Banks need to be aware of trends in data analytics that are driving decision-making and customer experience so they can draft an effective data plan. Doing so will allow them to compete with the biggest banks and non-bank technology competitors that are already using internal customer data to predict behavior and prescribe actions to grow those relationships. These approaches leverage concepts like machine learning and artificial intelligence — buzzwords that may seem intimidating but are processes and approaches that can leverage existing information to grow and deepen customer relationship and profitability.
10 Data and Analytics Trends Banks Should Consider
Current trends in analytics include focusing on the customer’s experience, using artificial intelligence and machine learning in analysis, and storing and organizing information in ways that reduce risk. Banks also need to know about threats like cybersecurity, long-term developments like leveraging blockchain, and how to build a governance program around the process. Knowing the trends can help companies make educated choices when implementing a data strategy.
How Banks Can Make Use of Data-Driven Customer Insight
Banks can use machine learning and artificial intelligence to gain insights into customer behavior and inform their decisions. These data-driven approaches can efficiently analyze the likeliness of future events, as well as suggest actions that would increase or decrease that likeliness. Many institutions recognize the need for new technical capabilities to improve their customer insight, but a significant percentage struggle to embrace or prioritize the technology among other priorities at their bank. These institutions have an opportunity to establish a data strategy, map out their internal information and establish appropriate governance that surrounds the process.