Planning, Preparing, and Practicing for the Unexpected
In a liquidity crisis, the importance and robustness of the CFP's design needs to be matched by the institution's ability to execute the playbook. Its people need to understand their roles and responsibilities under the streamlined command structure and its communication protocols so they can implement the steps needed to prepare for and manage the liquidity crisis.
The effectiveness in executing the CFP is further enhanced through periodic testing. While not all components/strategies of the CFP may be tested, leading institutions that perform frequent exercises which best simulate the potential liquidity crisis environment will improve the CFP's operational effectiveness and response times – aspects that are critical during a crisis. Further, the test simulations may also identify potential gaps and/or improvement opportunities that would otherwise be undetected if the CFP were left collecting dust on the bookshelf.
Liquidity Risk Management Information Systems
Enhance Ownership and Accountability of Liquidity Risk Data
As regulatory reporting requirements have increased over the past several years, institutions have been challenged to keep pace with the ever-growing regulatory requirements for additional and more granular information. In stretching to meet pending regulatory deadlines while simultaneously juggling the needs to manage the ever-increasing portfolio of systems and applications, institutions have had little time to develop and implement a holistic approach to the management of liquidity data. Consequently, this has resulted in data quality challenges, including incomplete or duplicated data, variations in reported results due to the use of multiple data sources, and increased manual and time-consuming efforts in reconciling and enriching information needed for reporting across the different parts of the enterprise.
Recognizing such challenges, leading institutions have often designated risk data “czars” to lead and coordinate data management practices across the enterprise, and spanning the risk data management lifecycle – including data capture, enrichment, quality maintenance, analytics, reporting, and archiving.
Manage Liquidity Data Comprehensively: From End-to-End and Top-to-Bottom
Institutions leading the charge to improve their liquidity risk management capabilities have invested significantly in developing a comprehensive view of liquidity information, improved data quality, and “data lineage” as information is captured, enriched, analyzed, and reported.
Leading institutions have undertaken a spectrum of initiatives along the following focus areas:
i. Integration of risk, asset liability management, funds transfer pricing, transaction processing, and forecasting systems to enable more comprehensive data sets and shared common analytic engines/modules (e.g., trade capture systems, collateral management systems, G/L and financial systems)
ii. Standardization of liquidity data definitions and attributes through improved reference and position data collection (e.g., detailed features of product and asset class characteristics, contractual maturities of existing positions, overlay of behavioral assumptions), regulatory reporting classifications, and other segmentations (e.g., holding company, lines of business, legal entities/jurisdictions)
iii. Development of integrated analytics and reporting suites for multiple purposes (e.g., CFP dashboard metrics and thresholds, resolution planning, strategic planning and forecasting)
Develop a Vision and Continue to Build on a Scalable and Flexible Liquidity Risk Architecture
As institutions continue to enhance their liquidity risk architecture and platform(s), they should remain mindful of the interconnections between liquidity risk systems and applications, ensuring that IT initiatives at the enterprise level and at other parts of the organization properly consider potential implications and considerations for liquidity risk as part of their planning and scoping exercises.
In this context, leading institutions demonstrate strong capabilities in several areas. First, they have a strong understanding of the information technology, systems, and data “blueprint” – both the current and the future state design, along with detailed phased implementation and change management strategies and plans. Second, there is an executive owner, such as the chief information officer or a risk data czar, who provides oversight and drives coordination, ensuring a comprehensive view of liquidity risk data and how such information is used across the enterprise. Finally, there is a strong business case and well-defined requirements for IT investments, coupled with the support and buy-in from senior management.
Recovery and Resolution Planning
Embed Liquidity Needs for Resolution Planning into BAU Liquidity Reserves
Resolution planning requires firms to identify and measure the liquidity necessary to resolve the firm in an orderly manner. Leading institutions use the liquidity estimates at the firm-wide and legal entity levels that are produced for resolution planning to assess the size of the liquidity reserves they will maintain to support liquidity risk strategies, both over the course of BAU activities as well as in recovery and resolution circumstances.
These firms model liquidity needs for their resolution strategies on a daily basis and adjust the size of their BAU liquidity base to ensure sufficient liquidity resources needed under recovery and/or resolution. They also set limits by using their resolution liquidity estimates and develop associated response actions, bringing them to the forefront of integrating resolution planning considerations into their liquidity risk management architecture.
Integrate LST and Contingency Funding Planning into the Resolution Plan
In developing a resolution plan and addressing the resulting liquidity impact, institutions should make assumptions concerning sources and uses of funding, including deposit runoffs, drawdowns on outstanding lines of commitment, and additional collateral demands. As part of this exercise, many institutions leverage the assumptions in their liquidity stress testing and/or contingency funding plans to forecast the aggregate amount of net liquidity needed to support their resolution strategies. Leveraging existing liquidity risk management and forecasting tools in this manner is similar to the approach originally prescribed by the regulators of estimating required liquidity under the Liquidity Coverage Ratio (LCR).
Leading institutions are taking additional steps to further embed their own internal liquidity risk management tools into resolution planning by forecasting liquidity at set intervals (e.g., daily, weekly, monthly, and quarterly) throughout the resolution planning horizon. These projections better identify potential liquidity and funding mismatches that might not be readily apparent when strictly analyzing point-in-time, aggregate liquidity requirements.
Understand Liquidity Traps and Frictions to Cash Transfer
U.S. regulators require covered institutions to identify potential liquidity traps in their resolution plans. Traditionally, most firms have provided only commentary with respect to legal entities and national jurisdictions in which liquidity could be trapped but have not fully factored these impacts into their liquidity models and forecasts.
Leading institutions have advanced this analysis by estimating the potential amount of trapped liquidity, along with other potential frictions to the transfer of liquidity among entities, and included this impact in their resolution plan liquidity forecasts. They have also developed liquidity risk triggers and response actions to ensure that entities with national or jurisdictional liquidity requirements will have adequate funding under different stress scenarios and environments.
Optimizing Business Practices
Strategic and Tactical Implications of the New Requirements
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