In a recently released series of global articles, consulting firm KPMG examined the future of the banking experience, including key trends impacting the industry and insights on how to redefine business models for long-term sustainable growth. Below we look at some highlights from the series, including how the banking customer experience, in particular, is undergoing a massive transformation thanks to big data analytics and automation.

According to KPMG, today’s banks need to be resilient and agile, which requires being comfortable with disruption and new technologies. Fortunately, many of today’s banks and their leaders are taking action. Consider the following KPMG findings from its recent survey of banking CEOs:

  • 69% say growth relies on their ability to challenge and disrupt any business norm.
  • 72% are prioritizing more investment in buying new technology.
  • 58% say they have begun to use artificial intelligence (AI).
  • 63% admit they need to significantly improve their understanding of customers.
  • 65% say they need to improve innovation processes and execution.

When it comes to customer experience, the banking industry continues to raise the bar for digital engagement and personalization using big data analytics. This is being driven by a better ability to harness customer data across different systems, applications, and channels, then using that data to tailor service to the individual and better predict what they may want or need next. In order to do this, KPMG notes that disruptive banks have shifted from a model that relied solely on historical data to serve customers to one that is powered by AI and machine learning to predict what customers will want in the future.

To get there, many banks experimented with customer service bots and automation in an effort to reduce costs and move to a purely digital model. According to KPMG, these companies quickly found out that fully automated customer service with no available human assistance was not a technologically viable model—and one that most customers would not be willing to accept.

Instead, innovative banks are combining automation technologies with predictive analytics to help employees be more strategic and deliver a better customer experience. This includes assisting agents by suggesting the next best actions to complete a process, resolve an issue, or close a sale. Data integration platforms and the right analytics and machine learning tools are key to making this strategic business intelligence quickly available and actionable for employees. But that’s not all. According to KPMG, banks are also using machine learning and predictive analytics internally to improve operations, including better predicting ATM downtime and branch utilization models.

Whether you’re in the banking industry or other space undergoing massive digital transformation, KPMG offers four key focus areas to help you capitalize on the move to predictive business models. Take a look:

  1. Data Management: With most banks getting a handle on their internal data sources, next up is external sources that can help provide a more complete view of customers. According to KPMG, this will require companies to be more sophisticated about data management, security, and strategy.
  2. Customer Experience: While predictive analytics is helping make customer interactions more valuable, KPMG notes the need to connect in “back-end” data and automation with the front office to create great customer experiences.
  3. Employee Adoption: According to KPMG, companies can help encourage adoption and overcome any fears of automation by building awareness and communicating the value to both employees and customers.
  4. Innovation Ecosystem: KPMG also notes that banks are not expected to build all these new capabilities internally. However, companies should “think very carefully” about their technology and data ecosystem—including external sources—to ensure maximum value and flexibility. 

To learn more, you can check out the complete series of KPMG articles.

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