Liquidity serves as the lifeblood of financial institutions. Coming as an immediate priority, even before any risk measurement, it simply captures the ability for the balance sheet to be operated at a reasonable cost.
Amid ongoing global challenges, such as inflation, rising interest rates, and new regulatory requirements, the task of identifying and effectively utilizing liquidity has become a top computational challenge demanding ongoing real-time monitoring from risk managers. To remain trustworthy to communities of customers exchanging information instantly, banks need to demonstrate their adherence to capital reserve and reporting guardrails.
The management of liquidity dynamics is now closely intertwined with reputational risk, impacting all other risk categories. To address this, management strategies must be backed by transparent analytical lineages that can accurately model market stress situations and forecast outcomes. Furthermore, these strategies should actively monitor events that surpass pessimistic expectations, enabling timely identification of business opportunities. This proactive approach not only mitigates risks in a timely manner but also yields returns on investments in new technology.
Fortunately, banks now have access to a new generation of operational intelligence technology, capable of uncovering hidden sources of liquidity within existing portfolios and between consecutive reporting exercises. With a deeper and instant understanding of portfolio projection data from various sources, decision-makers can confidently and swiftly manage emerging risks and seize opportunities that arise.
Defining Current Market Dynamics
In the past, liquidity risk was managed with a time lag of T+2 and T+1, relying on moderate volatility assumptions within 30-day time frames, considering cyclical trends. Banking and treasury operations, which operated on a timeframe of days, were adequate to maintain liquidity levels in line with regulatory and risk management requirements.
However, inflation and interest rate hikes have made today’s margins far tighter, and reporting requirements need to achieve customers’ trust as well as compliance. As a result, banks can no longer afford any time lag in their monitor, and a 30-day survival horizon may not capture the catastrophic runoffs we have recently observed.
All of these pressures have driven the financial industry to pursue solutions that operate with increasing precision over rapidly-diminishing time intervals, and these new technologies have made it possible to access new sources of liquidity that had previously gone unnoticed.
Where New Liquidity Hides
Platforms that incorporate real-time data streams and interrogate pre-aggregated data stacks in-memory at near-instantaneous speeds provide users with unprecedented insights.
In the past, when firms analyzed their positions on a daily basis, they were unable to tap into resources that arrived early or identify delayed sources of liquidity. However, with today’s technology, it becomes possible to generate comprehensive, of-the-moment reports on all assets, instantly revealing these sources of liquidity, ready to be used as collateral. Institutions equipped with the necessary data infrastructure to identify them, the analytical capabilities to assess them, and the operational intelligence to leverage them gain a significant competitive advantage.
Computational Timeliness: the New Financial Virtue
Armed with these new insights, all that remains to unlock these new liquidity sources is the ability to operate quickly enough to equip decision makers with reliable and accurate information to act before the window of opportunity closes. In this climate, the value and analytical strength of a system is not merely a measure of its computational capacity, but also its computational timeliness.
Existing systems and data architecture processing T+1 or T+2 data may prove insufficient to support a competitive operational intelligence practice. Institutions identifying opportunities supported by comprehensive and transparent reporting, modeling, and stress testing capabilities will stay ahead. To achieve this going forward, computational timeliness will be a defining factor.
Atoti, developed by ActiveViam, is a data analysis platform that serves as a universal semantic layer between users and data. Seamlessly integrating with existing infrastructure, it provides instant insights, revealing r hidden liquidity. Its state-of-the-art architecture delivers an unprecedented end-to-end real-time push that empowers financial institutions with the computational intensity and operational intelligence they need to make the right decisions precisely when they are needed.
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