Finance in Focus: The power of personalized banking
As people look for ways of managing their money quickly, simply and effectively on a daily basis, banks are increasingly striving to provide a personalized experience that can help consumers take charge of their finances. In doing so, banks hope to instill loyalty by heightening levels of customer satisfaction.
Accordingly, financial institutions have invested heavily in technologies such as predictive analytics that can help them deliver personalized services in real time while taking into account individual customer transactions, events and data points. But how well are these solutions doing? In this discussion, hear how a study published by Jim Marous in the Digital Banking Report highlights the gaps between what consumers want and the services they are offered.
- Jim Marous, owner of the Digital Banking Report and copublisher of the Financial Brand
- David Gerbino, a fintech, bank and data-driven marketing consultant
- Matt Kinney, IBM offering manager for banking analytics solutions
Meet consumer expectations
In the first part of this podcast, tune in to hear Jim, David and Matt discuss the article “Banking Industry Still Falling Short of Consumer Expectations,” published on the Financial Brand:
- What types of engagement do consumers want to have with their financial institutions? How well are banks able to meet this need? What are some good examples of this?
- How can advanced analytics help banks transform their interactions with consumers?
- As consumers become increasingly digitally savvy, what kinds of competitive pressure are banks encountering from offerings originating with other industries, such as retail?
- Cognitive business is making headlines by promising to redefine relationships between humans and machines. How will the cognitive era change the ways that banks relate to their clients?
Just start now!
Keep listening to hear Jim tackle predictive analytics as he encourages banks to “think big, start small . . . just start now!”
- How are leading banks using predictive analytics? How effective has this approach been?
- When Jim mentions a shift from a mobile-first to an AI-first approach, what does that mean? How would such an approach affect bankers?
- What technological advances have triggered banks’ increasing adoption of predictive analytics?
- What pitfalls should banks avoid when using predictive analytics?
- How can banks connect high-level predictive and prescriptive analytics work with customers and extend it to the field?