By John San Filippo
Finopotamus was onsite at Money20/20 USA in Las Vegas Oct. 24-27. Co-founder John San Filippo interviewed more than two dozen technology experts on a wide range of topics. The results of these interviews are presented in this series called “The Voices of Money20/20.”
“Every single credit union website today tells the same story to every visitor, regardless of who they are,” Craig McLaughlin, CEO of Finalytics.AI, told Finopotamus. “It's the exact opposite of what would happen with your best member service representative in the branch. The MSR can quickly judge based on the questions the member asks, what's the right thing to present to this member?”
In the COVID-19, all-digital era, the challenge according to McLaughlin is replicating that dynamic experience in a digital setting. That’s where artificial intelligence (AI) comes in.
“We use data and artificial intelligence to dynamically change the digital experience based on behavior of that particular user,” said McLaughlin. “For the member, they just see that the credit union cares about them and is listening to them. In other words, it seems to be an experience tailored to their needs.”
McLaughlin offered the example of someone looking for a mortgage loan. He said that on average, applying for a mortgage loan online requires 2.7 visits comprised of 13 different pages on the credit union’s website. By dynamically adjusting the experience according to each action made by the member, the Finalytics platform can reduce both the time and complexity of this process.
How It Works
“What we’re doing is tracking the behavior of a visitor and we're picking up on attributes like their geographic location as they're coming into the site,” said McLaughlin. “Based on those attributes, we're dynamically re-rendering the experience for that individual visitor.” He added that Finalytics looks only at behaviors, not actual account information. That means the system works equally well on both sides of a member’s login credentials.
“We're moving away from cookies,” said McLaughlin when asked how the system keeps track of a member’s behavior. “We're using the local storage of the browser. And we're also piggybacking on the web analytics that the credit union is using. A lot of credit unions use Google analytics, some are using Adobe analytics. We're piggybacking on that data set so that we can see who is a repeat visitor. When somebody comes to the site, we're looking at their attributes. And based on that, we're making predictions about what product they might be interested in, what service or support they might need.”
AI Versus Old-School Predictive Analytics
Finopotamus then asked McLaughlin the difference between an AI-driven system like Finalytics and the predictive analytics that credit unions have been using for 10 years or longer.
“If you go by the bare bone definitions of it, predictive analytics are most commonly doing an analysis and looking at historical data, then making a forecast about the future. That’s it, you’re done. You've made your forecast,” responded McLaughlin. “I think the key difference with the machine learning aspect of it is, as it's seeing more people convert or drop out of the funnel, it's changing those signals that were used for the prediction.” In other words, the system keeps getting better and better at making those predictions.