Attitudes toward liquidity risk have changed

Going beyond Basel III compliance toward better ROI

By Ravi Chari, Director of Regulatory Risk Solutions, SAS

Prior to the financial crisis, most banks took for granted that they would always have access to liquidity, and so they didn’t worry too much about liquidity risk. Even regulators didn’t worry much about liquidity risk – until liquidity was exposed as a contributing factor in what many label as the worst financial crisis of the 21st century.

The media has moved on to other issues, but regulators and financial institutions are still hard at work to prevent another crisis from happening in the future. Their attitudes toward liquidity risk management have changed: They want banks to view liquidity risk strategically – similar to credit and market risk.

Banks can also use this investment to simultaneously bolster their risk management systems, realizing business benefits from regulatory compliance.

For example, in 2008, the Basel Committee on Banking Supervision published its Principles for Sound Liquidity Risk Management and Supervision. This has led to banks investing heavily in systems and processes to ensure that they have a timely, accurate picture of their liquidity risk and position intraday, and over a longer period, across the entire institution.

SAS looked at the key areas banks should be considering with the liquidity risk optimization challenges they face today. To effectively manage their liquidity risk, banks will need the right strategy, solutions architecture and IT systems, and governance in place to manage this process. Banks can also use this investment to simultaneously bolster their risk management systems, realizing business benefits from regulatory compliance. 

Read the full report: Liquidity Optimization: Going a Step Beyond Basel III Compliance.

Rather than short fixes, banks need to look for a long-term strategic solution across three areas:

  • Data integration.
  • Computing capabilities.
  • Interactive monitoring and reporting.

Data integration

Enterprise-level liquidity risk optimization requires an integrated risk management system that consolidates various data sources and related models across both the asset and liability side of a bank’s balance sheet.

  • Being able to effectively integrate data is even more important for banks with global operations and investments, as they need to achieve risk aggregation and consolidation across different currencies, local rules, time zones and more.
  • An integrated risk management system facilitates interaction between finance and risk, giving you a complete picture of risk drivers and capital determination.
  • A unified data management platform with embedded data quality functions and common metadata for data management and analytics provides a single version of truth.

Computing capabilities

To generate reliable optimization results that allow for future liquidity and growth, you need to use simulated future cash flows and market states across multiple time horizons. This requires a high-performance risk engine that ensures timely and uninterrupted completion of the optimization process.

Many banks are expected to stress-test their liquidity risk and position under various adverse scenarios. If your bank isn’t adequately equipped with high-performance computing capabilities, it will struggle to:

  • Identify potential liquidity issues and investment options.
  • Validate procedures to monitor compliance with supervisory directives and internal policies.
  • Implement effective internal controls and review for liquidity and funding management.

Interactive monitoring and reporting

Liquidity management and asset allocation activities require banks to have an enhanced, continuous monitoring and reporting system. This is necessary to track liquidity positions and compliance, as well as to generate investment scenarios and funding plans.

For instance, imagine that your bank wants to monitor and manage regulatory liquidity ratios, funding gaps, risk concentration, optimization of capital allocation and efficiency on a daily or monthly basis, based on its business and risk strategies. To do this effectively, you need a way to extract the right information from large amounts of data and various analytical results. This typically involves using automated ETL and reporting systems that provide high levels of speed, transparency and flexibility. When banks lack such systems, they spend a great deal of time and manual resources pulling data from multiple places and systems – only to generate static reports that are quickly out of date.

Changing business dynamics and regulations have created critical challenges for banks seeking to stay profitable while meeting liquidity requirements. Nevertheless, many firms view liquidity risk management as not only a regulatory compliance issue, but also an opportunity to find business value.

Our white paper, Liquidity Optimization: Going a Step Beyond Basel III, offers insights and recommended approaches that you’ll find valuable as you work to improve your systems and processes and deliver actual ROI from liquidity risk management.

Ravi Chari’s areas of expertise are credit risk, liquidity risk, ALM, market risk, data management, capital management, data management and stress testing. He often speaks on topics of risk, regulation and governance at industry and regulatory forums sponsored by such organizations as GARP, RMA and PRMIA. He is an author of white papers, research reports and articles on banking, financial risk management, stress testing and Basel II, and holds a Master’s in Technology from the Indian Institute of Technology (IIT) and a FRM from the Global Association of Risk Professionals (GARP).

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