Employing new technology, such as a bank-wide liquidity management system, will help banks identify and deal with poor quality assets.

Given the current economic crisis, the question of how to improve the management of liquidity risk¹ has become a major focus for financial institutions.

Recent developments in technology have influenced the way banks manage their future risk. Some banks are proactively using technology to keep them ahead of recent challenges, while most find themselves frantically reacting to the prevailing circumstances.

This is not to say that technology alone is the answer, nor to suggest that those banks that were more advanced in their efforts necessarily fared better. However, there are lessons to be learned by looking at the state of liquidity management and liquidity risk - understanding what has gone right, what has gone wrong, and how a multitude of challenges, some of them technical, might be better addressed moving forward.

Current Trends in Operational Liquidity Risk

Liquidity, a secondary risk, is closely linked to credit, market, and operational risks that have been the primary focus of regulators in recent years. As a result, liquidity and liquidity risk management have been subject to an inadequate level of governance, both internal and external. Clearly, liquidity management is a vitally important function that banks and other players in the financial markets have recently overlooked. It is equally clear that new capital adequacy requirements do not facilitate the proper management of liquidity and liquidity risk, nor do they support managers and regulators in the measurement and control of liquidity risk.

Given these conditions, a new set of rules for the management of liquidity risk will likely emerge, requiring new technology that enables more flexible, adaptive, and comprehensive analysis of risk in volatile and uncertain markets.

Technology and Liquidity Risk

As it relates to managing risk on a holistic basis, technology can play an important role with benefits in four key areas:

The latter was seldom the driver for a bank's enterprise liquidity risk initiative in the past, but it is certainly in the forefront today. Liquidity was a neglected backwater of risk management in many banks. Credit and market risk models often made sweeping assumptions about the availability of liquidity. In August 2007, much of that changed. The commercial paper market disappeared overnight, interbank lending in London froze, and banks realised that the models used for liquidity stress testing failed to contemplate the reality of what was suddenly being experienced. Moreover, the systemic nature of the problem became obvious. It wasn't enough for a single bank to have a detailed view of their liquidity at a given point in time if all banks did not. If you were borrowing and knew your exact positions, but the lender, at 10 minutes before close, didn't understand their positions, fear of the market would take over and lending would stop. And so it did.

Pioneers in managing liquidity on a predictive, intraday basis aggregated their flows across the bank and knew at any point where they were and where they would be. They knew what was supposed to be there yet wasn't and what wasn't supposed to be there but was. Yet without all banks understanding their liquidity point of view at any given time, even the most sophisticated of banks were reduced to the least common denominator of those around them.

The pioneers using technology have followed managing intraday, predictive liquidity management over the years. The challenges that have been addressed are:

• Absorbing, normalising, aggregating, and analysing cash flows across the entirety of the bank.
• Optimising those flows based on bank priorities - from payment flow control to modelling the behaviour of flows over time for better predictive capabilities.
• Extending the definition and scope of liquidity to all liquid assets.
• Monitoring and modelling those assets in the context of the bank's overall liquidity picture.

Since August 2007, people have begun to re-think the approach to liquidity stress testing and liquidity risk in general. It is clear that banks were widely disappointed with the models in the past, and there has been much discussion of ways to improve confidence in the models and the flexibility and adaptability of the prevailing approach to managing liquidity risk.

One such approach has been to use operational data within the bank, such as the type of information contained in a bank-wide liquidity management system, to supplement the balance sheet information that had traditionally been the basis of the risk analysis. The thinking is that using actual 'live' data within the system in conjunction with the latest balance sheet could provide a much more accurate view of the bank at a given time and the models could draw far much more reliable information and yield better results.

Beyond managing risk, a bank-wide liquidity management system can also provide insight into customer behaviour and suggest more servicing opportunities, such as:

• Giving the funding desk a single consolidated view across all flows, for troubleshooting customer problems.
• Gaining insight into who, internally or externally, is using the bank's liquidity and how they are using it.

Another key benefit is to allow banks to optimise their central bank account balances in conjunction with how they manage liquidity risk. Without a confident understanding of the bank's positions, many banks over-fund at the central bank in order to ensure that payments are made. This 'big buffer' approach may provide comfort, but it comes at a cost that is directly related to the bank's bottom line.

Last, and perhaps incredibly relevant to the current environment, is that deploying a system that manages bank-wide liquidity can reduce cost, primarily in terms of people. The direct benefit is to reduce the number of people required in the mid-office to track liquidity. The method of choice in many banks is to employ a hoard of people who spend most of their day transposing spreadsheets to track the bank's positions. This is not only inefficient and prone to error, it is costly. So, a reduction in headcount would be part of the bank's hard-dollar (sterling or euro) justification for deploying a bank-wide liquidity management system.

More subtle, but no less important, is the system enables the bank to scale. As we discussed at the beginning of this article, volume and complexity are up. Banks that manage liquidity with people in the mid-office need more and more people as the volumes rise. That doesn't scale. Many banks saw this in spades in August of 2007 and certainly again in the fall of 2008. A system that manages bank-wide liquidity can allow a bank to manage these flows and adapt to dramatic increases in volumes without deploying additional people - or hitting the wall because they can't.

In the end, though, managing liquidity on a bank-wide basis won't improve the quality of an underlying asset. A bad collateralised debt obligation (CDO) doesn't become a better asset because you deployed a bank-wide liquidity management system. But you may be able to deal with it and the world around you better - and faster - as a result.

Article by Tony White serves as managing director of product and research & development at Wall Street Systems, focusing primarily on the development of progressive solutions to today's business challenges. He has been with the company since 1993. Before becoming head of development, White's other roles included back office product manager, software engineer and consultant for major client installations at Deutsche Bank and British Petroleum. During his time at Wall Street Systems, White has also established a research & development laboratory at the company's London offices. Prior to joining Wall Street Systems, White worked at Manufacturers Hanover Trust (now part of JPMorgan Chase) in a development role for trading systems for fed funds and exchange traded derivatives

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