Stronger use of customer feedback, service data and segmentation has helped improve response times, complaint
resolution and support for priority customer groups
Singapore’s Oversea-Chinese Banking Corporation (OCBC) is using service analytics to make customer engagement more responsive and operationally useful. In 2024, the bank brought together operational data, customer feedback, demographic information and business data to help teams respond faster and offer direct support more accurately.
In retail banking, customer engagement is often shaped through routine interactions rather than headline moments. It shows up in contact-centre calls, complaint handling, follow-up requests, fulfilment delays and the quality of service recovery. OCBC’s programme focuses on using those signals more effectively so teams can act sooner and with better precision.
Strategic dashboards
One of the clearest changes is displayed in the contact centre and service functions. OCBC has developed dashboards that show shifts in call intent, rising wait times, complaint patterns and repeated requests. That gives teams a better view of where pressure is building and allows them to redeploy resources more quickly, identify weak self-service journeys or poor communications and deal with issues before they escalate further.
The bank has also expanded its use of unsolicited customer feedback by reading it alongside customer and business data. That has helped distinguish one-off complaints from wider process or service-readiness problems. It has also given frontline and service teams a stronger basis for earlier intervention and more targeted recovery. Analytics is also being used to reduce manual work. OCBC has automated repetitive review and checking processes, cutting routine manual work by 63%, freeing staff to spend more time on investigation, prevention and service improvement.
Generative AI
Generative AI is being applied to specific service tasks. The bank uses it to identify repeated complaints from the same customer and to improve classification of complaint themes. Human review remains part of the process, but the tools have helped speed up analysis and made recurring patterns easier to detect.
The programme has also had a stronger segmentation element than a standard service improvement effort. OCBC is using service analytics to better understand the needs of higher-net-worth (HNW), elderly and offshore customers. That includes identifying dissatisfaction with relationship managers, finding friction points in premium services and examining complaint patterns among older customers.
Strong results
The results point to a more responsive service model. OCBC has improved contact-centre performance, complaint handling and operational efficiency, while using customer data to identify recurring issues earlier and support service teams more effectively. The programme has also contributed to a 94% overall customer satisfaction rate, underlining the impact of a more targeted and data-led approach to service delivery.
Overall customer satisfaction has risen to 94% overall customer satisfaction rate. This suggests the bank is using data to make customer engagement more targeted and responsive rather than simply more automated.
OCBC is not using analytics as a reporting layer sitting above the business. It is employing customer signals to shape staffing decisions, improve complaint handling, reduce manual processes and sharpen customer support. That makes the story more credible than a simple claim of better dashboards or more digital channels.