These four use cases for artificial intelligence in the financial services industry can clarify where and how to get started at your credit union.
Deploying technology to meet members’ needs these days—wherever they are in their financial services journey—increasingly means leaning into artificial intelligence and predictive analytics. But taking the AI bull by the horns isn’t the right approach for every credit union. AI requires a certain amount of care and feeding, and many organizations don’t have the necessary skills or resources to make an enterprise-wide AI approach live up to its full potential. That said, a pinch of pragmatically applied AI can help guide credit unions’ efforts to be more focused on meeting member needs.
Use Cases for AI in the Credit Union Industry
But how and where is AI best utilized by credit unions? There are a number of key AI use cases that are ideally suited to aid sales, marketing, operations and member service. Understanding the goals and benefits of these use cases can help credit unions determine where and when AI is best inserted in their tech stack.
1. Expand your service surface area while helping reduce the cost to serve. You’ve probably heard of AI-powered chatbots being deployed in the financial services realm, and there’s a good reason to do so. According to a June report from the Consumer Financial Protection Bureau, “approximately 37% of the United States population is estimated to have interacted with a bank’s chatbot in 2022, a figure that is projected to grow.” AI-driven chatbots are proving themselves to be MVPs on the front lines, providing an always-on, white-glove touchpoint for members while deflecting calls to the call center, reducing the cost to serve.
2. Discover those individuals most in need of your services. Today, the buyer journey starts online. AI-based intent offerings can surface leads for those individuals showing the greatest interest in your products and services across the web. Credit unions can then prioritize the most promising leads, focusing efforts where they will have the greatest impact by reaching out and nurturing those leads with highly personalized and appropriately timed sales and marketing efforts. This can be an effective way to make vital marketing funds go further through greater focus.
3. Offer quick and seamless pre-approval. In the lending continuum, AI can be leveraged in the front end of the process, to identify who the member or prospect is and/or to verify their business entity, associations and credit history. The goal is a quick, easy and seamless application process. According to BAI, 37% of Gen Zers and 29% of millennials prefer to open accounts via a mobile app. The addition of open banking and alternative data can give credit unions an edge in addressing the needs of thin-file credit applicants and make credit more inclusive. These AI-enabled processes are also highly beneficial in fighting fraud.
4. Support kinder, gentler and more intelligent collections. Another way AI can help credit unions meet members where they are is around collection activities. Being prudent and sensitive is the goal here, and an approach of benefit to both credit unions and their members. AI can help predict the best time to reach out to members, the likelihood of collecting from members, and discern what settlement offers and payment plans are most optimal. This is another area that chatbots can be valuable, by supporting member collections outreach in a less threatening way.
These AI use cases aren’t just “nifty” time savers—they are helping credit unions address real member needs by meeting them where they are. Today, that’s increasingly online and through digital channels. Additionally, while many individuals’ only access to financial services are through credit unions, not everyone has access to a branch location. AI is enabling rich digital engagement that provides the means to know and serve these members online. It can also help make services available to those individuals that are outside of your branches’ geographic area, so that you can expand your total market for products and services. That means more opportunity for growth.
The onus is on the vendor community to make the power and promise of AI offerings available, approachable and cost-effective for credit unions. Go with a trusted and experienced service provider that has AI models that are already trained for the task at hand. This can ensure you get rich insights without having to do the heavy lifting.
Leaning into these pragmatic and practical AI use cases can help credit unions support members’ financial well-being by being there at every turn throughout the member lifecycle to provide an exemplary member experience.
Michael Fife is SVP/North America—West, sales and professional services for Provenir, a global leader in data and AI-powered risk decisioning software, processing more than 4 billion transactions annually for disruptive financial services organizations in more than 50 countries worldwide.