PREDICTIVE ANALYTICS DEFINED: DATA + ANALYTICS = OPPORTUNITY
October 20, 2017
A tool for getting to know your members on a deeper level. A window of insight into how those members make decisions. A predictor for potential member behaviors and actions. Predictive analytics can be all these things and more for credit unions today, ultimately delivering the information needed to best serve members and to make the best business decisions.
So, what exactly is predictive analytics? Understanding the definition can be the first step for credit union leaders in embracing its power and setting the course for a more proactive and strategic approach to gain competitive advantage.
According to Tim Peterson, President of AdvantEdge Analytics, the concept is fairly simple: predictive analytics “uses statistical methods and data science techniques to suggest what the next action or result might be.”
There’s no shortage of member information available in today’s data-driven world. There for the taking, this data can be analyzed in an almost infinite number of ways to glean insights about current and prospective members. With these insights providing the foundation, credit unions can make predictions and create efficiencies around everything from member engagement to member departure and beyond. In short, Data + Analytics = Opportunity.
Taking a closer look at these components can help explain further:
- DATA. The data are the cold hard facts of the case, ready for dissection and interpretation. This could be anything from the defaults on loans to clicks on a Facebook post.
- ANALYTICS. Data is nothing without analysis. Sifting, winnowing and uncovering insights is the work of data scientists and data translators -- a quickly growing and valued field.
- OPPORTUNITY. Maximizing the opportunities revealed through the gathering and analyzing of data is the place where the payoff lives. The power of predictive analytics is lost if there is no action taken to close the loop and connect the dots.
Imagine the business benefits of knowing how likely a member is to leave the credit union or reduce services. Imagine predicting a member falling into financial despair. Imagine having a good idea of expected response rate on a promotional offer before that offer is made public. How would this information impact business decisions? With predictive analytics, there is no need to imagine. These key data points can be known and leveraged and deployed in a way that meets the high service expectations of members as well as the demands of an increasingly competitive business climate.
As Peterson concludes, “Fundamentally, at its core, it’s about using data and other methods and tools to make better business decisions.” Whether contracted externally or built internally, predictive analytics are available and scalable and ready to deliver a host of new insights and opportunities to credit unions of all shapes and sizes. Read our whitepaper, Predictive Analytics for Credit Unions, to learn more.