Three credit union examples:

The $182-million Lubbock Texas-based Texas Tech Federal Credit, which recently merged two credit unions, replaced merger services provided by its core data processor with Foxtrot RPA. "Over the next couple of years, we'll be able to reduce the cost of mergers by about 80%," Pranay Siri, the credit union's business intelligence analyst said.
The $1.04 billion Kalamazoo, Mich. based Consumers Credit Union actively engaged in selling its loans, typically bundling as many as 500 loans for sale at one time. Prior to deploying Foxtrot, the credit union manually prepared each loan for sale. "We've been able to eliminate several days' worth of manual data entry for every group of loans we sell," That inevitably leads to more loans sold in a shorter period.
The $2.5 billion Redwood City, Calif.-based Provident Credit Union, began using Foxtrot to close inactive credit and debit cards. However, according to document and image retention manager Amanda Seals, its greatest value is in the escheatment process, where she explained they cannot have a single error. "Sure, Foxtrot saves us many, many hours of manual processing, but accuracy is just as important. We've never had an error processing escheatments with Foxtrot."

The usage of AI, and its subset machine learning, is a rising trend among financial institutions as they seek to improve customer satisfaction, reduce inefficiencies and fight fraud. But some of the expectations are somewhat overstated, at least currently, according to Milam. He explained real AI, involving machines learning based on data and then altering its algorithms and tables accordingly, is hard to achieve. "I'm pretty sure that very little actual AI in production today, but it is evolving."

Instant Insights /

ROI-botic Automation Helping Credit Unions' Bottom Line

Related Stories

Recommended For You