Deep Dive: How AI Is Changing The CU Landscape
Credit Unions

Deep Dive: How AI Is Changing The CU Landscape

A Deep Dive that explores how credit unions are utilizing artificial intelligence for fraud protection and to create more engaging customer experiences.

As member-facing organizations, credit unions consider trust essential to survival. Members must feel confident that their CUs can be trusted to safeguard both their financial assets and personal data. They are even likely to abandon their credit unions for competitors if such relationships do not exist. 

Maintaining this trust is all the more challenging as cybercrimes become increasingly common. A study conducted last year found that 71 percent of U.S. consumers are afraid hackers might access their personal, credit card or financial information, and that 67 percent were afraid of identity theft. These figures considerably outweighed those of non-digital crimes like burglary and car theft, which came in at 40 percent and 37 percent, respectively. 

Thankfully, significant shares of CUs are taking these security threats seriously. The May 2019 PYMNTS Credit Union Innovation Playbook found that 79.4 percent of credit union executives identified anti-money laundering improvements as their top innovation priority, 62.7 percent cited data security and 60.8 percent noted anti-fraud initiatives. 

Many credit unions are turning to advanced learning technologies like AI to address this broad range of security concerns. AI-based solutions automatically review relevant data to verify users’ identities and accumulate profile information that can help FIs more effectively ward off bad actors. The following Deep Dive explores how such technology is changing the CU landscape. 

A Growing Role for AI Tech

Numerous FIs have implemented AI solutions to ensure that transactions remain fraud-free over the last few years, but the technology can also improve member engagement through chatbots and virtual assistants. 

AI-powered chatbots are equipped to help members navigate credit unions’ websites or mobile apps to address their immediate financial needs and handle administrative responsibilities. They can also help free up CU employees’ valuable time, enabling them to be more focused on resolving complex issues and other member-facing tasks. 

Using AI-powered chatbots also presents revenue-saving potential for credit unions. These services are on track to save roughly $8 billion annually by 2022, by some estimates, and do so across healthcare, banking and various other sectors. Adoption could help reduce administrative costs by an estimated 22 percent as well, tapped to interpret handwritten messages on paper checks and convert them into legible text that FIs’ computing systems can understand, for example.

When put to broader use, AI and machine learning (ML) solutions can significantly improve CUs’ understanding of their members’ behaviors. Developing this understanding is a key ingredient in keeping financial services fraud-free. 

Better Understanding for Improved Financial Offerings 

In addition to automating common tasks and reducing costs, AI has significant potential to improve the types of services credit unions roll out to their members. It can respond more effectively to specific needs when used in conjunction with ML solutions, for example. These systems can learn about members’ behaviors and gain a more complete understanding of the types of transactions they commonly perform, then more effectively detect fraud and data theft when suspicious patterns emerge. 

AI-based solutions can assist in automating CUs’ lending processes, too, which is especially beneficial for small businesses. The technology can be used to assess a member’s financial status, thus helping the credit union make more informed decisions about how much to lend and the terms that will come with a loan. Most importantly, such knowledge can help reduce the risk of CUs issuing loans on which members might default. Recent data indicates that AI and ML solutions can reduce an FI’s losses from delinquent payments by 25 percent. 

Members need to be able to trust their CUs to keep their assets and data secure. At the same time, credit unions need to be sure their members are who they claim to be when accessing services, and that they can fulfill financial obligations related to loan payments. AI-based solutions could be the key to helping both sides more effectively engage, providing a valuable tool that ensures transactions between all parties are valid and free of malicious intent.

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Our data and analytics team has developed a number of creative methodologies and frameworks that measure and benchmark the innovation that’s reshaping the payments and commerce ecosystem. The PYMNTS Next-Gen AP Automation Tracker, is a monthly report that highlights the most recent accounts payable developments and automated solutions that are disrupting how businesses process invoices, track spending and earn rebates on transactions.

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