The opinions expressed here are those of the authors. They do not necessarily reflect the views or positions of UK Finance or its members.

Leading institutions now focus on the emerging differentiator: removing effort from the customer journey entirely.

Customers evaluate digital banking by friction involved in getting things done. Streamlining navigation and unifying information simplifies decision-making in a world where digital experiences elsewhere are becoming progressively more anticipatory. The institutions ahead predict customer intent and surface relevant options before customers search for them, often before they articulate a need.

The effort economy and intent prediction

Intent-based features are now established practice among digitally advanced institutions. Based on behavioural signals and consent, a customer preparing for travel might see travel-related card settings, insurance options, or spending controls without manual searching.

What separates mature implementations from early experiments is infrastructure. Effective intent prediction requires combining behavioural analytics, event-driven architecture, and rapid decision engines. It also requires discipline: precision is essential to maintain customer confidence, making continuous feedback loops and model refinement critical. Intent systems that surface irrelevant suggestions train customers to ignore them.

Omnichannel as shared memory

Most banks offer services across mobile, web, branch, and contact centre. Channel availability is largely table stakes. The next maturity stage is shared memory: a unified customer view across every touchpoint. If a customer begins a loan application in a branch, their mobile app should reflect that immediately, without requiring restart or re-entry.

Many digital journeys still encounter friction at channel transitions. Closing this gap requires addressing legacy infrastructure: unifying data environments, synchronising event flows, and building architectural foundations for real-time context sharing. This investment will likely become a visible differentiator between digitally mature banks and those managing fragmented systems.

Agentic banking: structuring the decision context

Agentic banking represents the next phase beyond intent prediction and omnichannel continuity.

Agentic systems go beyond surfacing products or sending alerts. They evaluate contextual data, simulate possible actions, and present structured decision pathways assembling options on the customer's behalf while preserving clear control.

For example, if a customer's balance approaches zero, an agentic system could present eligible options: overdraft extension, short-term credit, or payment deferral, with costs, impacts, and conditions clearly explained. The customer retains control over the final decision while avoiding multiple product searches.

In this model, AI absorbs operational complexity while the customer retains visibility, understanding, and control.

A path forward

The move towards intent-driven and agentic banking could materially change bank-customer relationships. By absorbing operational complexity, AI allows customers to retain strategic control while bypassing traditional digital friction. The competitive advantage is no longer app breadth, but becoming invisible, precise, effortless, and seamlessly integrated into financial life. While this requires significant infrastructure upgrades, the reward is becoming an indispensable, trusted partner.