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Efficiently Grow with Predictive Artificial Intelligence Engagement Modeling

How community banks and credit unions can easily increase business from their existing pool of account holders

In an industry first, Alkami is now leveraging artificial intelligence (AI) predictive modeling to help financial institutions identify highly engaged account holders, offer them products and services most likely to increase incremental revenue, and deepen their relationships in the process.

Alkami’s Engagement AI Predictive Model creates a full spectrum of account holder engagement. This new model helps financial institutions grow revenue from engaged accounts while retaining more at-risk accounts. This targeting can pay dividends beyond revenue growth, such as fostering strong brand ambassadors who are less price sensitive, The Financial Brand notes

How the Alkami Predictive AI Engagement Model Works

The Alkami Engagement model leverages the output of a model looking to predict attrition. The model is trained by looking at account holders who have previously closed accounts. From there, all account holders are scored based on their likelihood of attrition. Those that score high on the model are added to an “Attrition Risk Positive” audience. Those that scored low for attrition, on the other hand, are account holders who are highly engaged. The Alkami model creates audiences for the entire spectrum of engagement so that financial institution can target each level of engagement with appropriate messaging.   

Alkami’s AI Predictive Modeling considers metadata tags as it searches for account holders demonstrating behaviors significant to the outcome it is trained to predict. 

Now, what does this mean for Engagement specifically?

Imagine, you’re tasked with finding your most engaged account holders based on their behaviors with your products and their spending. Then, you must build an audience which includes lookalike account holders who have the potential to increase their engagement with your institution. And, in addition to that, also keep an eye on those who are statistically much less engaged, cater to them in a different way entirely, in order to reduce the risk of them eventually attriting. Could you accomplish this manually, in time?

Traditionally, it might take a year or more, using a team of data analysts and data scientists, to create a customized AI model for one such segment. Now, Alkami’s community and regional banks and credit union clients can have instant access to powerful predictive models to drive marketing campaigns. These include profiles of those most likely to seek auto loans, certificates of deposit, checking and savings accounts.

As part of the Engagement AI Predictive Model process, each account holder is placed into one of four groups:

  • Highly engaged with the Financial Institution. They use multiple products, maintain high balances and show lots of money movement in and out of accounts, including receiving ACH payments and making regular outgoing payments.
  • The two middle groups are made up of moderately engaged and somewhat disengaged account holders. Financial institutions can experiment with cross-sell marketing to these groups as well. Those that are becoming more engaged can be targeted with relevant add-on products and services, while those becoming less engaged can be targeted for retention even before they fall into the lowest group.
  • Highly disengaged and most at risk of attrition. This group can be targeted with re-engagement campaigns. Deploying such marketing in a way that significantly cuts account churn rates is a big benefit to financial institutions. The more accounts retained, the more customer acquisition expense saved. As Leher notes, “Alkami’s full-spectrum engagement model doesn’t preclude a financial institution from trying to stem attrition—that still has value.” In fact, a recent Alkami analysis of financial institution data found that account holders with the lowest engagement were 15x more likely, on average, to close their accounts than those with the highest engagement.

It’s often said that the best way to grow a business is by focusing on making the best customers—your loyal consumers—more profitable. As Leher notes, “With the new Engagement AI Model, banks and credit unions can focus on growing the business of people who are already receptive to what the financial institution is giving them and are most likely to expand their banking relationship.”

Request more information about Alkami’s AI Predictive Modeling capabilities here.

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