How higher interest rates are affecting bank liquidity

A panel of industry experts discusses the challenges posed to banks’ capital and liquidity by a persistently higher interest rate environment. They also share insights on adapting their liquidity risk management strategies, tools and technologies for a new era 

Higher interest rates look set to persist. What challenges does this present for banks?

Ash Majid, SMBC Capital Markets and SMBC Nikko America: Higher interest rates will obviously increase funding costs for banks. However, this allows for an expansion of net interest margin if deposits/funds can be raised efficiently. This is challenging for larger banks as many digital/fintech start-ups are offering relatively higher rates to attract deposits. Additionally, with the higher cost of funds, management has become more selective in where to deploy capital in terms of scrutinising deployment and increasing hurdle rates, among other options.

Jan Willem Jagtenberg, de Volksbank: Higher interest rates will mean a challenge to the future net interest income of banks. This is driven by:

1. Challenges on the lending side, since higher costs will cause volumes to go down. Since there is still a lot of liquidity this means that there is increased pressure on margins.
2. The shape of the curve, inverse, is also a challenge. It is normal business for banks to borrow short and lend long. However, it is currently more profitable to place deposits with the central bank, which means high sensitivity to monetary policy and short rates.
3. Challenges caused by the impact of high rates on economic environments and, consequently, default rates.

Treasury risk specialist: One of the main challenges is the impact on banks’ investment portfolios. One of the reasons Silicon Valley Bank (SVB) went down was because its ‘available for sale’ portfolio was recorded as ‘other comprehensive income’, but had taken a lot of losses because of higher rates. Even though SVB did not record them as losses to its capital, the market perceived it as a risk, and that was one of the triggers for the deposit flight.

The SVB collapse also raised questions about another portfolio that nobody used to look at – the held-to-maturity (HTM) portfolio. Banks tend to hold quite large exposures in the HTM bucket because they don't need that liquidity and they don't want income volatility. There has been a lot of attention in this area since the failure, the concept of shadow capital and what your capital ratio would be if your HTM portfolio were fully marked-to-market? Would you be adequately capitalised? Large banks in particular are looking at how to mitigate that risk. To manage perceptions, they are looking at how to hedge the risk, but this has its own downsides because those hedges won't qualify for hedge accounting.

The level of capital is important because of capital deterioration: the strength of these banks has also taken a hit, which has led some large depositors to look at alternatives, such as money-market funds, which they may perceive as less risky. Competition for deposits has increased, and banks have been required to start pricing more aggressively.

Pierre Gaudin, ActiveViam: Aside from the mechanical changes this brings to the maturity transformation operated by a bank’s balance sheet, the current context clearly requires operational optimisation. Broadly speaking, we can see two approaches deployed by financial institutions to build their exposure to interest rate fluctuations. Some institutions rely mostly on floating-rate loans, which transfers the interest rate risk to the borrower. The current context challenges this strategy as it increases institutions’ exposure to credit risk while the financial situation of borrowers deteriorates.

Banks that have mostly granted fixed-rate loans now avoid this effect. To achieve this, asset-liability managers and treasury teams deploy operational tools to optimise their hedging strategies. Similarly, on the liquidity side, the same tools can increase operational efficiency and help optimise funding costs. Overall, these institutions are now in a position to navigate the current scenario, with operational efficiency being instrumental to their competitiveness.
 

What are your primary concerns around liquidity in the current environment?

Ash Majid: Securing deposits and deposit stickiness have been a source of concern recently. That said, we have not been led to believe there are systemic liquidity issues across the industry at this point.

Jan Willem Jagtenberg: It is obvious the shift in rates has resulted in a lower market value of liquidity portfolios and, if not managed appropriately, will cause problems in cases of stress. On the other hand, in the Netherlands, retail funding and especially guaranteed deposits have proven stickier than expected. The current uncertain environment does require a review of the robustness of liquidity contingency options.

Treasury risk specialist: The key concern around liquidity is the deposit flows, and what the liquidity stresses should be. Should we increase outflows in our stress-testing given what we saw with the SVB failure? And do we have deposit concentrations in a particular industry? Firms are establishing sources of liquidity as a contingency, such as standby credit with the US Federal Reserve. Things can happen quite dramatically, given the role of technology and social media.

Pierre Gaudin: Institutions are indeed exposed to new challenges. Regulation for liquidity coverage and net stable funding, set by regulators in the wake of the financial crisis that began in 2007–08, is now well in place, but the past year has illustrated how these ratios need to be managed in a context of high interest rates and asset price volatility.

The time horizons for liquidity management – 30 days for liquidity coverage, and one year to define stable funding – are now challenged. As asset prices fluctuate, their contribution to liquidity coverage demands closer monitoring. Furthermore, the disclosure of liquidity ratios may trigger an immediate reaction from depositors, amplified by instant communications across social networks.

Overall, liquidity risk now displays a heightened propensity to trigger reputational risk. As a result, we now see an increased focus on the operational capacity of our clients’ risk, treasury and finance teams to monitor risks, identify problems as they arise, and seize every opportunity to reduce funding costs.
 

What actions have you taken or are you taking to improve liquidity management practices?

Ash Majid: Liquidity stress-testing models and assumptions have been reviewed to ensure they are still sound models.

Jan Willem Jagtenberg: Liquidity risk management has always been a cornerstone of proper balance sheet management. Improving the way of working is a continuous process; however, based on the lessons drawn from the failures of the US banks and Credit Suisse, an assessment has been performed on the assumptions of the internal liquidity stress test, the risk profile of the liquidity portfolio and the robustness of the liquidity contingency options.

Treasury risk specialist: As part of your regular business activities, such as introducing new products or completing a large transaction, you need to assess the liquidity impact. The recent Industrial and Commercial Bank of China (ICBC) failure, for example, had a liquidity impact. So, if you extend loans to ICBC to cover some unsettled rates, you need to be aware of how much liquidity you have and how much you can afford. So liquidity is getting more integrated into day-to-day management.

Pierre Gaudin: In this context, our clients have deployed Atoti for Liquidity, an innovative technology providing fast in-memory analytics that serves as an operational intelligence platform. This framework acts as a communication hub between teams, consolidating a single source of truth according to their preferred classifications. It provides key operational efficiencies, allowing different teams of users to view, adjust and monitor all data and analytics, and see the effect of what-if assumptions on all current and forecast liquidity metrics.
 

To what extent do banks need to reassess their liquidity stress-testing assumptions in light of this year’s bank failures?

Ash Majid: We have been enhancing our stress-testing models as business as usual since the beginning of the year. Assumptions have been challenged and, additionally, stress scenarios have been revamped. We have had a requirement to revisit stress scenarios, at a minimum, annually. We have now changed that to quarterly and, of course, scenarios can be changed at any time deemed necessary in this environment.

Jan Willem Jagtenberg: This year’s failures once again highlighted the close relationship between interest rate risk, capital risk and liquidity risk. This is input for reassessing scenarios and severity of the internal liquidity stress-testing model. In addition, the speed of outflow and timing of intervention of appropriate authorities is an important input for recalibrating the assumptions.

Treasury risk specialist: Banks need to conduct liquidity stress tests more frequently, and the tests need to be more robust. Senior management should be looking at those tests not just for regulatory reporting, but to always be aware of the liquidity position and whether there is enough liquidity to cover a stress.

Pierre Gaudin: The events of 2023 have underscored the need for a proactive approach in predicting ballooning effects in much shorter time horizons than previously expected. As a response to these challenges, our users are now incorporating a significantly higher number of ad hoc, what-if scenarios into their daily interactions with the business, treasury and finance teams, in addition to the calibrated scenarios managed by their asset-liability management (ALM) and liquidity systems.

In this evolving landscape, operational intelligence has gained substantial importance. It acts as a valuable supplement to existing forecasting methods, enabling treasury, risk and finance teams to collaborate seamlessly and access data instantly. This real-time interaction allows them to adjust their forecasts and observe the immediate impact. By doing so, they can proactively monitor and pre-empt risks when and where needed to support contextual analysis and decision-making.
 

What are your hopes and fears around future regulatory changes to liquidity risk management?

Ash Majid: Industry expectation is that there will be new regulation following the SVB/regional banking debacle. We are yet to see formal new regulations; however, we have noted heightened regulatory monitoring and enquiries/scrutiny on practices.

Jan Willem Jagtenberg: For regulators, there is an opportunity to rethink their approaches on liquidity risk management. There should not be a focus on stricter limits for metrics such as liquidity coverage ratio (LCR) or net stable funding ratio, but a more comprehensive view on financial risk management, including alignment with accounting rules. Obviously, bank failures were not driven by low liquidity buffers but by mismanagement in other areas such as credit risk and interest rate risk management. My fear is that regulators only look at liquidity risk in isolation, and changes do not contribute to a more robust financial system.

Pierre Gaudin: As illustrated by the Comprehensive Liquidity Analysis and Review framework in the US, supervisors are increasing their focus on stress-testing to ensure banks remain above the required level during difficult times. Beyond the review of these analytics, they may also set an emphasis on auditing the operational procedures in place to prevent and mitigate such incidents in a timely manner.
 

What factors should determine firms’ strategies defining liquidity buffers?

Jan Willem Jagtenberg: The liquidity value of products in different stress events, idiosyncratic as well as system-wide, and depth of the market (market liquidity) are important considerations. Furthermore, the diversification of different components – for example. cash, sovereigns, retained residential mortgage-backed securities – is also a key factor.

Pierre Gaudin: From our observations, it is evident that the LCR has become a communication tool for managing reputational risk. Financial institutions are now striving to display an optimised ratio, even during periods of financial stress. By demonstrating a clear discipline in their management of funding resources, the objective goes beyond regulatory compliance; institutions seek to instil confidence and trust among stakeholders. In a June 2022 report on liquidity measures by the European Banking Authority, notably high figures were reported. Systemically important institutions displayed LCRs at around 150%, while smaller institutions set themselves above 200%, seemingly associating a reputation value with an enhanced coverage capability.
 

How can banks best embed liquidity risk management principles in day-to-day decision-making?

Ash Majid: Better-crafted early-warning indicators, along with liquidity risk metrics, to monitor overall liquidity risk posture are essential for better day-to-day decision-making.

Jan Willem Jagtenberg: The answer lies in appropriate governance and a strong risk management framework. Managing liquidity risk is not based on day-to-day decisions, but on a clear view of balance sheet structure, risk appetite, mandates, capital and funding plan, contingency and recovery measures, among others. Management information systems should enable monitoring drivers of liquidity risk on a daily basis to allow for a swift response.

Pierre Gaudin: ActiveViam’s clients have adopted its operational intelligence framework for liquidity. The Atoti for Liquidity platform seamlessly integrates with clients’ existing ALM and treasury infrastructures, offering immediate insights into the current liquidity available and its precise location. These insights can be displayed alongside the latest forecasts calculated by the balance sheet management system, as well as additional stress tests handled by the operational intelligence framework itself.

To support the operations for intraday decision-making and end-of-day controls, Atoti streamlines communication between teams, allowing users to share reports and dashboards, track key performance indicators and receive notifications on any limit breaches. The platform also supports the associated sign-off processes, ensuring any data audit and adjustment follows the proper validation processes. Balance sheet forecasts are also compiled with additional analytics, allowing users to adjust data and simulation assumptions to gauge the impact instantly on all liquidity indicators.
 

How can firms maximise value from their investment in liquidity risk management tools and technology?

Ash Majid: This is a difficult proposition, as liquidity risk is ideally managed at the enterprise level, therefore requiring data from systems and platforms across all business lines to be aggregated. Additionally, there should be analytical capability at that level, which is challenging, as now you are dealing with different businesses and products. To maximise value, firms need to design data warehousing and management appropriately to ensure the proper analytical and aggregation frameworks can be implemented at the top of the house.

Jan Willem Jagtenberg: From my perspective, risk management tools allow for identifying sensitivities in the balance sheet. The impact of certain stress scenarios might be severe, especially when products on the balance sheet contain contractual and behavioural models. While some banks stop when they have calculated and forecasted the different metrics, the real value lies in the actual management. Questions such as 'Are there sensitivities within the risk appetite?' and 'Does it require business steering, hedging or other forms of insurance?' must be raised on an ongoing basis.

Treasury risk specialist: Banks will always need to invest in this area, but the question is how much to outsource and how much to build in-house. Large banks like to build their own systems. Smaller ones are more likely to look to third parties.

Pierre Gaudin: Atoti's operational intelligence framework for liquidity harnesses in-memory analytics and taps into the extensive big data stored in an institution's data lake. This allows users to understand trends and identify historical reference points, which are presented alongside current production data.

The infrastructure places a strong emphasis on performance and process optimisation, facilitating operational efficiency across large teams of users. By applying instant aggregation and business rules over billions of data points, it delivers unparalleled agility in supporting users’ enquiries and decision-making.

In summary, this framework helps business, treasury, risk and finance teams maximise the usage of the analytics delivered by existing systems to deliver instant answers, report and manage liquidity risks as they emerge, anticipate and navigate stressed situations, and identify business opportunities.
 

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