On November 13, 2014, the Federal Reserve Board (FRB) finalized liquidity reporting requirements for large US financial institutions and US operations of foreign banks (FBOs). These liquidity requirements are intended to improve the FRB’s monitoring of liquidity positions at financial institutions including FBOs that are subject to both liquidity coverage ratio (LCR) and liquidity monitor reporting requirements. Ultimately, these are oversight monitor tools used by the FRB to enhance the oversight of liquidity across financial institutions. This post describes how native visual analytics facilitates a robust liquidity monitoring and reporting processes across the enterprise.
Fundamentals of CLAR and Liquidity Monitoring Reporting
A major driver in the sustainability of any financial institution is adequate and consistent levels of liquidity within its operations. Put plainly, a glass needs to hold enough water to quench your thirst and possibly share with others. That water needs to be available over an extended time to sustain life. During the crisis in 2008, financial institutions were not lending to each other because their liquidity positions were below adequate levels. They had very little water. As a response, the Federal Reserve in 2012 launched the Comprehensive Liquidity Assessment and Review (CLAR) for both large complex financial institutions and FBOs.
CLAR is an annual quantitative and qualitative review that assess lines of business across the institution overseen by a multidisciplinary committee of liquidity experts from across the Federal Reserve. In CLAR, supervisors assess the adequacy of the bank’s liquidity positions relative to their unique risks and test the reliability of these firms’ approaches to managing liquidity risk.
The FRB also requires financial institutions to enhance Liquidity Monitoring Reporting, specifically, the FR 2052a and FR 2052b reports. These reports exemplify the heightened expectations of regulators because reporting is required on a consolidated basis and for each underlying entity over a wide range of factors. These include selected assets, liabilities, funding activities, and contingent liabilities, covering broad funding classifications by product, outstanding balance and purpose, segmented by maturity date.
The section below provides examples of specific challenges that arise from CLAR and Liquidity Monitoring Reporting along with how native visual analytics address those challenges. Native visual analytics describes the process of running business analytics engines directly on (native to) data sources and allowing subject matter experts to join and render that analysis visually and in a self serve manner. In this scenario, data is not aggregated and moved to another place for analysis so that granularity and fidelity is retained.
Key Industry Challenges of CLAR and Liquidity Monitoring Reporting
Given the increased regulatory reporting requirements placed on financial institutions around liquidity reporting, firms are faced with the challenges of continuously monitoring and measuring changes to both assets and liabilities and accurately reporting these changes on designated templates and forms. This presents multiple challenges and opportunities for solutions as provided below.
Enablement Via Native Visual Analytics Capabilities
|Fidelity of aggregated data across entities: Data from multiple business sources (Wholesale, Retail, and Commercial) and products lines (Deposits, Savings, Loans and etc.), and jurisdictions need to be aggregated up without loss of fidelity to the underlying detail.||Enable analysts with the ability to connect directly to individual data sources (lines of business, product lines, jurisdictions, etc.) so that they can run analytics at a granular level and aggregate those results up to the enterprise level. This mitigates the errors that occur during the extract, transform, and load processes required by traditional BI platforms. Data fidelity is ensured because data is not moved.|
|Dynamic governance and oversight: Internal controls need to be flexible and integrated across the organization, monitoring continuous changes within assets and liabilities so that calculating, matching, and reporting can be done in a timely and accurate manner.||Enhance the firm’s internal control framework by providing visual analytics and BI capabilities that monitor, measure, and report in real time, providing the most up to date analysis at any point of time. Dynamic governance and oversight is a vital area that regulators are increasingly reviewing and requiring financial institutions to strengthen.|
|Transparency of Capital Allocation: Stress testing increases the demand on firms to have robust liquidity systems and processes in place. Liquidity Management and Treasury operations are required to frequently monitor and assess the impact on liquidity requirements across business lines by allocating funding costs accurately.||The capabilities described above, together, enable transparency and enterprise wide visibility. Analytics can be run directly on the disparate data sources and types that make up a typical banking organization. Native visual analytics provides the capability to juxtapose real-time and historical analysis at a granular level and across functions on one data application. This helps to centralize both the capital allocation and data transparency processes|
Native visual analytics unifies data discovery, business intelligence, and real-time visualization in a single, integrated platform. It provides users with direct access to big data (it runs natively on Hadoop clusters to leverage its capabilities) through an intuitive and self-service interface. Referring to the examples above, a team can explore billions of rows of highly varied data, join views into interactive packages, and share that package with relevant colleagues to solve problems in a timely, secure, and collaborative way.
 PwC: Ten key points from the Fed’s finalized liquidity reporting requirements
 Federal Reserve Bank of San Francisco: How is Banking Safer Following the Financial Crisis