Data and analytics are at the core of organizations’ digital banking transformation efforts. In the accelerating digital economy, banks and credit unions are compelled to collect data from disparate sources and generate insights that are forward-looking and progressive to remain competitive. These insights drive improved efficiencies, better revenue opportunities, and enhanced customer experiences.

With a hyper-connected ecosystem, each transaction and interaction create massive datasets. The collection and use of this data continues to evolve in scope and potential, helping create new business models and driving a customer-centric approach to digital banking transformation. Despite the importance of data and insights, most financial institutions still lack the ability to leverage insights to drive decisions.

That does not mean that there is not the desire to improve. According to Forrester, 85% of institutions want to improve their use of data insights in their decision making, but 91% report that improving the use of data insights in decision making is challenging.

Data and advanced analytics allow financial institutions to improve back-office operations, allocate resources, build new pro­ducts and services and drive increased customer engagement at a time when connectivity to the consumer is more important than ever. A data foundation also enables financial institutions to create benchmarks for digital banking transformation progress.

Managing the collection and use of data requires a strong data governance program, quality data and an understanding of both the owners and users of the data. Without confidence across the organization around the quality of the data being used, any digital banking transformation process is at risk. Investing time and effort (up-front) around data governance, advanced analytics and machine learning will have a significant pay-off, including increased efficiency, improved customer experiences and greater revenues.

To achieve the vast potential of an integrated data strategy, banking organizations need to be built with cloud-computing infrastructures that allow for the combination of data assets and the use of AI algorithms to deliver better quality, improved efficiency, seamless delivery of services, proactive recommendations and enhanced risk mitigation. While most organizations will begin with internal data, the real power will be the integration of external data and insights, including those from open banking APIs.

In addition to increasing efficiency and improving decision making, using AI and applied analytics in combination with advanced technologies will enable current staff to assume higher level roles within the organization. By humanizing digital banking transformation, banks and credit unions will be able to develop the digital expertise across the organization, thereby accelerating the level of employee transformation required to succeed in the future.

This white paper explores the application of data and AI for improving business models and delivering enhanced customer experiences. This analysis uses insights collected from financial institutions globally combined with insights from third-party organizations. The paper reveals the challenges and opportunities available with the building of a data strategy as well as best practices in the industry.

We appreciate the support of IBM in the development of this research and the sharing of their insights which were key in the development of recommendations.