Movemint Symposium 2026: Cracking the Indirect Member Code
By John San Filippo
For decades, indirect auto lending has represented a familiar paradox for credit unions. On paper, indirect lending platforms provide a near effortless channel to book auto loans and expand membership rosters. In practice, however, these borrowers rarely behave like full-fledged members. To most indirect borrowers, the credit union is merely an institution where they make an automated car payment each month. Converting these single-service relationships into primary financial partnerships has long remained an elusive industry goal.
At the recent 2026 Movemint Symposium in Lakeway, Texas, a panel of leaders showcased a collaborative approach to solving this challenge. Rather than accepting indirect members as single-service accounts, Binghamton, N.Y.-based GHS Federal Credit Union partnered with Vertice AI, AviaryAI, and Movemint to construct an automated ecosystem dedicated to activating indirect borrowers.
GHS manages roughly $253 million in assets, proving that sophisticated data science and automated outreach are no longer restricted to multi-billion-dollar institutions.
The Holy Grail of Indirect Lending
Credit unions frequently face high friction when attempting to engage indirect borrowers because the institution often lacks initial touchpoints with those members. Dealers collect minimal information, and traditional follow-up typically relies on standard mailers or batch email blasts that members often ignore.
“The indirect mountain to climb, or as I’ve been calling it, the Holy Grail of credit unions is, man, if we could have the best rate in town, the best member service, and have the best dealer relationships, what’s stopping us from growing this indirect membership into a full-fledged membership?” Ryan Best, Director of Innovation at GHS, asked rhetorically. “Technology has finally caught up to where we can climb efficiently that mountain.”
Rather than treating indirect borrowers as secondary participants, GHS sought to put tailored offers in front of these members at the exact moment they need them.
“A lot of people think of the indirect channel as something on the side, like we do our stuff for our membership and then we have our indirect guys as well,” said Best. “Our goal is to treat the indirects the same way we treat our strongest members.”
Assembling the Technology Engine
Solving the indirect activation problem required connecting data, predictive intelligence, outreach, and digital fulfillment into a single workflow, Best noted. The initiative brought together four distinct roles:
GHS Federal Credit Union: Provided the core indirect member data, auto application files, and relationship strategy.
Vertice AI: Applied predictive propensity models to analyze first-party data and identify which members are most likely to adopt specific credit union products.
Movemint: Delivered digital storefront fulfillment and personalized campaign workflows, dynamically placing high-propensity offers directly in front of the member.
AviaryAI: Deployed conversational voice AI agents and two-way texting to proactively reach out, notify members of tailored offers, and guide them directly to digital conversion.
Vertice AI uses deterministic machine learning to evaluate account data, collateral details, and loan application files, explained Mitch Rutledge, CEO at Vertice AI. Even attributes like vehicle type and loan-to-value ratios can serve as strong indicators of future financial needs.
“Propensity models are taking all of this first-party data that we have about the members or the indirect members,” said Rutledge. “We have a series of predictive models that essentially score every one of these members on every product and service that GHS offers.”
Instead of pushing generic credit cards or checking accounts across the entire member roster, the models generate a prioritized, ranked list of members and recommended products. Movemint then ingests these scores to deliver dynamic digital placement, said Samantha Ziesemer, COO at Movemint and the panel’s moderator.
“One thing I’m really excited about is the latest feature we’ve rolled out with Vertice, where we can take the highest propensity scoring products and actually put that as the primary product on the storefront and shift the product placement to be in line dynamically with what these propensity scores are telling us,” said Ziesemer.
Moving Beyond One-Way Blasts
The final piece of the workflow addresses outreach. Most credit unions do not possess the contact center bandwidth to manually call every new indirect borrower, while static mail campaigns frequently produce low engagement.
“Eighty-two percent of financial institutions do not make those proactive outreaches,” said Blesson Abraham, CEO at AviaryAI. “What we built was to fill that gap, which is proactively calling members as they’re going through the journey.”
AviaryAI’s voice agents initiate personalized calls to indirect borrowers, informing them that a curated offer is ready and sending direct follow-up links via email and text messaging. The conversational AI handles basic member inquiries, updates bad contact information collected at the dealership, and can warm-transfer complex conversations or trigger internal notifications via Microsoft Teams when a human in the loop is required.
Abraham noted that member reception to voice AI outreach has proven remarkably strong.
“Of those 11 million members that we’ve reached out to, 44% of them are picking up the phone,” Abraham said. “Of half the people that actually do pick up their phones, seven out of 10 of those end in a natural goodbye,” driving home the point that most consumers are comfortable talking with well-implemented AI.
Abraham added that Aviary’s interactions show a 94% positive sentiment rate, with less than 1% resulting in negative feedback regarding AI usage.
Quantifying the Results
The combination of predictive targeting and automated engagement has delivered notable lifts across early deployments:
Product Adoption Lifts: Across its broader customer base, Vertice AI has documented product adoption rate increases ranging from 110% to 140%, with specific indirect loan conversion campaigns achieving up to 250% higher adoption rates compared to baseline figures. In targeted scenarios, conversion rates reached up to 11 times higher than traditional efforts.
Rapid Baseline Engagement: In an initial test campaign rolled out with GHS involving a 30-member file, the credit union secured four redemptions within days.
Unprecedented Campaign Speed: Leveraging automated workflows, GHS and Vertice AI executed 90 separate campaigns in just nine weeks.
“Don’t think of AI as artificial,” Rutledge emphasized. “I think we should be thinking about it as automated. We ran 90 campaigns in 9 weeks with GHS, and now we’re going to start doing calling with that. This is an efficiency play to really, again, test and learn.”
Agility Over Perfection
Rather than spending months building an elaborate internal infrastructure, GHS pursued simultaneous vendor implementations, relying on open collaboration among partners to make the tech stack connect seamlessly.
“We jumped into the deep end,” Best said. “We stacked implementations of Vertice, Aviary, and Movemint. I think if you went to another credit union our size and said, hey, we’re going to be implementing three technologies at once, I bet half the team would pass out.”
For credit unions grappling with the economics of indirect lending, the GHS use case outlines a practical roadmap. By pairing predictive member data with automated conversational outreach and dynamic digital fulfillment, credit unions can finally crack the indirect code – turning transactional auto borrowers into long-term, engaged credit union members.
