BAMIDELE OGUNWUSI
The recent accelerated rise in global interest rates, the fastest in decades, brought the curtain down on an extended period of cheap money but provided little clarity on the longer-term outlook, McKinsey & Company said in a report titled, “Banking on interest rates: A playbook for the new era of volatility”.
In 2024, competing forces of tepid growth, geopolitical tension, and regional conflict are creating nearly equal chances of higher-for-longer benchmark rates and rapid cuts. In the banking industry, this uncertainty presents both risks and opportunities. But in the absence of recent precedent, many institutions lack the necessary playbook to tackle the challenge.
As rates have risen from their record lows, banks have in general profited from rising net interest margins (NIMs).
However, if policy makers switch swiftly into cutting mode, banks may see the opposite effect.
For now, futures markets predict the start of that process toward the end of 2024.
In that context, the question facing risk managers is how they can retain the benefit of higher rates while preparing for cuts and managing the potential for macroeconomic surprises.
The volatility playing out in rates markets is reflected in bank deposit trends, with customers more actively managing their cash to make the most of shifting monetary conditions.
In Europe, deposits reached 63 per cent of available stable funding (ASF) in 2023, compared with 57 percent in 2021.1 In the US, conversely, the share of deposits over total liabilities fell over a similar period as money migrated to investments such as money market funds.
In the face of accelerating deposit flows, McKinsey research shows that bank risk management and funding performance has been highly variable. Between 2021 and 2023, the best-performing US and EU banks saw interest rate expenses rise 70 per cent less than at the worst-performing banks.
Alongside the impacts of deposit flows, funding has come under pressure from other factors, including the steady withdrawal of pandemic-related central bank liquidity facilities.
Meanwhile, innovations such as instant payments have motivated customers to make faster and larger transfers. These withdrawals can happen quickly and be fueled by social media, creating a powerful new species of risk.
In the context of a more uncertain environment, regulatory authorities are doubling down on oversight of the potential impacts of rate volatility—for example, by asking banks to mitigate the potential effects of rate normalization, increasing overall scrutiny, and demanding evidence of methodology upgrades.
Among European supervisory priorities for 2024–26, banks are advised to sharpen their governance and strategic frameworks to strengthen asset and liability management (ALM) and develop new funding plans and contingency measures for short-term liquidity shocks, including evaluating the adequacy of assumptions supporting some behavioral models.
In the same vein, the Basel Committee on Banking Supervision in 2023 proposed a recalibration of shocks for interest rate risk in the banking book.
Banks can achieve this by extending the time series used in model calibration from the current December 2015 standard to December 2022, bringing more volatile rate distributions into the equation.
In a recent McKinsey roundtable, 40 percent of Europe, Middle East, and Africa bank treasurers said the topic that will attract most regulatory attention in the coming period is liquidity risk, followed by capital risk and interest rate risk in the banking book (IRRBB).
With these risks in mind, 34 per cent of treasurers said their top priorities with respect to rate risk were enhancing models and analytics, revising pricing strategies on loans and deposits, and beefing up ALM governance and monitoring capabilities.
Most participants also expected treasury teams to get more involved in strategic planning and board engagement and to engage business units more closely to define pricing strategies and product innovation.
Most banks expect more treasury involvement in strategic processes and more interaction with business units.
Steps to enhancing the treasury function
To manage volatile interest rates more effectively, leading banks are revisiting practices in the treasury function that evolved during the low-interest-rate period and may no longer be fit for purpose—or at least should be updated for the new environment.
Pioneers have taken steps in five broad focus areas: steering and monitoring, risk measurement and capabilities, stress testing, bank funding, and hedging.
A precondition of effective oversight of interest rate business is to ensure decision makers have a clear view of the current state of play.
Currently, the standard approach across the industry is somewhat passive, meaning it is based on static or seldom-reviewed pricing and risk management decisions, often taken by relationship managers.
Models are fed with low-frequency data, and banks use static fund transfer pricing (FTP) to calculate net interest margins. Monitoring often reflects regulatory timelines rather than the desire to optimize decision making.
Increased product innovation to boost funding from both corporate and retail clients ensuring access to high-quality, frequent, and granular data, with systems equipped to send early warning signals on potential changes in customer behaviors, especially to capture early signs of liquidity shifts use of risk limits and targets as active steering mechanisms, bolstered by links to incentives automation of reporting and monitoring, so liquidity and other events can be scaled internally much faster, backed by real-time data where possible.
Leading banks are getting a grip on IRRBB risk in areas such as balance sheet management, pricing, and collateral. Many have assembled dedicated teams to help them make more effective decisions. Given the threat to deposits, some are making greater use of scenario-based frameworks, bringing together liquidity and interest rate risk management. They are using real-time data to inform funding and pricing decisions.
To ensure they consider all aspects of rate risk, leading banks employ a cascade of models, feeding the outputs into steering and stress-testing frameworks, and capturing behavioral indicators that can inform balance sheet planning and hedging activities. Some banks are employing behavioral models to forecast loan acceptance rates and credit line drawings. Best practice involves using statistical grids differentiated by type of customer, product, and process phase.
Several players are integrating interest rate risk, credit spread risk, liquidity risk, and funding concentration risk in both regulatory and internal stress tests. Indeed, the IRRBB, liquidity risk, and market risk (credit spread risk in the banking book, or CSRBB) highlight the trade-off between capital and liquidity regulations. In short, higher capital requirements may reduce the need for excessive liquidity, and vice versa, for a bank with stable funding—a situation that remains a challenge to current regulatory frameworks.
Stress testing to measure interest rate risk is also evolving, with some banks adopting reverse stress testing (see sidebar “Enhancing Basel’s interest rate risk measures: Exploring the efficacy of reverse stress testing and VAR”).
In upgrading their stress-testing frameworks and interest rate strategies, banks need to balance net interest income (NII) and economic value of equity (EVE) risks that may materialize as a function of rate volatility.
On NII, banks can productively apply scenario-based yield curve analysis across regulatory, market, and bank-specific variables and weigh these in the context of overall balance sheet exposures, hedges, and factors including deposits, prepayments, and committed credit lines. Additional economic risks include basis risk, option risk, and credit spread risk, which also should be measured.
Decision makers should evaluate the value of mortgages under different interest scenarios and derive sensitivities to economic value and P&L. They can then select hedging instruments with the aim of neutralizing scenario impacts.
Another important focus area is deposit decay. Many banks still prioritize moving-average approaches segmented by maturity and backed by expert judgment. A best practice would be to identify a core balance through a combined expert and statistical approach, looking at trends across customer segmentation, core balance modeling, deposit volume modeling, deposit beta and pass-through rates, and replicating portfolio/hedge strategies.
This would mean leveraging AI and high-frequency data relating to transactions, to estimate each account’s non-operational liquidity, which customers may be more likely to move elsewhere (see sidebar “Case study: Deposit modeling to limit deposit erosion”). Some banks also use survival models to gauge non-linearities in deposit behaviors.
Decision makers should evaluate the value of mortgages under different interest scenarios and derive sensitivities to economic value and P&L. They can then select hedging instruments with the aim of neutralizing scenario impacts.
Another important focus area is deposit decay. Many banks still prioritize moving-average approaches segmented by maturity and backed by expert judgment. A best practice would be to identify a core balance through a combined expert and statistical approach, looking at trends across customer segmentation, core balance modeling, deposit volume modeling, deposit beta and pass-through rates, and replicating portfolio/hedge strategies.
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