Do you need AI or a consultant?

I was reading McKinsey’s annual summary of what’s hot and what’s not in banking the other day. They pick on four areas:

• Technology
• The new consumer
• Capital efficiency
• Targeted M&A

What got me is that this is just PEST in other words. What’s PEST? It’s the way we predict the future based upon Political, Economic, Social and Technological forces of change. Fair enough, but McKinsey wraps it into pseudo-intellectual consulting speak. No wonder it’s the end of consultants.

Anyway, have a good read if the future of banking interests you …

Executive summary

In 2024, the global banking sector generated profits of about $1.2 trillion, the highest total ever for any industry. Yet capital markets remain skeptical: Valuations trail the average of all other industries by nearly 70 percent.

Why? Markets doubt banks’ recent highs are sustainable, seeing them as tailwind driven. Complicating the picture are macroeconomic forces, including declining interest rates, shifts in technology and consumer behavior, and the steady siphoning of attractive profit pools by fintechs, private credit, and wealth managers. This confluence of factors could push banks’ ROE below the cost of equity in many markets.

To thrive in this new era, banks need new solutions. Macro-focused, scale-driven strategies once promised resilience but no longer suffice. Precision is the decisive differentiator, separating leading banks from slow movers and reshaping the industry’s performance curve.

The “precision toolbox,” applicable to banks of any size, revamps strategy across four core dimensions:

— Technology: focusing surgically on technologies with the greatest impact—even within agentic and gen AI—while scaling back investments that don’t improve workflows, customer engagement, or business models.

— The new consumer: moving beyond broad segmentation to individualization (a “customer segment of one”), delivering hyperpersonalized, data-driven access to products and services that earn trust in an era of fading loyalty.

— Capital efficiency: shifting from sweeping reallocations to micro-level balance sheet discipline—product by product, client by client, down to individual risk-weighted assets—to free up trapped capital with precision and put it to work where it earns more.

— Targeted M&A: moving from scale for size’s sake to precision, pursuing deals that add reach in specific micromarkets or geographies, or that bring distinct capabilities in a specialized area.

Precision, not heft, is the great equalizer. In the age of AI, even smaller banks can capture disproportionate rewards by embedding precision into every dimension of strategy.

This report covers all four elements of the precision toolbox, with an in-depth look at AI and the new consumer.

AI, particularly agentic AI, holds significant promise for banking, with early adopters securing a lasting advantage over slow movers. Given these are still the early days of agentic and gen AI, it is imperative to use surgical precision to identify where these technologies can truly generate earnings impact, rather than piling into them because of the fear of missing out.

As AI is implemented across the banking industry, it could bring gross reductions of as much as 70 percent in certain cost categories. But because these savings will be partly offset by rising technology costs, the net effect on banks’ aggregate cost base is expected to be a 15 to 20 percent decrease. The impact of these savings, while welcome, won’t last. As with earlier innovations, competition will likely erode the gains for banks and most of the benefits will accrue to customers over time.

Longer term, AI is likely to erode bank profitability as consumers start routinely using AI agents to optimize their finances (for example, automatically moving deposits into higher-yield accounts), which would reduce customer inertia and reshape industry economics. In particular, agentic AI could disrupt deposits and credit card lending by cutting through inertia.

The threat from third-party agents could be material. If banks don’t reposition their business models to adapt, over the next decade or so, bank profit pools globally could decline by $170 billion, or 9 percent. This could reduce the average return on tangible equity (ROTE) by one to two percentage points and push many banks below their cost of capital.

But the effects won’t be felt equally. AI pioneers could see ROTE increase by up to four percentage points, using their lead to reinvent models and capture value. Conversely, slow movers are likely to see lower profits long term.

Winning with consumers is also crucial. AI is shaking up how customers and banks interact, raising expectations for seamless, hyperpersonalized experiences, especially among younger generations.

Consumers are more digital, less loyal, and more deliberate in how they choose financial providers. In the United States, for example, only 4 percent of new checking account applicants choose their existing bank without first exploring alternatives, down from 25 percent in 2018. Instead, customers place more importance on the first few banks they consider in their purchasing journey. Banks that secure a place in this initial consideration set are best positioned for success.

The transformation has been driven by AI and mobile. Most consumers already use gen AI and expect their banks to provide these tools as well, while mobile is now the most widely used banking channel. Banks that integrate AI-powered insights with mobile-first, personalized experiences, blending digital ease with human connection, will define the next era of customer engagement.

To thrive, banks need to win consumer mind share, embrace mobile as the gateway for engagement, and embed AI into customer journeys before challengers seize the advantage.

For banks that are used to time-worn, traditional strategies and the pursuit of scale, adopting precision won’t be easy, but those that act decisively stand to capture outsize payoffs. In the new era of AI-enabled precision, leadership is not about size—it’s about focus.