Five Best Practices for Capital and Liquidity Risk Management

Over the last few decades, risk management in banking institutions has evolved significantly, driven by regulatory changes, technological advancements, and lessons learned from periods of financial instability. With each regulatory update or technological innovation, a fresh set of guidelines and frameworks have emerged to help banks maintain compliance. 

Amid the wealth of information from conferences, dialogues, webinars, the media, or annual reports, the message is clear: banks must stay knowledgeable on and adapt to evolving regulations in capital and liquidity risk management. Multiple perspectives and frameworks claim to offer the best solutions, each purporting to be the best path forward.

This article takes a use-case driven approach to best practices, offering suggestions for each scenario. By identifying the primary use cases and aligning them with the fundamental objectives of capital and liquidity risk management, it's possible to distill the wealth of information available into a few key principles.

The most successful capital and liquidity risk management frameworks are built on these five best practices.

• 1.Integrated Risk Management Systems
• 2.Capital Stress Testing and Planning
• 3.Data Management and Technology Integration
• 4.Monitoring and Compliance
• 5.Training and Development

1. Integrated risk management systems

A holistic approach to capital and liquidity risk management systems can help banks align their business across a number of different departments, as well as meet regulatory requirements at scale, ensuring long-term adaptability and resilience.

There are many ways to think about risk management and improving collaboration, all of them optimizing across the 'classic 3': people, process, and technology. For example, Deloitte’s approach to integrated risk management breaks governance into seven components called the "governance wheel", where they state that "...while the extent and emphasis will vary, the elements of this governance wheel will be found in most organizations."¹

McKinsey breaks it down slightly different, suggesting that banks "...focus on four mutually reinforcing areas: organization, governance, processes, and digitization and advanced analytics."²

Ultimately, the components across the various frameworks can be categorized into a few areas: robust governance, organizational alignment, information sharing, and quality assurance.

Learn more: Capital & Liquidity Management: Risk, Regulation, and Technology

2. Capital stress testing and planning

Conducting regular stress tests across different scenarios — base case, severe adverse, and reverse stress — is vital. These tests support the development of a robust capital plan that ensures banks are prepared for adverse market conditions, aligns with their strategic planning, and complements its risk appetite.

Stress testing provides banks with increased transparency into their liquidity risk exposure to improve contingency plans. This can include diversifying funding sources, maintaining sufficient levels of high-quality liquid assets, and establishing a well-functioning liquidity risk management framework.

Treasury and financial resource management (FRM), in collaboration with data and technology teams, have an opportunity to capitalize on the growing availability of data sources in the industry. By leveraging these resources, they can broaden the scope of scenario analysis while increasing its depth and precision. By refocusing on strategic planning, the bank can now enable more sophisticated models, improving the overall financial stability of the firm.

3. Data management and technology integration

Investing in technology to manage complex balance sheets and products is crucial for success. Ensuring data integrity and lineage for regulatory reporting and internal risk assessments is a key component of this practice. By leveraging technology, banks can capture and optimize risk data, fulfilling regulatory requirements efficiently.

The treasury and FRM duo holds a central role in ensuring the success of any integrated data management strategy. To achieve this, both teams must maintain strong connections and close collaboration with risk management, liquidity, capital, and interest rate risk. Comprehensive information sharing provides the most efficient and scalable approach to meeting each team's specific requirements. Centralized sources of information, self-serviceable access to data, and configurable collaboration tools are the essential foundation in a bottom-up approach to integrated risk management.

Banks should embrace a holistic approach to data management and technology integration to strengthen their capital and liquidity risk management. This involves not only investing in advanced analytics and integrated risk management systems but also establishing a robust data governance framework. This framework should include clear policies on data usage, storage, and access, as well as educational programs to raise awareness about data governance principles. Defining clear roles for data stewardship and cataloging data assets and metadata are crucial steps in fortifying data integrity and effective risk management.

Technological tools like data management platforms, lineage tools, and advanced analytics are vital for shifting from reactive to proactive and predictive decision-making strategies. These tools support the centralization of data sources, which facilitate cross-business line integration and leverage cloud computing for enhanced analytics and artificial intelligence applications. Moreover, fostering a data-driven culture and adhering to data protection regulations across regions are essential for compliance and improve decision-making processes in capital and liquidity risk management.

4. Monitoring and compliance

Compliance checks within a banking institution span a variety of domains, each with their own unique protocols. In an era where data-driven operations are advantageous for competitive edge and innovation, centralized data sources have become prominent. Data fabrics reflect this approach, creating a user-friendly layer to interact with data that was sourced from multiple domains.

One unintended consequence of a legacy data warehouse is that the repercussions of flawed data are multiplied with every point of egress. Unchecked, this could jeopardize regulatory compliance efforts across the organization. The quality of this data is therefore paramount, and any data fabric must be built with this focus. Meticulous data checks should be domain-specific, configurable as needed, and contain a multi-layer structure where quality assurance takes place each time the data is handled.

Ongoing reviews, audits, and trend analyses are necessary for maintaining compliance and refining contingency planning over time. Continuous monitoring of metrics including liquidity coverage ratios and net stable funding ratios keeps teams informed in real-time, allowing them to adapt as necessary. It also drives root-cause analysis, ultimately enhancing the bank's overall data quality. The most effective teams benefit from access to historical data, bi-temporal audits that monitor changes across both knowledge and effective date timeframes, and self-service reporting capabilities that enable real-time adjustments to analysis methodologies.

5. Training and development

Establishing a culture of risk awareness and accountability is fundamental to the success of any program. Providing ongoing training across all tiers of risk management helps organizations adapt to evolving regulatory and market dynamics. This can include providing access to industry specific conferences and workshops, as well as encouraging cross-functional training and collaboration. By continuously investing in the knowledge and skills of team members, organizations can ensure that their risk management team is equipped to handle any challenges that may arise in the future. Additionally, promoting a culture of learning and development can also foster a sense of ownership.

A common pitfall to avoid when structuring these programs is training teams in silos, without exposure to or communication with other groups that may have related responsibilities. The silos can lead to inefficiencies and quickly become an obstacle to even the most robust capital and liquidity risk management strategies.

By embracing the reoccurring theme of "integrative practice", this approach to team and company development makes sure that all employees are equipped with the knowledge and skills needed to manage capital and liquidity risks effectively.

Conclusion

The evolution of risk management in banking institutions has been driven by various factors such as regulatory changes, technological advancements, and lessons learned from past financial crises. With the vast amount of information available, banks must understand the breadth, synergies, and limitations of each component suggested in each capital risk framework. This understanding can help banks create their own approach to their next iteration of capital and liquidity risk management standards.

Implementing these practices effectively and timely can help banks align their business, improve collaboration, and verify data integrity — ultimately leading to effective risk management and compliance. By following these principles, banks can mitigate risks and establish a strong foundation for their financial health and success.

In today's volatile market and ever-evolving regulatory landscape, managing Interest Rate Risk in the Banking Book (IRRBB) is more critical than ever. Are you equipped to ensure your bank's compliance and operational effectiveness?