Meet Gene and Fran, $6 billion MSUFCU’s internal and external virtual support agents—next-gen chatbots that play a critical role serving the CU’s 300,000-plus members and staff alike.
Next-gen conversational artificial intelligence has arrived, and financial institutions ranging from major banks to small community credit unions should take note of how investing in this technology can help mitigate existing member experience problems and provide the capacity to fuel growth even further than currently possible.
Unfortunately, the first generation of conversational AI left a bad taste in the mouths of many organizations due to its cost and underwhelming capability, among other pain points. Today, the biggest shocks—and sometimes major misconceptions—related to the potential use cases of conversational AI in MX and employee experience workflows are the positive advancements in the time it takes to onboard, the cost-benefit ratio and the scalability. At Boost.ai, we are now working to overcome these misconceptions based on first-gen experiences through the simple breakdown of successful use cases where our customers have seen remarkable returns and impact.
No-Code Solutions Are a Credit Union’s Best Friend
Many consumers have moved to digital-first service options, and it’s much easier to gain their business when you meet them where they already are. Furthermore, change is inevitable, and looking for dynamic solutions that can adapt as your needs change is integral to providing better member experiences. Such dynamic offerings are often costly, but no-code solutions keep costs low without sacrificing crucial components to meet evolving member needs. With no-code, current staff members can become your conversational AI experts without requiring additional internal software engineers on the payroll. Technology budgets are often tight, so it’s best to seek out solutions that are low-cost with high reward.
Sometimes solutions are needed at a moment’s notice, but often software can take weeks, years or even months to get up and running. Sometimes that length of time is allotted to just get base packages installed. The pandemic showed us external factors can wreak havoc on a financial institution’s support capabilities. Taking the time now to onboard dynamic technology solutions allows credit unions to remain competitive and responsive to outside factors, because those solutions can shift and scale as your demands do. In the case of CAI, credit unions should look for pre-packaged solutions that come with intents—topics a member has in mind when typing in a question—built in to ensure implementation time is manageable.
Michigan State University Federal Credit Union, which manages almost $6.9 billion in assets for its more than 327,000 members, uses both internal and external conversational AI-powered virtual agents, named Gene and Fran, to meet a continuously rising influx of support requests from its growing member base. Initially, MSUFCU’s CEO, CUES member April Clobes, wanted to explore using a chatbot. So, CUES member Ben Maxim, VP/digital strategy & innovation for MSUFCU, along with Ami Iceman, VP/research and digital experience, and CUES member Ashleigh Ashbrook, VP/eServices, took action. When asked why MSUFCU felt it necessary to onboard virtual agents, Maxim said, “We have 327,000 reasons why Gene and Fran are so important to our organization: Boost.ai’s user-friendly platform enables our in-house AI team to continue to find new ways to provide the best possible service for our members.”
By the Numbers
The value of integrating CAI speaks for itself. Since launching Gene and Fran, MSUFCU has seen impressive metrics that validate the value of both virtual agents in their respective use-cases. In spring 2020, the beginning of the pandemic in the U.S., MSUFCU saw a massive increase in the amount of incoming live chats, with 130% growth from the previous month, inspiring the need for virtual agents who could offload some of that capacity. Since implementation, Gene, the internal agent who helps employees find information, has handled over 12,000 conversations with MSUFCU staff, which breaks down to around 26,000 messages received. As of March 2022, Fran has grown to the point of deploying over 1,100 intents in resolving customer queries, up from the original 250.
Other key metrics from this partnership include:
- a 10-day time frame to build out a bot’s knowledge base from initial integration to implementation within a customer-facing setting;
- a 100% employee satisfaction rate by the end of the four-week pilot program when asked “How beneficial would the chatbot be for day-to-day work?” and
- the projected automation of 2,000 employee-to-employee interactions each month by the end of the pilot, saving time and greatly increasing operational efficiency.
Additionally, the external-facing virtual agent Fran is now equipped to address thousands of types of inquiries from MSUFCU’s members with 24/7 availability. This growth in capabilities represents a 400% increase in intents since MSUFCU’s initial rollout of Fran in 2019, supporting the credit union’s rapid scale-up to accommodate rapid growth.
While the public feeling around AI-driven solutions may be that they are complex and require multiple academic certificates to interact with, the reality when it comes to the virtual agents of today is quite the opposite. Investment in programs that are built on natural language processing is skyrocketing. They can appear as simple to the consumer who interacts with them as they are to the associates on the back end who are reviewing the metrics and building up new conversational paths. The point of these virtual agents is not to replace the member service teams that help to build relationships between your credit union brand and member base, but instead to cut down on the administrative efforts on both ends of the interaction that takes up time for both enterprise and member.
Bill Schwaab is VP/North America at Boost.ai, where he is currently focused on growing the company’s North American presence, with an emphasis on the financial services, banking, insurance and e-commerce sectors. He brings with him more than 15 years of experience in conversational AI, machine learning and data analytics and a successful track record of helping mid to large-size enterprises scale through the use of AI. Bill is committed to helping Boost.ai customers develop more intuitive, interactive and efficient customer experiences.