3 ways AI and machine learning can boost your card portfolio

According to Forbes Magazine, global revenue derived from artificial intelligence (AI) for enterprise applications is projected to grow at more than 52 percent annually, from “$1.62B in 2018 to $31.2B in 2025.” The share of U.S. jobs requiring AI skills has grown “4.5X since 2013.” And 84 percent of enterprises “believe investing in AI will lead to greater competitive advantages.”

While AI, machine learning and related technologies are poised to transform the future of fintech, what do these tools mean for credit unions, and how can they be applied to unleash growth opportunities?

“AI presents an enormous opportunity for credit unions to transform the member experience on many levels,” said Fotis Konstantinidis, SVP of Fraud Products and Data Scientist for CO-OP.  “By analyzing millions of data points about your members’ spending and transaction history, a sophisticated AI platform can help you uncover deep insights about your members and engage with them on a more personal level.”

Take card portfolios, for example. Credit unions can leverage the power of AI in varying degrees of complexity to gather and analyze member data points ranging from membership accounts, activation rates and number of transactions by category (PIN, signature and credit) to average ticket, revenue and expense. Benchmarking this type of data can help credit unions develop more informed penetration, activation and usage (PAU) strategies – and execute more successful marketing campaigns as a result.

 

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