As the effect of geopolitical events, inflation, and rise in interest rates are becoming the new norm, the immediacy of communications across communities of customers is creating a sense of urgency in the banking industry to reach beyond current risk management and controls. As the recent collapse of mid-size institutions has shown, in the US, a failure to anticipate liquidity can immediately trigger a reputation risk.
As a result, positions accounted for as held-to-maturity may become available for sale overnight, at a significant discount, jeopardizing the integrity of the institution as a whole. In this context, liquidity is no longer a T+2 or T+1 risk to manage. It has become a same-day stress situation that risk officers need to actively monitor.
This new reality impacts all aspects of liquidity analytics across treasury and banking books’ operation and compliance, empowering front office, treasury, risk, and finance teams alike with timely and operational intelligence they need to track actual liquidity usage against the last forecast, allowing users to change the projections assumptions on the fly to identify additional stress and corrective actions.
Understanding the Current Environment
Rising interest rates, inflation, and new FRTB regulations are all working in conjunction to drive analytical demands to increasingly shorter timeframes. From a risk management standpoint, they are presenting two broad challenges to the industry.
In contrast to the previous era of strategic thinking, a survival horizon of 30 days seems like a long term. As catastrophic run-offs are now part of the observable landscape, risk managers can no longer assume retail and SME deposits display only moderate volatility around a cyclical trend. The banking book has now an immediate effect on treasury and needs to be forecasted continuously.
Because Basel liquidity requirements are now well in place, treasury teams need to actively monitor the possibly severe impacts on their forecast, liquidity coverage, and net stable funding as a way to hedge the related compliance risks. These demands have significantly increased the computational intensity necessary to meet reporting requirements, manage reserves, and instill customers with institutional confidence.
The Importance of Computational Timeliness
In this context, capital reserves are only addressing long term stability, while the current environment escalates the need to monitor liquidity margins closely.
As any calculation performed on outdated inputs bears the potential for a balance sheet collapse, the ability to analyze and react quickly to new information has become critical. At a time where most risk management solutions emphasize improving accuracy, the problem has now become one of computational timeliness.
As recent discussions with our peers indicate, institutions are now moving to adopt contemporary technologies to get instant insights on market conditions and reach beyond compliance—the goal of operational efficiency.
The benefit is clear: insofar as risks are well managed, treasurers can also identify new opportunities. A cash flow received earlier than expected no longer goes to waste. As liquid assets become available, even for a short period of time, they immediately go back to the inventory of the collateral management system and serve as high quality pledges in credit support agreements.
Computational timeliness is equally important for managing emerging risk and compliance scenarios. Assets remaining unencumbered longer than expected may unbalance forecasts, and the ability to have instant visibility unto the real-time state of the books provides managers with a powerful tool for making critical and consequential decisions rapidly.
Addressing the Liquidity Challenge
Banks generally deploy state-of-the-art analytical systems to meet their end-of-month reporting requirement. This exercise typically assumes a moderate mid-term volatility around a cyclical trend. However, in this new environment, they need to augment their capabilities with solutions that deliver the computational timeliness and operational intelligence required to deliver insights in real time.
To achieve this, treasury, risk and finance teams would ideally leverage a solution integrating as a simple add-on to existing architecture. In effect, this is where in-memory analytical capabilities can change the game. By loading all analytics from risk and performance forecasting systems and combining it with current treasury data, they offer the required flexibility to account for foreseeable shocks and events and deliver instant answers. Providing heads-up on compliance ratios, they help identify and handle risks as they arise, and also immediately identify business opportunities.
The Future of Liquidity
Today’s unique liquidity pressures will continue to affect risk and compliance analytics for the near future, and banks will increasingly need to differentiate themselves using technology to support their operational intelligence framework and computational timeliness.