Act One: Stress Testing Scenarios — It’s Stressful Living With A Black Swan

By Harry Chopra, Chief Client Officer, AxiomSL

Since we were feeling that there was not enough stress in our lives already, we decided to consider how a financial institution’s balance sheet and other measures of financial position or business condition will continue to be stressed in a post-COVID-19 world. This naturally leads us to consider the need for stress testing processes and technologies that can be leveraged to prepare for black swan events — like an unprecedented global pandemic — and other systemic or idiosyncratic disruptive forces to liquidity management. In effect, we should be prepared to handle swans of all shapes and sizes and in multiple shades of black, white, and gray. Thus, we propose a series of ideas that should be considered by financial institutions as they seek to build industrial-grade stress testing processes.

Natural Adaptation — Connecting Daily Deposit And Loan Activities To High Quality Liquid Assets (HQLA)

While many institutions are adept at calculating liquidity coverage ratios (LCR) and net stable funding ratios (NSFR) — given the frequency with which regulators require them — for dynamic liquidity monitoring in times of stress, a comprehensive perspective is required. Assessing daily changes in the trifecta of inflows, outflows and HQLA within an organization is critical. For example, COVID-19 has led to massive drawdowns on retail savings. This has taught us that not having automated connectivity between daily deposit activity and cashflow, impacts an organization’s ability to accurately create liquidity stress testing scenarios.

Fortunately for some organizations, FDIC 370 regulations in the U.S. as well as European Banking Authority (EBA) and national central bank (NCB)-mandated regulations like AnaCredit and Deposit Guarantee Schemes (DGS), have forced many to improve their loans and deposits management and monitoring solutions. As a result, many firms now have their customers-accounts-deposits data integrated into a single repository covering risk management, compliance, and management information. Thus, they can produce an accurate daily perspective on deposit flows. Liquidity managers should carefully consider how this adjusts their view of expected outflows in these turbulent times. This number is surely higher than any drawdown rates prescribed in typical LCR reports and pre-COVID-19 stress testing scenarios.

Cashflow Currents And Staying Afloat On HQLA

On the flip side, inflows are faring no better. People and businesses across entire economies are cut off from their sources of income, and governments have put moratoriums in place that provide relief for borrowers but leave lenders waiting. This is in addition to the problem of an increasing risk of defaults, as discussed below. Furthermore, a firm needs to keep a close eye on its book of HQLAs, which faces liquidity risk as the issuance market dries up and the risk of downgrades increases. Through recent injections of large amounts of cash and liquidity support into the economy — including direct purchases of corporate debt securities — raising funds through wholesale money market instruments has been helped by the actions of the U.S. Treasury and Federal Reserve, the U.K. Bank of England and similar national bodies. But like a babbling brook flowing slowly towards a lake, benefits take time to trickle down to all participants in the economy.

Firms need stress testing scenarios and processes to manage liquidity and capital risks during systemic disruptions.

To summarize, step 1 for coping with a black swan involves having a deep understanding of what physical or virtual network of factors drive liquidity. And how those factors impact both short-term liquidity and medium-term funding buffers in times of extreme economic stress.

An Altered Color Gene — Understanding Credit When The Definition Of Default Changes

Capital adequacy measures and related reporting requirements such as standardized approach to counterparty credit risk (SA-CCR) and the fundamental review of the trading book (FRTB) provide a system-driven mechanism to report wholesale credit and market risk on a financial institution’s books. In these uncharted new times, the very definition of default is changing. This is mandated by newly installed legal default forbearance, an economic stimulus program, or a regulator. Such a scenario is almost impossible to model. Having said that, future stress testing processes for deteriorating credit will have to cater for exceptions, given the unprecedented precedent set by COVID-19. To model this in step 2, it makes sense for an institution to have a system-driven perspective of their credit and market risk profile. Having this type of data available in a repository — complete with daily calculations — will provide the best-case scenario of inputs for stress testing scenarios.

Keeping The Swans At Bay By Utilizing Capital Buffers

Due to many COVID-19 driven regulation reprieves, the entire industry has gained a year to reflect on how best to address upcoming Basel IV requirements. Many of the concepts contemplated within the Basel framework can be implemented in processes that take future regulations and stress testing scenarios into account. They are outlined as follows:

  • Capital conservation buffer — designed to avoid breaches of minimum capital requirements.
  • Countercyclical capital buffer — aimed to ensure that capital requirements consider the macro-financial environment.

As a financial institution’s top line is stressed, as is occurring in the current crisis, there will be greater demand for credit to stay afloat. Decisions by the EBA and NCBs to provide fiscal or monetary help to the real economy translates into credit growth. The same phenomenon is true for North America and in most economies around the world. Thus, step 3 means provisioning for both buffers with stress scenarios and understanding the impact of these buffers in a challenging economic environment.

Don’t Make Assumptions

There is yet another quasi-esoteric topic to consider — the assumption that all swans look alike, and that risk appetite should be assessed as a percentage of annual earnings. This percentage could be thought of as the level of loss a bank can sustain in a financial year and continue functioning. The amount typically ranges from one to two quarters of earnings, but perhaps it is time to revisit those assumptions. COVID-19 has shown that a drastic reduction in global economic activity in a very short timeframe is entirely possible. Therefore, it follows that step 4 would require a perspective on risk appetite in terms of the economic scenario that is being modeled. While this perspective could differ from institution to institution depending on what risks they are most prone to, it could be dangerous to assume that there is only one right answer. And not just esoterically.

A Ballet Of Stress Testing Scenarios

In the European Union, financial institutions are required to have robust ILAAP, ICAAP and IFRS-9 stress testing processes in place as part of their risk management monitoring. However, even without those regulatory obligations, stress testing is increasingly becoming mandatory when assessing the ongoing financial health of institutions. Having an accurate point-in-time view of financial positions that cuts across the below, combined with an understanding of one’s own risk appetite, serves as the basis for developing stress scenarios. At a minimum, positions should include:

  • Deposits, loans, trading, and banking books
  • Liquidity ratios
  • Credit risk
  • Market risk
  • Operational risk
  • Capital buffers


At its most basic, stress testing can be done using a series of assumptions and utilizing end-user computing tools to gain insights. In a post COVID-19 new normal, financial institutions will seek more depth and detail, leading to an increasingly complex undertaking that will have to examine all members of the flock:

  • A changing definition of default
  • Inclusion and/or exclusion of certain types of exposures and their hedges
  • Assumptions on the initial and/or scenario-specific values of collateral and exposures across asset classes
  • Assumptions about correlations and volatilities in hedging strategies
  • Assumptions about interconnectedness and risk contagion
  • Assumptions on liquidity runoff rates and HQLA recognition of various asset classes
  •  Changes to risk appetite, given stress conditions


So, in other words, a financial institution’s stress testing framework needs to be comprehensive, fully integrated, and built to encapsulate all aspects of an organization’s business.

Other than a vacation far away from swan-inhabited waters, what could mitigate all this stress?

Firstly, a data management platform that can consolidate and house point-in-time data sets to provide a holistic perspective that accommodates all of the above considerations. And secondly, leveraging this platform to serve as a foundation of transparent and traceable data to drive stress testing processes in a world reeling from COVID-19, and perhaps other (as yet) unimagined black swan events.

Given the picture outlined above, there is much to be done over the next couple of years to get financial institutions ready for implementation of industrial-strength stress testing processes. On the positive side, effectively addressing these concepts will not only imbue financial institutions with confidence on their Basel journeys, but it will enable them take flight on a favorable breeze in a post-COVID-19 new normal.

Taking Flight With Stress Testing Scenarios and Processes: AxiomSL’s Data Management, Risk Calculations, And Reporting Capabilities

Running on its secure RegCloud® or on premises, AxiomSL’s ControllerView® data integrity and control platform provides institutions with a strategic and scalable, end-to-end reporting capability to address regulatory reporting transparently and efficiently across Basel and other frameworks. Underpinned by its extensible, flexible data dictionary architecture, AxiomSL’s powerful risk calculation spectrum architecture provides a framework for a range of complex Basel-related capital and liquidity calculations, including the analytics to support results of risk-weighted assets (RWA), LCR, NSFR, funding net spread and stress testing scenarios. The platform delivers the calculations, calculation histories, optimizations, granular results, analytics, and regulatory reports that satisfy compliance requirements and provide insights for capital and liquidity risk management.

AxiomSL risk solution teams are collaborating to assemble a single cohesive stress testing framework that allows scenarios to be defined and applied across all relevant risk and reporting domains, including credit risk, market risk, liquidity, and balance sheet views. AxiomSL solutions running on the platform are constantly being innovated by AxiomSL’s dedicated innovation center. Enhancements are bringing current and future solutions onto big data technologies including Spark and Hadoop, delivering cloudified and highly scalable solutions by leveraging the likes of Redshift, and providing cutting-edge user experiences powered by ControllerView with customizable dashboards powered by AnalyticView. In addition, machine learning-enabled AI solutions will help outlier detection, automation of data mapping, and predictive analysis in stress testing scenarios.

By future-proofing their risk and regulatory reporting across Basel and other frameworks with AxiomSL, financial institutions strengthen their resilience in times of crisis, and ultimately, enhance their decision making to drive business growth — even when an uninvited swan descends on them.



We use cookies in order to give you the best possible experience on our website. By continuing to use this site, you agree to our use of cookies.
Accept