The Optics Of (Sane) Liquidity Risk Management

How The Right Lens Can Make Data King When Confusion Reigns!

Gavin Pugh, Head of APAC Risk Sales, AxiomSL
Saumyadeep Datta, Head of APAC Risk Products, AxiomSL

The global economy has been in a state of chaos for over a year, resulting from the treacherous market conditions caused by the Covid-19 pandemic. The once steady increase in the interdependence of the world’s economies, cultures, and populations has hit a road bump, as countries and entities scramble to cope with the unprecedented and unpredictable market conditions. Many are hoping that this past year will be an outlier, and that the trend towards globalization will eventually resume. But, around the world, countries, and regions are reverting to tribal economics.

Perhaps this famous quote from Albert Einstein sums up the reasoning – or lack of reasoning – behind these baffling times: “Two things are infinite: the universe and human stupidity; and I’m not sure about the universe.”

Confusion Reigns, Leaving Many Dumbfounded

To many, this crazy economic world is reflected especially brightly in the equities markets where the market cap of Tesla, Inc. can exceed that of the nine largest automakers combined and the stock of a money-losing entity called GameStop Corp. can shoot to astronomical levels on a short squeeze.

A major factor behind these irrational market conditions is the low interest-rate environment that has prompted investors to shift to high-risk investments and resulted in excess liquidity in the market. The search for higher returns has propelled many speculative securities and instruments, such as cryptocurrencies, to unimagined highs – during a period when the global economy is at a pandemic-driven standstill.

Another factor leading the market astray is the ever-present stream of so-called fake news that is adding fuel to the fire.

Access To Good Data – Key To (Sane) Liquidity Risk Management

To navigate these volatile conditions, financial institutions need to be nimble. They must be able to quickly weed through the barrage of misinformation to envision real outcomes. More than ever, access to accurate data remains essential to make critical decisions in a tight timeframe. Nowhere is the importance of data more apparent than in financial institutions’ treasury departments where many struggle to monitor liquidity risk due to a number of factors including:

  • Increasing regulatory oversight
  • Changing nature of funding markets
  • Need to manage huge volumes of daily, monthly, and quarterly liquidity data
  • The burden to report correctly and more frequently


Having access to the right data and efficient data-management software would enable treasury departments to study key variables over time (historic balances, intercompany payments and receipts, and forecasts versus actuals) to determine the levels of capital required for each unit. Being able to hone operating capital levels with transparency and confidence is crucial especially in the current low-interest rate environment. For firms operating with low margins, holding excessive capital buffers under these conditions can be painful and possibly fatal. Accurate, well-managed data is a goldmine that yields critical information about the liquidity health of a financial institution – a boon in terms of liquidity risk management.

But when confusion reigns, how can organizations establish a better, saner perspective on liquidity data and risk management?

Back To Einstein, Physics, and Optics

Rules of physics indicate that when light rays pass through a concave lens, they diverge, whereas when they pass through a convex lens, they converge, as shown here:

liquidity risk management: concave and convex lens

Indeed, this simple optics concept applies quite neatly to data architectures for liquidity data and regulatory risk management.

The Concave Lens Approach – Contributes To Confusion

Most financial institutions tend to send their liquidity-related data through a concave-lens shaped system depicted below whereby:

  • The upstream data sources are the incoming rays of light
  • The data repository acts as a concave lens
  • The downstream systems are the outgoing rays of light

liquidity risk management: a divergent architecture

Under this concave-lens like process, synergies achieved in the data repository are lost as data diverges to different systems (mostly Excel-based regimes) for each regulatory requirement including liquidity coverage ratio (LCR), net stable funding ratio (NSFR), fund transfer pricing (FTP), funding gap analysis, and for other internal liquidity management needs.

This divergent use of data creates serious problems that damage the potential for efficient, informative liquidity risk management. This structure inhibits validation of information across regulatory regimes and makes achieving full data lineage and attribution analysis impossible.

Using a concave-lens type architecture, by definition, creates operational and cost burdens and thus escalates the risks around liquidity monitoring and reporting across the board, including reputation risk. Such detrimental impacts include:

  • Difficulty in establishing truth in data
  • More spending (often duplicative and siloed) on BAU and new regulatory requirements
  • Increased complexity in cross validation and attribution processes
  • Not keeping pace with advanced technologies (AI/ML) as maintenance of legacy applications takes precedence, also resulting in staff frustration


The Convex Lens Approach – Makes Data King

Conversely, using a convex-lens type system architecture for liquidity risk management ensures synergies across regulatory mandates and across the organization. This architecture operates on a single ‘macro’ platform that optimizes the incoming data to enable coherent, consistent ‘micro’ solution components, as depicted here:

liquidity risk management: a convergent architecture

The benefits of using a convergent liquidity risk management architecture include:

  • Trusted liquidity risk data – Natively sourced data is enriched via a flexible, extensible data-dictionary for liquidity that ensures data entering all downstream applications is fit for purpose and consistent.
  • Dynamic data lineage and traceability from source to report – For example, the loans data feeding both LCR and NSFR can be easily traced to the same original source.
  • Cross report validations – The solution enables firms to validate, for example, that the high-quality liquid assets (HQLA) reported on LCR before considering the unwinding effect should reconcile with the number reported on NSFR, and/or that operational deposits should reconcile between LCR and NSFR.
  • Shared business rules – For example, the business rule for the definition of stable retail/other retail deposit that is expected to be the same for LCR and NSFR is configured once and maintained in a single place.
  • Optimized technology and maintenance costs – A single platform approach with a flexible, data dictionary architecture eliminates replication and proliferation and enables advanced technology evolution.
  • Efficient change management – A small change in an upstream system or data input is managed such that downstream impacts are visible and therefore only the delta tested, thus avoiding triggering the butterfly effect that occurs when an upstream change hits a divergent architecture.


A (Sane) Convex/Convergent Liquidity Risk Management Architecture

As depicted below, AxiomSL’s liquidity risk management ecosystem exemplifies a convex-lens type convergent architecture. The platform seamlessly ingests original-source data from wherever it exists in the organization without need of transformation, enriches it via a joint data model, and then provides consistent, traceable data to the ecosystem’s solution components.

liquidity risk management: axiomsl controllerview

Designed to break down the barriers of an organization’s silos, this converged data platform enables more “talking” which, in turn, leads to more efficient communication downstream, and superior liquidity risk management outcomes.

Back to Einstein, Good Questions, and Good Data

Traditionally, scientists have used divergent approaches to explain the universe: defining electrical, magnetic, and gravitational forces separately. In contrast, Einstein spent his entire life exploring the theory of one – one force that governs everything physical – a convergent approach. Likewise, AxiomSL’s fully managed RegCloud® – the ControllerView® platform in the cloud, mirrors Einstein’s quest for one solution. AxiomSL’s single data integrity and control platform converges different business problems pertaining to liquidity risk management into one ecosystem.

Throughout his career, Einstein made many profound observations and considered many options in his quest to explain the mysteries of the physical universe. Treasurers, liquidity risk managers, and financial technology professionals are facing tough challenges during these confusing times. They also must continuously observe, question, and reassess options. A decision made yesterday does not preclude a different approach tomorrow.

Reflecting on Einstein’s comment about the universe and human stupidity, we believe that especially when confusion reigns, thoughtful inquiry is critical – questions should always be asked – right through the liquidity lifecycle. And a simple, yet powerful optics concept like the convex lens, is remarkably useful in exploring how to effectively manage diverse data and establish (sane) liquidity risk management. That’s not infinite stupidity and makes sense in any universe!

Go ahead, ask us a question about your liquidity lifecycle today!

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