In our related posts AI in Retail Banking, we looked at how AI is transforming retail banking today, and what the AI enabled bank of the future looks like here The Agentic Bank. The bank of the future article cited some brutal prognostics about bank margin compression.

To recap, a potential $170 billion fall in overall retail banking profits. A 9% reduction in general profitability. A 1-2% reduction in Return on Equity (ROE) (Source: McKinsey).

In this article we explore what is driving that forecast, and why AI adoption is do or die for retail banks to save their bacon.
This article is based on an AI workshop our founder Emma recently conducted with a group of professionals from a leading UK retail bank.

In the world of banking, deposits have long been the quiet powerhouse behind profitability. High net interest margin, which is the difference between what banks earn on loans and pay on deposits, have been propped up by one simple truth: customer inertia.

People stick with their low-interest savings accounts not because they're thrilled, but because switching banks feels like a hassle. Paperwork, branch visits, direct deposit changes. It is all too much effort for most.

But that era is ending, fast.

Enter AI-powered tools that are revolutionizing how customers manage their money. These innovative products scan the market in real-time, identifying the highest interest-bearing accounts across any bank and automating the switch with minimal friction.

Suddenly, loyalty isn't about habit; it's about who offers the best rate, right now. For banks, this spells trouble. Margins that were once comfortably wide are now under siege, as deposits flow like water to the highest bidder. Profitability is at a tipping point, and traditional banks risk being left high and dry.

The Deposit Game Just Got Fiercer

To survive and thrive, banks can't rely on outdated strategies. The "win the deposit game" playbook demands agility, data smarts, and a customer-centric overhaul. Here's what leading institutions are doing to fight back, based on emerging best practices:

Dynamic and Personalized Pricing Strategies. Gone are the days of one size fits all interest rates. Banks need to craft relationship based pricing that treats customers as individuals. For instance, newly acquired customers might respond to aggressive introductory rates to build loyalty, while long standing ones could be nudged with tailored perks based on their price sensitivity. Empowering front line staff with real time tools to personalize offers, drawing on specific attributes like life stage or spending habits, turns generic transactions into sticky relationships. Without this, AI switchers will poach your best clients effortlessly.

Gaining Full Customer Balance Sheet Visibility. Knowledge is power, especially when deposits can vanish overnight. Banks must prioritize a near real time 360 degree view of each customer. This means aggregating data on transaction flows, demographics, and key churn signals like a big life event or sudden spending spike. With this visibility, banks can spot "critical moments" for intervention, such as offering a better rate just as a customer eyes a switch. It's not just about holding deposits; it's about deepening ties before competitors do.

Leveraging Advanced Deposit Modeling. Data driven decisions are non negotiable. Top banks are building sophisticated analytics to execute deposit strategies with precision. Think bespoke models that test price elasticity at the individual relationship level. How much rate bump will it take to retain $10,000 in savings? Or balancing the trade-offs between higher rates (which attract volume) and sustainable profitability.

Building a Unified Operating Model. Silos kill agility. To compete, banks need cross organizational coordination with governance that enables dynamic deposit management. Marketing, product teams, and risk must align on a single playbook, allowing quick pivots like launching a targeted promo in response to market shifts. Without unity, even the best ideas fizzle out in bureaucracy.

Enabling Rapid Decision Support. Speed wins wars, and the deposit battle is no exception. Leading banks are tracking promotion and marketing campaign effectiveness on a daily or weekly basis. This real-time feedback loop lets leaders make evidence based calls, tweaking strategies on the fly. In an AI driven world where customers switch in seconds, hesitation could cost millions in outflows.

The Profitability Pressure Cooker: Why Banks Can't Go It Alone

These strategies sound robust, but implementing them isn't for the faint of heart. Traditional banks, weighed down by legacy systems, regulatory hurdles, and internal politics, often move at a glacial pace. Meanwhile, AI disruptors and fintechs are iterating weekly, capturing market share with nimble innovation. The result? Eroding margins, shrinking deposit bases, and a profitability crunch that could ripple through balance sheets.

Banks face existential pressure. Net interest income, once a reliable cash cow, is vulnerable as never before. If deposits keep migrating to higher yields elsewhere, funding costs rise, lending power shrinks, and shareholder value takes a hit.

Why Internal Teams Aren't Enough

The roadmap outlined above is clear, but the timeline is unforgiving. Implementing advanced modeling, unifying operating models, and achieving real-time data visibility are heavy lifts for legacy institutions.

Most banks are burdened by bureaucratic layers and legacy tech stacks that make rapid innovation difficult. By the time a traditional bank internally develops and deploys these capabilities, the AI algorithms will have already moved a significant portion of their deposit base to a faster competitor.

A Call to Action

Audit your current deposit strategy against the five pillars. Identify the biggest gaps.

Select a strategic partner with proven AI driven solutions. Not powerpoints and prototypes. Actual AI Agents that actually work in actual production.

Co-create a rapid deployment roadmap and target a pilot that delivers a 360° view and dynamic pricing within 90 days.

Implement real time decision dashboards to monitor campaign impact and adjust instantly.

Scale the solution across the organization, implement the unified operating model and governance.