The need for banks to properly recognise liquidity as a scarce resource was highlighted by the bankruptcy and collapse of Lehman Brothers in 2008. This crisis was due largely to the firm’s risky investments in the sub-prime mortgage market, with the institution finding that it did not have the reserves to pay its creditors when liquidity tightened. Since then, banks’ liquidity arrangements have come under increasing scrutiny and regulatory pressure, as market reforms aim to bulwark the financial industry against another liquidity shock.
The Basel III capital adequacy regime introduced regulations to increase banks’ capital reserves and manage their liquidity risk positions. These were extended in January 2013 when the Basel Committee on Banking Supervision (BCBS) discussed two mandatory components to tackling liquidity risk, namely the liquidity coverage ratio (LCR) and the net stable funding ratio (NSFR). Intraday liquidity indicators are set to be tackled in the new regulation proposal.
The new components being introduced in the CPSS consultation paper aim to monitor a bank’s liquidity requirements using several indicators. These are designed to monitor a range of activities, such as a bank’s usage of – and requirement for – intraday liquidity both in normal times and in times of stress, as well as the intraday liquidity available to banks on a daily basis. To comply with the new regulations, financial institutions (FIs) will need to start strictly measuring their daily maximum intraday liquidity usage, available intraday liquidity at the start of the business day, total payments settled and received, and the timing of intraday settlements using a much more granular style of reporting.
The new emphasis on intraday liquidity monitoring raises some weighty operational and reporting challenges for FIs. A question mark will rest over how efficiently, and in what time frame, they can feasibly absorb the regulatory changes. To this end, compliance officers and IT teams will need to harness approaches initially designed for financial firms to manage the increasing data management demands of reporting intraday on liquidity.
There are a number of scenarios which will require immediate attention from a reporting perspective come 2015.
Should a regulator request ad-hoc reports on liquidity risk positions, firms will need to produce their reports ‘on the fly’. Firms never know in advance what information will be asked of them and how complex the question will be. The challenge, therefore, is how to respond to unplanned demands in a timely fashion.
Liquidity reports will now need a much greater level of granular detail than previously required. Ratio breakdowns need to be constructed according to multiple criteria, such as counterparty, currency, maturity level and legal entity. These criteria demonstrate the multi-dimensional nature of liquidity reporting and the increasing volume of data that need to be manipulated to reach the level of detail that is expected.
The reporting aspect of the CPSS regulations is intended to act as a monitoring mechanism for FIs and regulators to alleviate the risk of a new liquidity shock. To this end, FIs will be asked to demonstrate that their liquidity holdings are sufficient to cover a major crisis in real time. Creating scenarios to test their resilience against major funding events, such as unexpected downgrades of assets to an illiquid status, will demonstrate to a firm how their liquidity risk strategy is working in real time. To execute this, a bank will have to analyse multiple cash flow scenarios on the fly and repeat the exercise, adding and subtracting data to simulate real world conditions.
As data demands get more onerous, firms with inefficient technological systems will have to expand the reporting and monitoring teams to keep on top of the requirements. The extra cost of these team members is a burden on the company, one that can be alleviated by capital expenditure (capex) investment in a modern and, more importantly, scalable data analytics architecture.
The Current Analytics Issue
The new intraday reforms mean many, if not all, liquidity reporting structures will need to be revised over the next year to ensure compliance. Historically, banks have relied on traditional relational databases that do not perform at a level sufficient to satisfy new reporting and monitoring requirements. The first reason is that all data must be pre-aggregated before it can be consumed into the reporting environment, which de facto excludes the possibility of flexible analytics. If business users want to analyse liquidity using classifications that have not been previously configured in the report – for example look at the LCR breakdown by another legal structure – they need to wait for the IT database team to entirely rewrite the report.
Adding further information into a traditional relational database is itself a challenge. A relational database simply cannot hold more than a handful of criteria in its structure, which prevents users from grouping and filtering the data based on the analysis axes that are relevant during query time. A top count type query to find the answer to a question such as ‘Who are the top 10 counterparties that represent 80% of the bank’s funding structure?’ might appear a basic question. In reality it is rendered extremely slow with a traditional relational database, if not impossible to complete, when records of hundreds of thousands of counterparties must be scanned against multiple criteria.
Solving this challenge will require an ad-hoc reporting mechanism that operates on the fly, without restraint.
High Performance Analytics
Critics of intraday liquidity reporting have highlighted the manifold increase in the amount of data-points to be measured and analysed to comply with these new requirements. To manage the regulations effectively will require a highly competent data management system and, as highlighted above, current standards are not going to provide a proper data analytics framework for the future.
A more flexible technological solution to the challenges presented by the CPSS regulations is to use an in-memory analytics database. This type of database stores large volumes of data in a computer’s accessible memory, rather than on a storage-based hard drive, which represents significant gains in processing time. All data is processed in memory, which eliminates the need for pre-aggregation. As a result, any scenario can be generated at query time and delivered in a split-second.
The most advanced multidimensional analytics databases deliver real-time calculation and aggregation of large volumes of data. They allow on the fly report generation and enable trend analysis as well as the capacity to instantly add and subtract different filtering criteria. This is invaluable considering the multidimensional nature of liquidity monitoring reporting and the need for liquidity specialists to analyse data following their ‘train of thought’. Most importantly for those keeping an eye on both the IT and the risk management department budgets, it negates the need to hire extra personnel to manage the extra data analysis and reporting demands the new regulations create.
Use Your Time Wisely
January 2015 marks the start of the monitoring of intraday liquidity. Now is the time to properly assess future reporting needs versus current capabilities and invest in the right technology for the future. Those FIs lagging behind when the new reporting requirements come into force will find themselves overspending and overworking their staff when new technology advances can now prevent this. Rigid and incomplete liquidity reporting in an ‘on demand’ world is going to be a drain on resources – one that no department head wants to see.
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This year promises to further the regulatory compliance burden imposed on financial institutions. How are firms in the sector responding to the challenge?