Why Retail Banks Are Deploying AI for the Wrong Reasons (and How to Fix It)

Retail banking is standing at a critical crossroads, and many executives are asking the wrong questions as they navigate the shift toward artificial intelligence. While financial institutions pour billions into generative AI (GenAI), their current strategies may actually be pushing customers away rather than drawing them in.

According to Alyson Clarke, principal analyst at Forrester, banks risk turning their products and services into mere commodities. As consumer-facing AI tools become mainstream, traditional banking relationships could be disrupted. If banks do not adapt, third-party platforms—including tech giants like Apple—could easily step in as the primary interface for consumer financial decisions.

The Consumer Pivot to Financial GenAI

The demand for AI-driven financial advice is growing rapidly. Forrester previously estimated that more than half of consumers under the age of 50 would utilize GenAI tools to help guide their financial decisions.

Interestingly, Forrester’s research reveals a paradox: even though users often trust AI less as they experience its limitations, such as “hallucinations” and errors, they remain committed to using it. Consumers actively want these tools to succeed because they provide something banks traditionally haven’t: accessible, low-cost, personalized guidance.

Historically, personalized financial advisory services were reserved for high-net-worth individuals. The average retail consumer was left with generic product brochures. GenAI has democratized this advice, offering the one-on-one personalization that banks have long promised but rarely delivered at scale.

The Misalignment: Efficiency vs. Relationships

The primary issue with current banking AI strategies lies in how financial institutions measure success. Many banks focus heavily on traditional metrics, such as:

• Reducing operational costs
• Accelerating customer service resolution times
• Driving adoption of self-service digital channels
• Boosting immediate product sales

While these metrics improve short-term productivity, they fail to build customer loyalty. As Forrester points out, “Efficiency is not a relationship strategy.” Treat AI purely as a cost-cutting tool, and you risk eroding the very customer relationships that prevent churn.

The Impartiality Challenge and the Apple Threat

When consumers use third-party GenAI tools, they expect impartial advice. An independent AI will scan the entire market to find the best interest rates or credit card rewards.

A bank’s proprietary AI, by contrast, is highly unlikely to recommend a competitor’s product. This inherent bias puts bank-owned AI tools at a competitive disadvantage.

The threat becomes even more pronounced with the evolution of major tech ecosystems. As Apple integrates advanced AI deeply into iOS and the Apple Wallet, Siri could easily transition into a highly sophisticated personal financial assistant. Because these tools can securely analyze a user’s entire transaction history across multiple institutions, they are poised to become the ultimate hub for daily financial planning.

How Banks Can Compete in the GenAI Era

To survive this disruption, banks must change how they deploy AI. Instead of building tools that simply push products, banks must create digital “personal bankers” that leverage their most valuable asset: proprietary customer data.

Traditional banks sit on a goldmine of transaction histories, savings habits, and credit behaviors. An external AI tool does not inherently possess this deep, historical context. By safely utilizing this first-party data, banks can deliver hyper-personalized, context-aware advice that third-party alternatives cannot easily replicate.

A Shift in Metrics Is Required

To successfully transition AI from a basic chatbot to a trusted financial advisor, retail banks must update their Key Performance Indicators (KPIs). Financial institutions should move away from purely transactional metrics and begin tracking relationship health indicators, such as:

• Long-term customer retention and loyalty
• Depth of customer engagement
• Overall share of wallet
• The volume of proactive financial health check-ins initiated by users

Shifting this focus requires patience. Prioritizing trust over immediate sales will not show instant results on quarterly balance sheets. However, in the long run, consumers who trust their bank’s AI advisor will be far more willing to share proprietary data and remain loyal, even if competitor pricing is slightly more favorable.

Source: thefinancialbrand.com