Positioning firms for resilient financial performance

Synopsis

After decades of low interest rates, many financial institutions find themselves with long-dated, fixed rate assets in a rising rate environment. In periods of rising rates, it is difficult to manage the interest rate exposure of these positions. Unchecked, these conditions compress net interest margins, tangible book values, and other key financial ratios of the firm.

Derivatives enable financial risk managers to optimize investment and funding decisions, and client requests rather than being driven by their interest rate risk profile. Recent accounting changes and advances in analytical capabilities following CECL adoption allow executives to explore hedging strategies with greater flexibility and precision than they experienced during previous rate tightening cycles. For financial risk executives, capitalizing on this more flexible playbook is a strategic imperative.

Why in this environment?

Rising interest rates impact demand for fixed-rate financing, and the value of your institution’s fixed-rate loan and debt securities positions (bond prices fall as rates rise). More problematic for executive teams, the accounting for these valuation adjustments adversely impacts key performance metrics scrutinized by investors, even when the underlying portfolio performs as contracted.

After a long period of historically low interest rates, concerns over inflation have moderated the Federal Reserve’s accommodative monetary stance, and rates have risen in response. Increasing interest rates provide unique challenges to institutions managing the risk of fixed-rate assets, especially instruments backed by residential and commercial real estate that are characterized by dynamic prepayment and default risk. To navigate this environment successfully, institutions will need to develop a deep understanding of how these assets may behave in different market environments and consider hedging away unwanted risks.

Updated accounting for hedges

The Financial Accounting Standards Board’s (FASB) previously released updates (ASU 2017-12) that introduced the “last-of-layer” method, which enabled fair value hedges to be recognized for prepayable financial assets. Under this method, entities designate a stated amount of the asset or assets that is not expected to prepay, default, or experience other events affecting the timing and amount of cash flows, as the hedged item in a fair value hedge of interest rate risk.

Newly released Accounting Standard Update 2022-01 expands the last-of-layer model to allow designation of multiple layers in a single portfolio as individual hedged items. By allowing multiple hedging relationships with a single closed portfolio, the update enables entities to hedge a larger portion of the interest rate risk associated with a portfolio and allows more flexibility in the derivative structures available to hedge interest rate risk. The update includes provisions for new hedges to be designated, or existing hedges to be dedesignated at any time—allowing accounting to better reflect changes in an entity’s risk management activities in a dynamic interest rate environment. If a breach is anticipated (or occurs), a multi-layer strategy provides additional flexibility in determining which hedge or hedges to dedesignate.

How CECL tools help

CECL provided the incentive to advance institutions’ tools for understanding two key factors that impact hedge effectiveness: default and prepayments. Various disciplines throughout banks had some insight available to evaluate these outcomes, but CECL prompted more rigorous consideration by bringing their lifetime effects to bear on bank income statements at the inception of each loan. This financial impact enhanced the importance of understanding the interaction of macroeconomic and loan-specific information on the competition between default and prepayment risks (in a multi-period setting, raising the conditional probability of prepayment will reduce the overall or cumulative probability of default and vice versa). The resulting models integrate consideration of:

• Economic stress on loan performance
• Layers of risk (the combined effects of various factors including credit quality, loan age, combined loan to value)
• A multiperiod view (capturing time-dependent effects on default, prepayment, and recovery behavior)

These models create a richer representation of borrower behavior than was previously available to most middle market and community banks. Modeling default and prepayment processes at the loan-level (as opposed to the pool-level analysis prevalent pre-CECL) significantly improves accuracy in estimating losses, particularly for portfolios with heterogenous credit characteristics. Importantly, these models allow nuanced analysis of portfolio performance with one or multiple macroeconomic scenarios. This forward-looking, multi-scenario view enables credit teams to provide deeper insights on default and prepayment with the same scenarios used by ALM and Treasury teams to plan liquidity, investment and hedging strategies (or provide CECL model outputs directly to ALM and capital planning tools). With these additional capabilities, hedging strategies can be optimized for resilience across a range of interest rate, default, and prepayment scenarios.

For those institutions that implemented a robust CECL methodology, the insight needed to create hedge relationships is already in place. For those that did not, executives should carefully consider this broader rationale for investment. Incremental process updates can significantly impact both CECL and hedging analysis of expected portfolio performance.

How does the strategy work?

There are multiple options from a derivative perspective—all are dependent upon a clear understanding of expected behavior in the hedged item. To create effective hedge relationships, entities will need to evaluate expected prepayments and credit losses in the hedged portfolio across a range of scenarios to understand possible paths for interest rates, as well as other factors relevant to prepayment and default behavior (e.g., real estate prices, vacancy, unemployment, etc.). This analysis maximizes the precision of portfolio construction, optimizes the effectiveness of the hedge for reasonable and supportable economic conditions, and provides a recurring reference for updating risk management strategies when actual conditions vary from forecast scenarios.

Once expected behavior of the portfolio is understood, a layered hedge strategy can be developed to respond to all or part of the identified interest rate risk. Some layers may focus on moderate swings in the economy and others may be designed to be unaffected outside of economic conditions at the extremes. For example, a 3-layered hedge of a portfolio may utilize an initial layer that even in periods of sizeable economic change would not see a risk of over-hedging. A second layer could represent the difference between the extreme and expected outcome, and a final layer that would be most at risk of prepayment or credit losses. This scenario is not improbable given the current economic outlook which includes rising interest rates, inflation risk, and increasing potential for an economic downturn.

Parting thoughts

Optimizing decisions for loans and the investment portfolio, funding, and client requests is key to financial institutions’ success. It is exceptionally difficult to manage these competing priorities, especially during times of rate volatility. Derivatives are a key tool for responding to market challenges and the infrastructure to support them has evolved since the last time interest rates increased. Advances in credit analytics and favorable developments in accounting requirements position firms for a more agile response and ensure financial results reflect the benefits of risk management activities in any rate scenario.

Authors

Ben Lewis – Financial Institutions Derivatives Advisory, Managing Director & Head of Sales, Chatham Financial

Scott Dietz, Director – Financial Institution Accounting Industry Practice Lead, Moody’s Analytics

Chris Stanley, Senior Director – Banking Sector Industry Practice Lead, Moody’s Analytics