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Imagine a scenario where your bank or credit union customer turns to an external AI financial assistant and asks, “What can my idle cash do this weekend?” Would your institution be among the top recommendations? Or what if an independent AI proactively suggests, “Hey, you won’t need this money for a week. Let me sweep it into a higher-yielding option than your checking account for a few days?”
This deceptively simple prompt – “optimize my idle cash” – should send shivers down the spine of every banker, warns Michael Abbott, global banking and capital markets lead at Accenture. The implications extend beyond just deposit accounts, encompassing recommendations for mortgages, consumer loans, and credit cards, with the potential for AI to even execute these transactions with customer permission.
The Rising Tide of AI in Personal Finance: Key Insights
Accenture’s Future of Banking Experience Survey reveals a significant shift in consumer attitudes towards AI in finance:
- A striking 65% of individuals are open to leveraging a ChatGPT-type financial assistant within a Generative AI (GenAI) platform or a digital wallet.
- An even higher 71% would prefer to see an AI assistant integrated directly into their primary bank’s mobile application.
- While eager for AI assistance, consumers demand control: 82% want to approve every AI action, and nearly as many desire a one-tap option to pause any GenAI activity.
- Trust remains high for banks: 86% of respondents trust their bank to provide smart AI assistants, compared to 49% who would trust other GenAI platform providers.
- Beyond banking, 54% are ready to use GenAI within their bank’s app for non-financial tasks like booking travel or grocery shopping.
As more consumers seek financial guidance from large language models, a critical challenge emerges: none of these powerful AI advisors are currently on banks’ payrolls. Abbott emphasizes that while the risks of this new technology are undeniable, it simultaneously presents unprecedented opportunities for institutions willing to adapt their strategies.
Beyond Balances: The Multifaceted Risks for Financial Institutions
The encroachment of AI into financial decision-making isn’t merely about immediate loss of deposits or loan business. As AI’s influence deepens, banks and credit unions face a spectrum of risks:
- Brand Erosion: The traditional connection between customers and bank brands can weaken.
- Channel Disintermediation: Control over where and how financial business takes place shifts away from the bank.
- Customer Connection: The direct relationship between consumers/businesses and financial services becomes mediated by AI.
- Decision Authority: Over time, the ultimate decision-making power in a customer’s financial interests could increasingly reside with AI rather than the individual or their traditional bank.
This transition isn’t entirely new; “brand disintermediation” has been evident for years. Consider a consumer asking, “Do you take Apple Pay?” The bank issuing the card embedded in that digital wallet loses direct brand visibility. Generative AI, alongside other advancements like wearable devices and evolving branch formats, is further accelerating this shift in control over the customer experience.
Five Strategic Responses for Banks in the AI Era
Michael Abbott outlines critical strategic pathways for financial institutions to navigate the AI-driven landscape:
- Join the AI Wave: Banks must recognize that large language models are fundamentally changing search. To remain relevant, institutions must be prepared to engage clients where they are now seeking information – directly with AI platforms like GPT.
- Leverage Traditional Strengths: For many, especially community banks, human relationship management remains a core asset. Banks should lean into this strength, particularly for small business accounts, but be ready to modernize and repackage these familiar offerings.
- Lead with AI Advisors: Instead of playing defense, banks can proactively develop and run their own sophisticated AI-driven financial advisors, becoming the preferred hub for customer guidance.
- Reinvent Virtual Assistants: Existing virtual assistants need a significant upgrade. Banks should infuse next-generation AI into these tools, designing for future capabilities rather than immediate obsolescence.
- Become an AI “Manufacturer”: This strategy involves banks focusing on their core regulated product management (design, pricing, risk, compliance, fulfillment) while external AI assistants handle the customer interface and orchestrate comparisons across multiple providers. This is an evolution of white-label cards and Banking-as-a-Service models.
Abbott suggests that many institutions will likely adopt a combination of these strategies.
Embrace Generative Engine Optimization (GEO) for Visibility
In today’s dynamic environment, even seemingly strong customer relationships can be vulnerable. A small business CFO, for instance, might query a GenAI model: “I’m looking for a small business loan. I’ve got $5 million in sales, $2 million in receivables. I need an accounts receivable loan for $750,000. Can you give me a recommendation?”
To be competitive, banks must proactively ensure their institution is visible to these AI models. This requires focusing on Generative Engine Optimization (GEO) and other advanced digital tools. Without it, banks risk becoming invisible both to potential new customers seeking services via AI and to existing customers exploring alternatives.
This may even necessitate maintaining a parallel website specifically optimized for GenAI to access institutional data and offerings. Bankers must critically examine why a customer wouldn’t simply contact their relationship manager directly, questioning “every loan I’m not getting – and why.” Furthermore, product strategies must evolve to encourage customers to consolidate their deposit and borrowing business with the same institution.
Transform Your Mobile App into a Virtual Relationship Manager
A crucial, proactive strategy involves transforming your bank’s mobile application into the primary AI hub for customer guidance. Abbott describes many current bank mobile apps as “functionally correct, but emotionally void” – akin to banking with a vending machine.
The ideal mobile app should function as your institution’s relationship manager: a source of advice, a platform for seamless text conversations with bankers, and a tool that actively thinks for the customer, helping them manage and optimize their finances. It needs to be personalized, remember past interactions, and effectively solve problems. The goal is to bring the human-centric relationship management that banks have perfected over decades into the AI world.
Furthermore, institutions must look beyond today’s GenAI capabilities and build towards the next frontier: agentic AI tools. As Abbott notes, “Feeling like you’re texting with your banker, that’s just the low bar.” Customers will soon expect assistants as responsive and intuitive as commercial GPTs for all their financial decisions.
As a bonus, institutions that master this integration can even curate other financial brands within their AI experience, effectively becoming a marketplace facilitator.
Becoming the “Manufacturer” in an AI-Driven Ecosystem
While banks cherish their brands, Abbott suggests that solely focusing on brand-led business may not be the only viable path forward. Many institutions already operate through B2B2C and B2B2B arrangements. As GenAI increasingly orchestrates financial interactions, some banks may find success by embracing a “manufacturer” role.
In this model, the bank retains ownership of crucial regulated functions: product management, design, pricing, risk assessment, compliance, and fulfillment. Meanwhile, external AI assistants take charge of the customer interface, comparing and orchestrating various offerings from multiple providers. This essentially positions the bank as one of several suppliers stocking the shelves of a virtual financial supermarket.
A key decision for banks pursuing this path is determining the acceptable level of brand disintermediation and how liability will be shared when an independent AI agent mediates between the bank and the end customer.
Source: Thefinancialbrand.com