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Consumers are always looking for ways to get more done in the same amount of time. As a result, many consumers have turned to self-service channels to accomplish the tasks on their list whenever they have time. Nice released their 2022 Digital First Customer Experience Report in which 81% of consumers stated that they wanted more self-service options. And consumers are looking for smarter service options that handle more complex tasks and understand requests faster. These rising consumer expectations mean credit unions need to embrace products and services to meet those needs. Artificial intelligence is an innovative technology that can help credit unions improve the member experience by efficiently responding to inquiries, personalizing the information provided, and providing upsell opportunities. Let’s take a look at how artificial intelligence can help credit unions achieve their service and sales objectives.

Consider the use of chat. In the past, chatbots were typically a question-and-answer solution. A way for a member to get information available on the credit union’s website or collateral material without having to sift through those sources. Artificial intelligence can take that same informational product and service experience to the next level. Consider this scenario, a member, or prospective member, visits the credit union’s website. The member asks for information about the credit union’s auto loans. The traditional chatbot would provide product information based on what the credit union had entered into the chat solutions question-and-answer library. The member then asks more specifically about the auto loan rates. The traditional chatbot would take the member to the rates page on the website.

While the chatbot provides the information that the member has asked for, it is not engaging the member by intuitively building on the questions previously asked. For example, after the member has asked the initial question about an auto loan, an intuitive chatbot may ask if the member is looking for a new or used car and the term of the loan that they want. The chatbot then may ask how the member would assess their credit score (excellent, good, etc.). Based on the answers to those questions, the chatbot knows the rate, or rate range, to present based on the type of auto loan (new or used), term, and estimated creditworthiness as provided by the member. The chatbot could then provide a promotion and take the member to the loan application. All of this is accomplished quickly with a short series of questions to move the member to apply for the loan.

But wait. There’s more. Suppose that same member had authenticated themselves via digital banking. If that member went through a similar interaction and decided not to apply, their information could be added to a file used for an auto loan campaign. Why did we use the term “file?” Because all authenticated members that asked about an auto loan would be placed into that file. In other words, instead of modeling an auto loan promotion around a list of potential members, the credit union has a list of members who showed actual interest in an auto loan. Talk about one-to-one member marketing! The member has received convenient and efficient service, the credit union has the opportunity to upsell during the initial engagement, and the member is added to a list of members who have demonstrated interest in auto loans, for use by the Marketing Department. Based on a series of intuitive questions, targeted one-to-one marketing offers can be presented to members without the need for the credit union to buy any additional consumer segmentation data or spend time creating a campaign list. That is a win for the member and the credit union.

And AI can be used for real time campaigns. Back to our auto loan example: Consider a scenario where the credit union wants to upsell mechanical breakdown insurance. Instead of just looking for members with an auto loan without mechanical breakdown insurance, AI can watch the transaction behavior and spot upsell opportunities. For example, the transaction data for a member with an auto loan shows multiple credit or debit card transactions at the same dealership in a four-week period. Additionally, the member’s loan has just reached its 37th month after the funding date, and the member does not have mechanical breakdown insurance on the loan. Because AI is continuously monitoring all of the member’s data, it predicts the member may be a candidate for an extended warranty based on the frequency of charges at the same dealership. Sounds like a great one-to-one marketing opportunity for an extended warranty offer. And this is just one scenario where AI can use member data to predict product upsell opportunities. The credit union has just hit the coveted sales scenario: the right offer at the right time. Every time.

Today’s members are looking for convenient solutions to efficiently assist them in managing their financial affairs. With the ability for AI to recognize a consumer’s interest in a product based on chat interactions and/or real-time behavior analysis, credit unions can maximize their marketing, digital, and member service budgets while meeting their strategic goals of cost efficiency, increased sales, and improved member engagement. Leveraging the power of artificial intelligence results in an efficient member experience to meet the needs of today’s members.