Within the last 15 years, regulatory bodies such as the Federal Reserve Board (FRB) and Office of the Comptroller of the Currency (OCC) have developed standards that financial institutions must follow to classify as models, tools used to project critical or material information. This information may include losses, value at risk (VaR), liquidity needs, valuations, etc. The foundation of these standards is supervisory letter SR 11-7: Guidance on Model Risk Management and OCC 11-12: Sound Practices for Model Risk Management.
There have also been many subsequent supervisory letters or rulemakings to address data quality, e.g., CFO Attestation, BCBS 239, etc., controls, infrastructure, and scenario design, that provide input to these models. What these standards attempt to accomplish is to ensure any tool used to quantify information critical to decision making follows a standard protocol for development rigor, governance, and validation. While these standards have been adopted for use in Comprehensive Capital Analysis and Review (CCAR), business as usual (BAU) capital planning, and general risk management, there are some areas where financial institutions may need to invest to meet the next wave of supervisory expectations.
The Need for Improved Recovery & Resolution Plan Capabilities
With the new Insured Depository Institution (IDI) Resolution Plan rule proposed by the Federal Deposit Insurance Corporation (FDIC), there are many questions in the industry regarding the level of sophistication, flexibility, and dynamism required of models and other supporting infrastructure and processes. These questions are more than justified, given the recent focus of examiners on the ability of financial institutions to produce a credible resolution liquidity execution need (RLEN) forecast within a few days when given a specific set of inputs. This is just one example where regulators have stepped up their expectations regarding testing and scrutiny of financial institutions’ resolution on critical infrastructure with an emphasis on speed.
Another example within the recovery and resolution planning (RRP) space is the potential carve up of valuable franchise components to accommodate a multi-buyer resolution strategy for Group A financial institutions, as defined in the proposed IDI Resolution Plan rule. Many IDIs still employ a single-buyer resolution strategy, which assumes their entire organization is bought in a single transaction. As a result, their technology likely does not have the capability, for example, to carve up their deposit franchise or a portion thereof for a quick sale to another financial institution only interested in a particular region or business segment. However, according to the proposed rule, any organization greater than $100 billion must have the capability to carve up its organization by franchise component to accommodate a multi-buyer marketing strategy. In addition, the capability to quickly value these franchises, and show the FDIC that the methodology for breaking up the organization achieves the objective of maximizing value, is no small task when considering the expectation may be that this information be produced over a very short period (such as a resolution weekend).
Adhering to data quality standards and having the ability to produce data on a timely basis is a basic requirement for all capabilities as described in the proposed IDI Resolution Plan rule, whether this be for an upstream projection at the model level or warehoused downstream in a virtual data room. While liquidity, given its maturity from a regulatory perspective may have the necessary data quality, newer requirements such as being able to carve up valuable franchises may create some additional work to allow for a more flexible view of an organization beyond legal entity, business, or critical operation. An example of this would be wealth management or deposit franchises. Some remediation work may need to occur on the system of record (SOR) or subledger, which given the age of some of this infrastructure may pose a challenge given the limitations of older technology. Financial institutions should assume a much longer lead time and significant investment dollars for work tied to older technology to produce desired results.
While speed is clearly a common theme of the most recent proposals, the ability to forecast over a range of scenarios and assumptions is tantamount. While firms can leverage much of the stress-testing infrastructure and scenarios as a base, the ability to induce failure of a financial institution through an idiosyncratic scenario illustrates the firm understands where some of their more fatal vulnerabilities may lie. It would also be prudent to consider second order and even tertiary effects and demonstrate these capabilities.
Governance and controls are another important topic to address. The current processes around forecasting rely on a long, drawn-out process of data certification, vetting of assumptions, review and challenge, and board sign-off. Forecasting, planning, and analysis (FP&A) and CCAR are notable examples of this. However, organizations must be realistic about how much time they have to produce and certify results. While baseline forecasting may have the luxury of weeks to certify results, the FDIC is working with a compressed resolution runway, which may require some results to execute a sign-off in a matter of days. The use of automation and specific playbooks that account for a compressed period of decision making should be employed and tested rigorously to reduce non-value add activities that only increase the time needed to make critical decisions.
Building the Foundation for Success
Given the current state of many RRP programs, increasing speed of execution without investing in the data quality, technology, and controls underlying its forecasting and valuation capabilities will inevitably lead to increased operational risk. While the build out of these programs to maturity will take years, firms should invest in the necessary foundational capabilities that they can steadily build upon and resist expense-saving measures that might appeal in the short term (but result in additional regulatory scrutiny in the long term). They should also routinely test these capabilities to help ensure they are in alignment with supervisory expectations.
For more information, reach out to a professional at FORVIS.