TechSolutions4CUs OTG

In this episode we talk about liquidity and lending solutions for credit unions, focusing on how they can create room to make more loans even when deposits are limited. We discuss loan participations, securitization, and ways to move loans off balance sheets so credit unions can keep lending to members.

We also explain the relationship between TAPP Engine and 9Squid. TAPP Engine is the parent company, with 9Squid as a separate brand for its capital markets and securitization work, while Mission Federal Services participates through its CUSO structure and invests in financial technology companies.

A major topic is why credit unions are investing in fintech. We discuss how these investments help credit unions gain access to technology, keep income within the industry, and reduce dependence on outside providers. We also talk about how fintech partnerships can be more efficient than building proprietary systems internally.

We cover how these solutions are designed for both large and smaller credit unions. The guests explain that securitizations have typically required large loan pools, but the platform is being built so smaller institutions can participate by pooling assets together.

We close with a focus on education and support. We explain that these services are not just products, but also involve consulting, training, and help for credit unions and their members so they can better understand liquidity, securitization, and wealth tools.

The guests discuss their companies, their working relationship, and how their collaboration began through the MSUFCU Conquer Fintech Accelerator. Arjun explains that Ascent is a data and AI platform designed to help credit unions understand their data and combine it with institutional knowledge such as policies, prior decisions, and member context. He says the goal is to create a single intelligence base that can be used across different systems and by both employees and automated agents.

Filip describes his role in the accelerator and says Ascent was one of the first companies in the program. He explains that the accelerator is meant to help fintechs understand how to work with credit unions, and that the relationship with Ascent has continued beyond the initial 10-week program.

They say Ascent currently works with about 70 credit unions and also serves community banks. Arjun says the platform sits above systems of record and data warehouses and can send “signals” or insights into tools such as Salesforce, CRM systems, Encino, or copilots, depending on what an institution uses.

A major topic is the role of AI in financial institutions. Both guests say AI is being discussed widely, but they emphasize that institutions need strong data foundations and practical use cases rather than broad AI messaging. They say many organizations still struggle with siloed and fragmented data.

They also discuss how to approach product development. Arjun says Ascent started with specific use cases, such as quality control, deposits leaving the institution, and lending opportunities, and expanded from there. Filip adds that smaller, focused solutions are often easier for institutions to adopt.

The conversation closes with future plans. Filip says applications are open for a new cohort of the accelerator. Arjun says Ascent is available to credit unions that want to improve workflow, identify member behavior, or address specific operational pain points.

The interview focuses on member engagement at credit unions, with Gregg Hammerman of Larky and Ami Iceman of MSUFCU discussing how they use push notifications to reach members more effectively. Gregg explains that credit unions offer many products and services, but members do not always know about them unless they are contacted proactively. They describe push notifications as messages sent through a mobile banking app, using the credit union’s logo and a permissioned channel rather than SMS.

Ami says MSUFCU adopted the system because it offered a more secure way to communicate with members amid smishing concerns, while also allowing alerts, offers, and product links. She says the credit union now uses push notifications in most of its marketing campaigns.

A major topic is controlling message volume. Ami says MSUFCU can set thresholds for how many messages members receive and prioritize urgent notices. Gregg adds that the system is designed to prevent over-messaging and to allow “break glass” alerts when something important needs immediate attention, such as a power outage or other urgent member update.

They also discuss location-based messaging and feedback. Gregg gives examples of messages triggered by a member being in a branch or at another location for a set amount of time. Ami says MSUFCU has used this to ask members for branch visit feedback through a survey link.

On integration, Ami says the system works with internal data and is manageable by her marketing team through a portal. Gregg notes that Larky also integrates with several digital banking providers and supports both large and small credit unions through automation.

The final topic is AI. Gregg says Larky uses AI to help generate better push notification copy, including call-to-action wording, emoji choice, and timing. Ami and Gregg also reflect on the value of the Summit for meeting partners and seeing new fintech developments.

Aaron Colcord says Voyager AI is an early-stage company focused on precision AI for commercial lending. He describes the company’s goal as helping lenders make more approvals by using AI to handle work that should not require human effort, so staff can spend more time on relationships and deal evaluation.

He explains that Voyager AI is designed to integrate and orchestrate existing credit union systems rather than replace them. The platform connects to lending origination systems and can also work with core systems, document sources such as SharePoint, and later covenant monitoring and other integrations.

Implementation depends on the credit union’s network setup and security requirements. Colcord says the system can support the full commercial lending workflow, starting with document collection and pre-flight review, then helping teams assess deals, gather borrower information, coordinate with underwriters, prepare credit memos, and take deals through committee approval.

The company currently stops before booking into the core system, with monitoring planned as a later step. He says the platform has reduced the total time of the lending process by at least 60% for some organizations. He also says it creates one shared source of intelligence for teams and can check institutional policies to reduce stop points while staying compliant.

On member experience, he says the system helps move credit unions away from both “short no” and “long no” outcomes. It can help them expand into more loan products, keep members through life changes, and reduce delays in loan decisions, including SBA processes that can otherwise take months.

Colcord says Voyager AI was invited to the Reseda Summit pitch contest and that feedback on the pitch was positive. He says the company is talking to a few credit unions and beginning onboarding. He adds that the company has been operating for about 18 months and that supporting credit unions and community banks can help them compete more effectively with fintechs.

Christian Klacko describes Kintera AI as an AI operational layer for institutions, especially credit unions. He says the company turns existing policies into workflows that AI can execute, with the goal of making back-office processes more efficient.

He explains that the company started in 2025 and launched its first product later that year, with its first credit union going into production in early 2026. The first live customer is Rockland Credit Union, now called Arise Financial.

Klacko says he is a serial entrepreneur and this is his fourth company and second fintech company. He says his earlier company, Micronotes, showed him that credit unions spend a lot of time on manual review of documents and procedures, and that generative AI is well-suited for reducing that workload.

He says the product is deployed on-premise so that personal information does not leave the credit union. To get started, the company needs access to a server and a copy of the institution’s policies. The system is browser-based and can run in common server environments.

Klacko says implementation is simple and fast, and that one credit union went live in 10 days. He says the company uses shared folders at first, without requiring integrations, and can later connect to loan origination systems or core systems if needed. He also says the product has little customization because the policies themselves drive the workflow.

He gives an example from Rockland Credit Union, where reviewing an indirect auto loan package reportedly dropped from about 20 minutes to 2 minutes. He says the same approach can be used for vendor due diligence and other document-heavy processes.

He says he was introduced to the Reseda Summit through mutual connections and was encouraged to pitch and explore a pilot. He mentions plans to attend other industry events, including GAC, VentureTech, and Money20/20.

He closes by saying the company started with credit unions because he values their collaborative spirit. He says the broader goal is to standardize back-office processes across credit unions, rather than having each institution use separate tools and workflows.

We talk with Arjun Kinective's about whether AI is truly as dangerous as some headlines suggest, and we keep returning to the idea that the current fear is being overstated. We also discuss using Gemini in everyday work, especially for troubleshooting, where we describe it as a back-and-forth tool that can help solve problems like a collaborative partner.

We shift to television and compare shows for travel viewing, including Lioness and Reacher. We describe Lioness as a CIA and geopolitics series with a strong cast and note that Reacher is more violent, with the action often overtaking the plot. We also talk about the challenge of finding something to watch on the road after going through airline movie libraries.

We then move into airlines and travel frustrations, comparing Delta, United, and the lack of competition in the U.S. airline market. We talk about expensive flights, poor communication during delays, and how flying outside the U.S. often feels easier by comparison. We also compare that to bigger banks versus community banks, where relationship and service matter more than the basic product.

We spend much of the conversation on trust, human judgment, and AI. We say people still want to work with people, not just technology, and that AI should be used to empower staff rather than replace them. We use examples from lending, email writing, recipes, and spreadsheet work to show that AI can help, but still makes mistakes and needs human oversight and context.

We end by predicting that the next major phase of AI will be institutions getting more serious about managing their data and using that to build useful agents. We also make a lighter prediction that Arsenal will win the Premier League again.

The interview focuses on Kinective's recent direction. The guests say the company has slowed acquisitions and is now concentrating on integrating what it has already bought and expanding the company's capabilities. A major theme is Kinective's work with fintechs that need access to core data. The guests say many credit unions want outside solutions, but those solutions still need to connect quickly and reliably to core systems. They describe Kinective's role as helping fintechs connect without having to build those links on their own.

They also discuss the current market for point solutions and AI tools. They say many products are very narrow and solve only small problems, which can make it difficult for credit unions and financial institutions to choose what will actually help them. They note that institutions cannot easily buy many separate tools each year, so value and fit matter.

Kinective's platform strategy is another topic. One guest explains that after acquisitions, the company now has three platforms coming together: a REST API platform, a GraphQL-based platform, and another in-house system. He says this gives fintech providers more flexibility in how they connect to Kinective and, by extension, to credit unions.

The conversation also turns to industry consolidation. The guests say they expect continued consolidation among both financial institutions and fintechs, and they question how many smaller companies can remain independent over time. They also say many fintechs have similar ideas, which makes differentiation difficult.

Trust and delivery are described as important in vendor relationships. The guests say people prefer the word “partner” over “vendor,” but real trust comes from execution, support, and ongoing work after a sale. They say Kinective's broad reach across many institutions helps build that trust and makes it likely that a fintech is already working with one of their prospects.

Marcell King explains that Nuuvia is a youth-focused digital banking experience embedded into a credit union’s existing technology stack. He says the product is designed to help credit unions compete with fintech companies for Gen Z and Gen Alpha by offering tools that combine financial education, real money use, and gamification.

He says the need for youth financial education has existed for a long time, but technology now makes it easier to deliver. King describes his own experience entering college without much financial knowledge and says many families do not teach money management in depth. He also notes that several states now require financial education in high school, while many Americans still are not financially literate.

King says the product helps credit unions with acquisition, growth, and retention, not just service. He points to one institution that grew from a few hundred youth accounts to over 10,000 after adopting the program, with some of those accounts bringing in new adult members through joint ownership.

He describes features for children and parents, including financial education, real-time transfers for chores or allowances, debit card spending controls, charitable giving, savings goals, and a parental lending tool that shows interest charges. He says the experience is designed to be personalized and easy to use within the institution’s existing digital banking platform.

On implementation, King says the solution is white-labeled or co-branded for credit unions. He says parents and kids access it through the institution’s current digital banking experience, and the youth version can be limited so children do not see features like bill pay or remote deposit capture.

King says institutions need to market the service to parents, but he believes it can also teach parents about money management. He adds that future plans include helping institutions bring in deposits from outside sources, such as relatives or other people paying a child for work. He says Nuuvia differs from some competitors because the credit union keeps the deposits, interchange, data, and member relationship.

Baron Conway of Finalytics AI discussed the company’s recent presentation at FinovateFall, where the company showed new features in a live demo. He said the event was useful for comparing the company’s work with others in the financial technology space and for sharing what Finalytics is building.

A major topic was Finalytics’ personalization platform for credit unions and banks. Conway said the system starts on the public website by recognizing visitors and adjusting the experience in real time based on their likely needs.

The newest feature is a first-time visitor learner model that predicts what product or service an anonymous visitor may be interested in, using patterns learned from large-scale session and event data. He said the model uses variables such as location, device, operating system, and time of day, along with other signals. Finalytics tracks engagement through the process, including whether visitors move deeper into the site, start applications, complete them, and in some cases whether applications are funded.

Conway explained that the first visit is the only fully anonymous visit. After that, Finalytics assigns a unique identifier so the system can recognize return visits and continue personalizing content without using cookies.

He also described learner models that already identify existing members and their products, then recommend products they do not yet have. Another rollout connects behavior on the public website with digital banking, so a member who shows interest in something like a car loan or certificate can see related messaging after logging in.

Looking ahead, Conway said the company wants to become a broader personalization layer that can identify likely product interest, determine the right message, choose the best channel, and sequence communication across touchpoints.