Issuers and banking institutions have access to large amounts of customer data. This includes data on payment habits, investment activities, purchases and so on. And irrespective of how customers chose to interact with different brands – they expect uniform and personalized customer experiences. While retail and hospitality industries are constantly pushing the envelope in orchestrating personalized experiences for their customers, banking institutions have tremendous potential for improving personalization.
In this article for PaymentSource, Sanjay Bhakta, Senior Director of Solutions, Ness Digital Engineering, discusses how the use of right tools and technologies like data, analytical models, and AI and machine learning can help banking institutions improve personalization for their customers.
“Personalization requires a wide spectrum of offerings that must be delivered via a frictionless, seamless, and pleasurable experience to customers. Orchestrating that “experience” and providing the content for the offerings and the operational frameworks to deliver it are distinctly “non-core” activities and present a real challenge outside the comfort of “Business as Usual,” notes Sanjay.