measuring systemic risk. It’s that the risk analyst, under a traditional bank structure, typically has no set of efficient, analytical tools to instantaneously calculate hypothetical liquidity shocks and quickly and clearly show the results. Measuring liquidity risk is about aggregating a bank’s comprehensive balance sheet cash flows and computing running totals on various time horizons, and then applying stress scenarios.

ActiveViam’s in-memory analytics platform, ActivePivot, turns a months-long exercise with multiple parties into an hours-long process for one point person. The software provides the ability to aggregate huge amounts of detailed financial information from entries that comprise the entire bank balance sheet and apply complex simulations within seconds. This is owed to our unique “post-processor” feature which provides dynamic, on the fly calculations, for instance, on the stressed scenarios without requiring massive duplication of stressed cashflows.

Another one of our unique abilities involves “vectorization” or compressing cash flow data, keeping it as reference data across all segments in a system’s direct memory and allowing for immediate access to it. This function provides the ability to cross reference hundreds of granular level attributes – for example, position level data on a portfolio of bonds with varying maturities or millions of cash flows on trade-level derivative positions – and paves the way for an infinite amount of data exploration and analysis.

Risk analysts have told us they are able to create a clear picture of the full spectrum of risk over a predefined time series. In sum, ActivePivot delivers the ability to inject necessary cash flow adjustments as well as applies basic modeling rules to transform a “static” balance sheet into a forward-looking balance sheet.

An analyst at any bank would be able to define extreme shocks and answer ECB questions in hours without having to store anymore data or consult anyone in IT. Our clients, which include several large European banks, have implemented the software to deliver such benefits.

“You can easily do this within hours, not days,” said Peter Dahlstrom, a senior liquidity risk analyst at SEB who has been using ActivePivot for three years.

Brexit aside, the ECB expects liquidity shocks may come from any angle. A three-notch credit downgrade or a 30% shift in a foreign exchange rate, for example, would reverberate across the entire bank balance sheet and create enterprise-wide risk. The software facilitates the user’s ability to change the stress scenario, apply a new treatment on any part of the balance sheet data (such as an extreme shock on the outflow of UK corporate debt) and immediately see the impact on the liquidity metric.

The regulator itself has not yet disclosed its chosen series of hypothetical risk scenarios. Furthermore, in the context of Brexit, the ECB is expected to perform an assessment of a bank’s intra-group liquidity flows, including those which are denominated in a non-euro currency. ActivePivot allows a risk analyst to combine this new stress test with others and compare and analyze the result by breaking down the effect of every stress scenario treatment in any section of the balance sheet all in real-time.

In the age of uncertainty that continues to rattle financial services industry, ongoing assessments of banks’ liquidity risk management frameworks are not going away anytime soon.

ActiveViam’s ActivePivot represents a sea change in the way a financial firm handles large, complex data analytics and offers an unparalleled solution to meet both regulatory and operational challenges.

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