Research & Insights
In part one in a series of articles separating fiction from truth when it comes to AI, AdvantEdge Analytics' Chief Strategy and Business Development Officer Shazia Manus tackles the misconception that AI will one day overpower humans.
Data is coming at us fast and furiously, and the volume of data being aggregated today is almost incomprehensible. By hosting Innovation Summit, our goal was to help our credit union partners, and our own team members, embrace the art of possibility with the science of data.
The digital footprint each consumer produces has grown exponentially over the last 10 to 15 years. Combined with advances in data analytics, businesses now have the ability to develop insights like never before, and they are investing heavily in that strategy.
The key to improving and transforming your credit union lies in gaining actionable insights from the best data. When employed effectively, it results in a new kind of lead generation, a different approach to cross-sell, better life event marketing, and more.
A little while ago, I was giving a talk on predictive analytics, and a young professional in the audience interrupted me: “What exactly is a data scientist, anyway?” he asked. Given the number of people who suddenly perked up to hear the answer, I realized he wasn’t the only one in the dark. If you’re wondering, too, allow me to shine a little light science on the topic. Let’s start with data science.
As more credit unions design and test their approaches to data analytics, a few common traps that slow success are emerging. During their talk at the 2018 NAFCU Annual Conference, our own Tim Peterson and Shazia Manus talked through five of these pitfalls and offered advice for side-stepping them.