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FICO survey reveals APAC banks lag in hyper-personalisation

Global analytics leader FICO has unveiled findings from a recent survey of senior banking leaders across Asia Pacific, highlighting significant challenges in achieving hyper-personalisation. Despite 88% of banks employing predictive analytics to anticipate customer needs, a mere 11% rate their strategies as highly advanced, underscoring a struggle to convert data into actionable insights.

The survey, conducted during FICO’s Platform Experience event in Singapore, involved over 30 senior executives and C-suite leaders. It revealed that 72% of banks have siloed or partially integrated customer communication channels, hindering seamless engagement. Additionally, 50% of respondents admitted that no more than half of their customer-facing decisions, such as credit approvals and fraud alerts, are automated.

Dattu Kompella, managing director in Asia Pacific for FICO, noted, “Consumers now expect the same level of personalisation from their banks as they do from Netflix and Amazon. With most banks still struggling to meet these expectations, those that succeed will gain a decisive edge in a market where customer experience is the ultimate differentiator.”

The survey also highlighted that whilst 43% of banks significantly leverage real-time data for customer insights, most remain at minimal or moderate adoption levels. Only 37% reported extensive use of predictive analytics, indicating limited maturity despite broad adoption.

To bridge this gap, banks are encouraged to unify data and decision-making processes across the customer lifecycle. Kompella added, “By consolidating activities, behaviours, and preferences into a single decisioning platform, banks can act on insights in real-time, driving deeper engagement and loyalty.”

The findings emphasise the urgent need for banks to enhance their personalisation efforts to remain competitive in an increasingly customer-centric market.

This story was selected and published by a human editor, with content adapted from original press material using AI tools. Spot an error? Report it here.

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