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Gen 2.0 Customer Analytics in Banking: IBM Operationalizes its Capabilities

NelsonHall attended the IBM Forum for Financial Services event in New York this past week, which focused on how bank customers are using IBM’s cognitive offerings. IBM has been investing heavily in services and technologies to enable deeper insight into financial institutions’ customers, starting 18 months ago with the development of Watson-based analytic assets.

IBM’s thesis is that it can segment financial services customers in a better fashion than traditional institutions have done in the past. Its approach is to segment customers by their individual preferences rather than by the institution’s preferences, i.e. asking the question ‘what does the person want or need?’ rather than ‘is this a high net worth customer or low net worth customer?’. To enable this, IBM is utilizing its repository of analytic learnings and clients’ customer databases, using its dynamic segmentation tools to identify changes in customer needs based on transaction history, which then enables banks to offer relevant products to meet emerging consumer needs.

In Generation 1.0 of IBM’s customer analytics for the financial services industry, it engaged clients in around 26 PoCs to establish new customer segmentation and improve both the customer experience and the clients’ sales. Of these POCs, around18 have moved to full production. The others are not funded at this time due to required capital commitment versus hurdle rates many of these on-hold projects will be revisited now that IBM has developed a cloud-based delivery system with a lower price point than an internally delivered project.   

At the forum, IBM announced Customer Insight 2.0, part of its financial services customer analytics offerings. IBM’s new capabilities include:

  • Prebuilt solutions based on experience to date
  • Cloud-based delivery to lower adoption costs, including private cloud implementation to address client security issues
  • APIs to integrate legacy systems into emerging technologies
  • Customer prebuilt profiles (nine life event profiles based on research and PoCs to date).

A key question that the PoCs have been seeking to answer is what life events and personality traits are driving customer behavior and how can a bank support the customer in dealing with those issues. Clients buying these services from IBM have been focused on single bank product lines, but are looking to maximize overall customer retention and life cycle value. Ultimately, better cross-selling of existing customers can only succeed if those customers have a high satisfaction level. Thus, immediate sales performance is not as important as customer satisfaction. 

IBM has developed a way of looking at customers that is less institution-centric and more consumer-centric. It uses its Watson capabilities and industry experience to enable better usage of a bank’s transaction data to understand its own customers. IBM uses its dynamic segmentation capabilities to identify changes in consumer needs, which can trigger changes in buying behavior that the bank can fulfill. IBM provides the infrastructure to deliver these now productized capabilities so that banks can use them to drive revenue and, more importantly, customer retention, at a lower price point than would otherwise be possible.

While further buildout of this offering will happen, banks using it are now can begin redefining their relationships with their customers for the digital age.

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