Banks Struggle to Reap AI Benefits Due to Outdated Systems: McKinsey

The report, titled "The AI-powered bank: Rewiring for excellence in customer care," said that while AI has become a "centerpiece of investment" in banking customer operations, the expected gains are not materialising across the industry.

"As early adopters move toward broader AI implementation, the gap between leaders and laggards is no longer defined by the tools they buy, but by the operating models they build," the report noted.

According to McKinsey, the problem is not with the technology itself, but with how banks are using it. "Most banks are not failing because their technology is weak; they are failing because they are layering AI onto legacy operating models... and automating broken processes rather than redesigning them," the report said.

Banks have been investing heavily in tools such as voice bots, agent copilots and real-time analytics, with the promise of reducing costs by 30 to 45 per cent and improving customer experience. However, these benefits have largely remained unrealised.

One key issue highlighted in the report is that banks are trying to automate customer service without fully understanding why customers are reaching out in the first place. "If banks don't capture these root causes, AI simply amplifies existing inefficiencies," it said.

For instance, what appears to be a simple query, like checking account balance, often turns out to be a deeper issue, such as unrecognised transactions or missing deposits, which AI systems alone may not resolve effectively.

The report also pointed to a disconnect between technology teams and business leadership. While AI pilots are often measured by technical success, such as accuracy or containment rates, executives focus on financial outcomes like cost per interaction and customer satisfaction.

"A bot might achieve a 90 percent containment rate... but if those customers call back three days later because the root cause wasn't addressed, the total cost per contact can actually increase," the report said.

Another major hurdle is regulatory and risk-related constraints, which often delay or limit the scaling of AI solutions. "True value is unlocked only when risk and compliance are treated as integrated design constraints rather than a final gate to be cleared," McKinsey said.

The report emphasised that banks need a fundamental shift in approach, moving from simply deploying AI tools to redesigning their operations around them. "AI implementation is not a chatbot initiative... it is a fundamental operating model transformation," it said.

According to McKinsey, banks that successfully integrate AI into their processes can see significant gains, including a 25 to 40 per cent reduction in customer calls, a 10 to 20 per cent drop in handling time, and improved customer satisfaction.

However, the report warned that success will depend on whether banks are willing to overhaul their legacy systems. "Success will not be defined by which banks have the most advanced AI, but by which have the courage to dismantle the legacy structures that prevent AI from delivering strategic value," it added.

- ANI