Fintechs and other specialists are pushing hard into banking’s traditional marketplace, growing at rates traditional banks rarely see. New technology has been accelerating this shift. Generative AI assistants are becoming a sales channel in their own right, allowing customers to compare offers, switch providers, and secure the best deal in every category with little effort. The unbundling of banking is no longer driven by customer choice alone, but by strong specialists and burgeoning technology that makes switching almost frictionless.
The scale of this competitive pressure from fintechs is already evident: A 2025 global study by the World Economic Forum and the Cambridge Centre for Alternative Finance, covering 240 fintechs, put average customer growth at 37% and revenue growth at 40%. This places profitable parts of the banking relationship at risk. But banks retain an advantage that specialists cannot easily match: a broad, established relationship with the customer.
The response should not be to outprice every specialist. Banks can make the overall relationship more valuable through two strategic bets: developing a truly holistic value proposition that rewards customers for consolidating financial needs in one place, and leveraging agentic systems to create a hyper-personalized client experience. While AI and agentic execution can help deliver both experiences at specialist speed, success from the banker’s perspective should still be measured through retention, share of wallet, and client value.
Relevance, not reach — why bank interactions lose to specialists
Winning requires more than a better loyalty program or AI assistant. Banks need to understand what matters to each client, identify moments when they can create value, and deliver needed intervention through the right human or digital channel.
The issue for banks is often the relevance, not the reach of their interaction with customers — and timing is everything. For instance, a client may receive a cross-sell campaign immediately after a service complaint, probably ensuring the offer will not be well received.
Instead, banks can combine products, balances, transactions, profitability, and digital activity with signals from service conversations, meeting notes, and other interactions. That breadth of context is a structural advantage over a single-product provider.
Composability — a system design principle where independent, modular components can be selected, mixed, and reassembled — turns that insight into a proposition. For instance, buying a first home can open the door to a bevy of service lines: a mortgage, insurance, renovation line, and savings plan offered as a package rather than four separate campaigns. This requires modular products and a pricing engine that can price the bundle, not just the parts. Bundled pricing and services become the plus of the banking relationship.
Rewarding breadth — making consolidation ore valuable for the customer
Loyalty becomes more powerful when it is part of the pricing architecture of the relationship. Rather than relying only on points or cashback, banks can improve terms as customers consolidate more business, creating a benefit that a single-product competitor cannot easily replicate.
The levers can include tiers based on breadth; improved spreads, rates, and fees; bundled pricing; household aggregation; and incentives linked to the value at stake. These benefits should be managed as commercial investments tied to retention, acquisition, and share-of-wallet economics.
AI makes relationship banking competitive at specialist speed
A relationship proposition only beats a specialist if it reaches the client with comparable precision and timing. AI can help identify emerging investment needs, available liquidity, attrition risk, or moments when commercial contact should pause or accelerate. The goal is to move from next-best-product to next-best-action and, ultimately, next-best-experience.
The questions become: “What does this client need, what intervention creates value for both sides, and how do we make it happen before someone else does?”
Agentic AI can connect insight with execution. For relationship managers, that can mean a workbench that prioritizes opportunities, assembles client context, recommends actions, and supports tailored conversations. For digitally served clients, the same intelligence can orchestrate interactions across mobile, online, and email.
Human and digital interactions should work as one system: Conversations inform the next digital interaction, digital behavior informs the next relationship-manager conversation, and outcomes improve future decisions.
A new AI engine or loyalty proposition in isolation will not change the outcome. Banks need an integrated response across four dimensions: people and operating model, distribution channels, personalization, and data and analytics.
Relationship managers need to adopt AI-supported recommendations, channels need to be orchestrated, personalization needs to connect with offer and pricing engines, and unified client data needs to support next-best-action. Across all four, agentic AI connects information, decisions, and execution within governance, risk, and compliance frameworks.
The business case should focus on commercial outcomes: retention, acquisition, share of wallet, deposits and assets, product penetration, client lifetime value, and cost to serve. Measures such as digital activation, engagement, recommendation acceptance, and relationship-manager adoption matter only when linked to those outcomes.
Where banks have moved the four dimensions together, implementations have shown a 30% to 50% increase in client meetings and touchpoints per relationship manager per day, 20% to 30% higher conversion among existing clients, 15% to 25% higher conversion for inbound prospects, and 10% to 15% higher fee margins.
The pattern also shows why sequencing matters. Decisioning technology without changes to relationship-manager behavior, or loyalty without the supporting data layer, can improve isolated metrics without translating into retention or share of wallet.
Banks need to design the commercial destination before choosing the route
Banks do not need to build the full vision at once, but they should design the destination first. A pragmatic route is to choose a few commercial priorities — such as investment share of wallet, attrition, or primary-bank conversion — and build the proposition, people, channels, personalization, data, AI, and performance management around them together.
If a bank does only two things, it should develop a truly holistic value proposition that rewards customers for consolidating financial needs in one place and leverage agentic systems to create a hyper-personalized client experience.
Banks that succeed will move from episodic product selling to creating value continuously at the moments that matter. That integrated commercial model is the bank’s real defense against unbundling.
