Deposits: the new centre of gravity in liquidity strategy

When it comes to determining how much liquidity they can safely deploy, banks should be looking beyond balance sheet size to a more important variable: deposit behaviour. In this article, we explore why understanding deposits has become the sharpest lever for unlocking growth, and the biggest source of risk when misread.

Deposit behaviour has always mattered, but in the wake of the banking stresses of 2023, it has become the defining factor in liquidity and balance sheet strategy. With buffers already elevated and recalibration cycles tightening, forecasting deposit stability with precision now plays a critical role in determining not just how much liquidity a bank holds, but how much it can use.

This article is part of a broader series from Baringa on how banks can rebalance risk and growth across the balance sheet, from the buffers and models that shape capacity to the infrastructure that determines how it’s deployed.

Here, we focus on a key variable driving liquidity and risk uncertainty: deposit behaviour. In our view, deposits have become one of the most sensitive behavioural variables on the balance sheet for many banks, and one of the least forgiving when assumptions fall behind reality.

Why deposit behaviour dominates liquidity outcomes today

Today, money moves faster than ever, and that speed means banks can’t rely on assumed stability the way they used to. Customers, corporates, and wealth clients can move balances in moments, with outflows increasingly reflecting confidence and narrative rather than price alone. Even small errors in behavioural assumptions can now impact liquidity outcomes more decisively than balance sheet size or funding mix, especially when behaviour shifts faster than governance can keep up.

This is why elevated liquidity buffers persist even when the economics argue for redeployment. Instead of regulatory constraints, uncertainty around deposit behaviour has become the main brake on unlocking capacity.

Challenging the traditional notion of “stickiness”

For many liquidity decisions, stickiness used to be a decent enough proxy for stability. Familiar rules of thumb like retail equals stable, insured equals safe, and operational equals durable don’t offer enough predictive confidence anymore. Behaviour now crosses these lines much faster, and in ways that do not always map neatly to old classifications.

Governance often struggles to keep up with these new dynamics. Labels stay the same long after behaviour has changed, and assumptions can remain unchanged even when frontline teams are seeing movement. The result is a growing gap between what models show and what’s really happening, especially when sentiment changes.

Segmentation still matters, but in a different way

Segmentation is still essential, but its value has shifted more towards showing how behaviours overlap under different conditions, rather than sorting deposits into fixed categories:

• Retail and wholesale deposits have different behavioural drivers, but neither label reliably predicts stability in all conditions
• Insured and uninsured deposits shape the incentive to withdraw, but insurance status alone doesn’t determine when or how quickly balances will move
• Transactional and rate-sensitive balances can sit within the same customer relationship, with the mix shifting as rates, liquidity needs, and market conditions change
• Operational balances are linked to day-to-day sercices, but only the portion required for those activities can be assumed to remain stable under stress.

It’s best to treat these segments as reference points, not anchors. What matters more than any single behavioural label is understanding the range of behaviours that each segment can show.

The evolving behaviour of a deposit

Thinking in maturities can offer a better way to understand how deposits actually behave over time. Every deposit is a mix of long-run core balances, reactive balances, and tactical money that moves with markets or sentiment. These proportions change much more often than most recalibration cycles allow for. When sentiment or rates move sharply, the share of deposits behaving like short-term money can increase abruptly.

On top of this, each component responds to signals in its own way, complicating things further. Core balances behave predictably, reactive balances follow the narrative, and tactical money moves almost algorithmically with volatility. This makes behavioural maturity much more fluid than any single number can capture, and it’s often where fixed decay rates and long-run averages start to break down. It means that the model may still be forecasting stability while the balance sheet is already moving away from it.

The limitations of real-world modelling

Decay models, survival curves, and behavioural profiling are still central to liquidity and IRRBB practice. They bring structure and comparability, and they are well understood across treasury, risk, and finance. However, their limitations are getting harder to ignore:

• Reliance on historical patterns that no longer reflect current behaviours
• Assumptions that hold under normal conditions, but flatten under stress
• Recalibration cycles that can’t absorb rapid behavioural changes
• Limited ability to capture concurrent rate, market, and confidence dynamics.

All of this means that responsiveness now matters more than precision. As we noted in our article on risk modelling, the industry has moved past debates about which model is “best” and towards a focus on how quickly insights can be refreshed and acted on.

Stress-testing deposit behaviour in a world of concurrent shocks

Deposit outflows rarely have a single driver anymore, but are affected by rate sensitivity, perceived safety, and corporate liquidity management, which often interact all at once. Outflows can accelerate even without extreme market moves. Sometimes, all it takes is a credible narrative to shift behaviour across multiple segments. This is why single-factor stresses increasingly understate risk.

Firms that rely on single-factor stresses often discover pressure points only after early warning indicators have fired. In contrast, those that build overlaps into their stress frameworks are better positioned to rebalance proactively.

Turning improved insight into headroom for growth

Deposit insight has increasingly become strategically important, and better behavioural understanding now shapes:

• Pricing: understanding elasticity before competing on rate
• Hedging: sizing structural hedges with greater confidence in deposit duration
• Funding mix: relying less on short-term wholesale funding, which is more volatile and costly under stress
• Balance sheet optimisation: safely unlocking trapped liquidity
• Governance: enabling asset and liability committees (ALCOs) to make deliberate decisions instead of defensive ones.

For many institutions, the main constraint on redeploying liquidity isn’t regulatory requirements, but behavioural uncertainty. Reducing that uncertainty has become one of the most effective ways to safely unlock capacity.

When firms rely less on blunt liquidity buffers and build more confidence in their behavioural insights, two things tend to happen. First, they stop treating large buffers as a universal safeguard. Their decisions become more precise and deliberate. Second, they gain more room to deploy liquidity for growth without increasing vulnerability. This reflects a broader pattern across the industry: as uncertainty narrows, capacity opens up.

Closing thought

Deposit behaviour has become one of the fastest-moving and most important variables in liquidity management. The challenge now is whether banks can put that insight to work by establishing clear ownership over it, keeping it up-to-date, and embedding it into decisions across treasury, risk, and finance. Better behavioural understanding creates opportunity, but only if it’s used consistently and at scale. And having the ability to act on insight may end up mattering just as much as the insight itself.