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Customer analytics help banks score big

Vice President, Banking Analytics Solutions, IBM

It's safe to say that technology has driven greater change in the financial services industry over the last decade than during any other time in history. Mobile deposits, over-the-air transactions and instant comparisons have quickly emerged as the new normal, while smartphone-enabled marketing and support have changed the face of customer experience. Customers educate themselves before buying, and they expect smarter interactions. Therefore, banks are realizing the value of analytics in banking to understand customer behavior in the increasingly complex digital world.

Customers in the driver's seat

In fact, customers are increasingly in control of their relationships with retails and service providers. As a result, banks must become far more sophisticated about how they approach and interact with consumers.

At the center of everything? Banking customer analytics. By combining legacy data and real-time information gathered from social media streams, mobile devices, beacons and other devices in the Internet of Things, it's possible to take banking analytics to a new level.

Banking customer analytics can revolutionize the way financial institutions interact -- creatings opportunities for new products and new business models. By moving beyond broad demographic segments and embracing more personalized and contextually relevant approaches, organizations can slide the dial from reactive customer service to proactive and predictive offerings.

Innovation through banking customer analytics

Financial institutions typically hold a wealth of historical data about transactions and customers. For example, spend data, which consists of what, when and where we buy, gives banks a behavioral model that can segment customers in new ways. By eliminating siloed data and instead sharing data from consumer, family, business and wealth accounts, banks can gain new insights. Banks can also supplement their data with other non-traditional, frequently cloud-based sources. Social sentiments and Internet of Things data are a good place to start, while eather, trends and news events are also gaining ground as significant sources of business insight. The underlying goal is to take data collection and analysis from a one-dimensional transactional activity to a multi-dimensional tool that delivers new insights and helps build a more personalized approach to customer interactions.

Ideally, retail banking analytics becomes the new driver for a bank's innovation agenda. For example, with predictive analytics, a bank might predicte when a customer is thinking about moving or buying a new car, and then send targeted information and promotions. The organization might also use banking customer analytics tools to understand what day of the week and time of the day a person is most receptive to messages. In a best-case scenario, customers will no longer view interactions such as marketing messages as intrusions or "noise," but rather as something that adds value to their day-to-day routine.

Steps to better banking analytics

https://kapost-files-prod.s3.amazonaws.com/uploads/direct/1443109633-13-6056/BankingCustomerAnalytics_Blog.jpgHowever, pulling all the pieces together to create a more advanced banking customer analytics platform isn't a simple task. Banks need to focus on key steps:

  1. Pushing out behaviorial analytics capabilities to line-of-business managers and other relevant parties so they are equipped to ask questions and make important decisions in real-time.
  2. Breaking down data silos and better integrating data across the enterprise from analysts and data scientists who understand both business opportunities and IT capabilities.
  3. Extending beyond traditional structured data to include unstructured sources, such as social media sentiment, real-time location services, keyword and semantic analysis of contact center communications, and machine and Internet of Things data.
  4. Selecting solutions and IT platforms that tap into the power of cloud computing and enable data to flow across systems and databases silos.

In the end, banks (or their industry-disrupting competitors) that master today's data environment will attract customers who are more educated about products and services, more loyal, more engaged with the brand and, ultimately, more profitable. Make sure that your bank is the one scoring big with banking analytics by signing up for a live demo of IBM Behavior Based Customer Insight for Banking, which helps banks more deeply understand customer needs and propensities, anticipate life events and provide a personalized customer experience.