6 Member Touchpoints Transformed by Machine Learning

6 Member Touchpoints Transformed by Machine Learning

6 Member Touchpoints Transformed by Machine Learning

The artificial intelligence (AI) and machine learning sector is poised for explosive growth in the U.S. and worldwide.

In fact, research from McKinsey has found 45 percent of all work activities globally potentially could be automated by adapting currently demonstrated technology – and some 80 percent of that could be implemented with existing machine learning capabilities.

So what does this mean for credit unions, and how will machine learning impact – and improve – the member experience going forward?

According to Phong Q. Rock, Sr. VP, corporate strategy and business development for Feedzai, more than any other technology, today’s machine learning solutions are able to transform the consumer experience for credit union members – across the entire member lifecycle.

Here are six ways members stand to benefit:

  • #1 – Instant Onboarding

Machine learning can onboard members for new demand deposit or credit accounts by calculating instantly the fraud and credit risk related to an application and presenting a decision on the spot. “This capability brings current offline, human-based approaches into the 21st century, where customers expect responses immediately,” said Rock.

Fraud is a constantly evolving challenge for credit unions and their members. As fraudsters advance their tactics, so too must credit unions to stay at least one step ahead. According to Rock, “Machine learning has the potential to detect fraud – and stop it – far faster and more accurately than any human or technological resource available to financial institutions today. Leveraging the technology for this purpose gives members the confidence they need to use your cards freely – and to give them top-of-wallet status.”

  • #3 – Frictionless Day-to-Day Transactions

Credit unions can also use machine learning to improve routine transactional member experiences. “For example, machine-learning fraud detection systems can automatically increase the amount above which PIN entry is required for debit transactions – in real time – making transactions fast and effortless for cardholders,” said Rock.

  • #4 – Marketing Offers That Resonate

Machine learning is already revolutionizing the marketing approaches of major consumer brands – such as Amazon, Apple, Netflix and Uber – by processing volumes of consumer data and recommending the exact right offer to send at the exact right time.

“For credit unions, the technology can identify personalized interests and online browsing signals to choose the right time and offer for an individual member,” said Rock. “Consider a member who’s just entered a car dealership. Machine learning can pinpoint the individual’s geographical location coordinates, cross-reference them with the business listing at that location, verify the member’s credit eligibility and send out a push notification in the mobile banking app – instantly.”

  • #5 – Support Without the Wait

With machine learning, credit unions can deploy automated bots that field the most common questions members ask. “When integrated with customer relationship management (CRM) systems, these bots can also provide tailored recommendations, advice and answers to inquiries that would otherwise tap costly human resources – or force members to wait in long queues for the next available representative,” said Rock.

  • #6 – More Productive Branch Visits

Machine learning works best in the branch when it automates regular, predictable tasks – but also brings in the expertise of humans when needed.

Rock notes, “One of the ways credit unions can improve the branch experience for members is by deploying self-service kiosks. These stations can take care of simple jobs for members like depositing checks, accessing account information and making payment transfers. But an automated teller could also address more complex member needs – proposing solutions to their problems, providing simple wealth management advice and calling in the right branch employee when that is the best way to serve the member.”

On the Horizon: Decoding Natural Language

Rock emphasizes deep machine learning is still in its early stages, and improvements in its capabilities – and especially its ability to understand natural language – will quickly evolve.

“As AI and machine learning technologies advance, credit unions that leverage the technology will forge deeper relationships, improve their cross-selling success, increased revenues and enjoy all the benefits that come with providing a superior member experience,” he said. “Plus, the value delivered by the technology will only improve as time goes on – and as the analytics platforms deployed learn more about the members they are there to serve.”

To learn more about advances in artificial intelligence and machine learning technologies – including CO-OP’s new solution set to go live in 2017 – download our newest white paper, “A New Frontier: Machine Learning, Artificial Intelligence and Big Data” below.