AI Helps Credit Unions Connect With Gen Z

Two fintech firms indicate they can help CUs bring in younger members through better user experiences and financial literacy tools.

Using artificial intelligence to connect with younger generations. (Source: Shutterstock)

Two recent fintech announcements claim artificial intelligence could assist credit unions reach Generation Z members and help create and maintain lending rules and policies.

Detroit-based online and mobile banking provider Bankjoy and Durham, N.C.-based financial literacy provider Zogo have partnered to help credit unions provide a better member experience – especially to the Generation Z population (people born between 1996-2010).

According to Bankjoy Founder/CEO Mike Duncan, one of his company’s mobile technology offerings allows online account opening processing in less than 90 seconds, which is vitally important in attracting the younger generations to credit unions – along with anybody else who desires a fast, online account opening process. Zogo Co-Founder Bolun Li added that his company provides credit unions with financial education to their members, engaging Gen Zers to change their bad financial habits.

As a result, the two firms indicated they can help credit unions bring in younger generations through a better user experience and with financial literacy tools to sustain and grow their memberships.

The fintech organizations will tie two of their products together: Zogo’s financial literacy program and Bankjoy’s online account opening product – as well as a referral program that allows consumers to become members in 90 seconds or less, while learning financial wellness tips.

Both Duncan and Li explained the partnership allows credit unions to fine tune their offers in an educational format – rather than a sales approach, which typically doesn’t resonate to the younger generations. At the same time, having a deeper mission or underlying value can attract Gen Z to credit unions.

The next step is to integrate the financial literacy program into other services such as mobile banking, online banking, conversational artificial intelligence, and statements to provide financial wellness information.

“Honestly, I’ve been kind of stalking Bankjoy for a while, so I was really happy when we finally connected,” Li joked. “I was really intrigued by the online account opening software Bankjoy has. This is something we’ve been looking for to let our audience take the next step and join a credit union.”

Duncan stated, “Zogo is exactly the kind of value we have been looking for to add to our digital banking platform.” He added, “Providing financial education to younger generations builds value on top of our digital banking ecosystem and delivers it through all our different channels to create a better member experience – especially for Gen Z.”

Islandia, N.Y.-based Teledata Communications, Inc., a provider of a complete consumer loan origination platform, announced development of an AI-powered, natural language rules engine that leverages machine learning to create and maintain risk-based rules and lending policies. The process does not require any specialized software development skills or the addition of IT resources or third-party assistance.

TCI’s DecisionLender 4 implementation of natural language understanding, utilizes machine learning that enables users to create rules using plain English and then convert the rule into code automatically. Any business user can add new and edit rules, and maintain risk policies.

“TCI continues to put more tools into the hands of its lenders,” Stefan Ionescu, vice president, development, TCI said. “Lenders can now build rule sets in plain English, honing and perfecting their models and deploying advanced policies without adding any new costs, resources, coding or special configurations.”

Traditionally DecisionLender 4 authors credit rules and risk policies using a domain specific language, requiring specialized training. With TCI’s new machine-learning tool, lenders can input their parameters using plain English commands and the system automatically creates credit rules and risk policies, empowering lenders to rapidly develop new lending policies and implement the changes quickly.

Test-It, a DecisionLender 4 tool, can help vet and select the correct test cases to fine tune the new lending model created with NLU in the demo environment. According to TCI, through DecisionLender 4, lending programs no longer tie financial institutions to the vendor’s procedures or timelines. These new tools enable lenders to control their lending modules at their own pace and timeline.