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.
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