In Part 1, we tackled the financial app frenzy on our smartphones, called out the lazy industry dogma that the primary financial institution is dead, and examined how credit unions got trapped in “skeuomorphic thinking” – trying to digitize a brick-and-mortar branch lobby. Now it’s time to talk about the cure.

What Not to Do

I hope my premise is clear by now. Becoming your members’ digital primary financial institution is within reach of any credit union. The tools are there. The first thing that needs to change is the thinking. With that in mind, it makes sense to look at what hasn’t worked well along this seemingly rough and rocky road. Specifically, let’s talk about data aggregation.

It seems like a quick and easy fix. Provide your members with a more or less complete picture of their finances. But there’s a reason Yodlee, Mint and your credit union’s PFM never captured the imaginations of the public in a big way.

The root problem is, you can’t transact with a picture. It’s important to know when there’s a crisis situation in one of your accounts. It’s more important to be able to do something about it.

Bottom line: People want to do, not view.

What We Can Learn from Walmart

Full disclaimer: I’m not a big fan of Walmart. Hundreds of shopping carts jockeying for position inevitably leads to a San Filippo anxiety attack of one degree or another. I feel the same way about Costco. And Albertsons during peak grocery hours.

However, Walmart did get something right. The popular thinking is that trying to be all things to all people in this digital age is futile. In the context of banking, it’s an easy way to explain away the death of the PFI. Walmart respectfully disagrees.

When they started building Walmart Supercenters, they set out very intentionally to be all things to all people. Shoppers don’t go to a Walmart Supercenter because they can get a loaf of bread or a quart of motor oil or Duck Dynasty slippers or a flat-screen TV. They go there because they can get all of these under one roof, in some cases 24 hours a day. They’ve taken the guesswork out of “I need X. Where should I go to buy that?” because no matter what X is, the answer is the Walmart Supercenter. They’ve become the PSO – primary shopping outlet.

Now think of your credit union as a financial supercenter. Whether the member wants to buy and custody crypto, manage their stock portfolio, get a HELOC, finance a new car or open a business checking account, they don’t have to wonder where to go. They know they can get whatever they need from their credit union. That’s the point at which your credit union becomes the DPFI for that member.

Give the People What They Want

Marketing has traditionally been about convincing people to buy whatever you happen to be selling. If you’re a credit union, it meant running campaigns to open more checking accounts, book more auto loans, or migrate regular savings to CDs.

Digital has put the consumer in control. You already know that. What that means to your marketing and to your product lineup is this: Especially with all the infidel competitors trying to tear down the gate, ask yourself not how you can better market your existing stuff, but what stuff you need to offer to establish yourself as your members’ DPFI.

Thankfully, there’s AI-driven persona modeling that can help you figure this all out. You simply can’t rely on the same product mix as you did in 2006 or even 2016.

I know in Part 1 it probably seemed like I was pooping on point solutions. I really wasn’t. I was critical only of the haphazard selection and implementation of point solutions, and the confusion they can cause if you’re not careful. Properly chosen and deployed, point solutions are key to this whole DPFI transformation.

The Orchestration Imperative

Orchestration layer is a term I hear more frequently these days. As the name implies, it’s a middleware layer whose primary purpose is to wrangle all those point solutions. The only problem with many of the discussions I’ve been party to is that there’s a disconnect between operational orchestration and experience orchestration. In short, orchestration layers are discussed primarily as plumbing projects. How can we add a middleware layer to make all the stuff we have work better together?

Building on my earlier restaurant metaphor, think of the orchestration layer as the mega restaurant supply house that delivers whatever you need whenever you need it. That in turn allows you to give the member whatever they need whenever they need it.

While operational orchestration is an essential starting point, experience orchestration is the gold ring here. The end goal is to create a unified, simplified user experience that allows your members to manage all their finances. In other words, it’s not just bundling and managing the stuff you already have; it’s being able to incorporate any new functionality that your members require. It’s becoming their DPFI.

The Race Is On

Technology – specifically the unbundling of financial services – has made consumers’ lives more complicated, not less. And it will probably get worse before it gets better. However, eventually somebody is going to figure it out. Somebody is going to put together all the pieces needed to simplify consumers’ financial lives. Somebody is going to discover the keys to DPFI success. My only question to you is: What are you waiting for?

Simplify and thrive!

My wife and I were sitting there the other night hoping to watch something on TV. But first we were faced with a flurry of questions that demanded our attention. We have our A List of streaming services – Netflix, Prime (with Acorn and Masterpiece add-ons), BritBox, Hulu, Apple and HBO – so the first challenge is always trying to remember which shows are on which services. Or are they on the cable carrier’s on-demand feature? When does the next six or eight-episode season start? Is the show in question bingeable or is it one of those episode-a-week deals? If the latter, did we already watch this week’s episode? Will Nigella Lawson be able to fill the shoes of Dame Prue Leith?

Oh, how I longed for the days of three VHF stations, a channel-selector knob that clunked so loudly it made the doily on the end table shimmy, and the trusty TV Guide to help navigate all those myriad choices. What I wouldn’t give for that degree of simplicity built into my current 80-inch surround-sound smart TV.

That got me to thinking about the parallels to my digital financial life. I remember scoffing when I first heard that most people have 20 or more financial apps on their phones. Then I counted mine. I had 26. Wth? All my life, I was told that technology would make our lives simpler. Juggling 26 or more apps just to make sure I have a handle on my money is anything but simple. I don’t care if each one of those apps is a masterpiece of UX art. The fact that there are 26 of them makes the whole experience a cluster.

The Death of the PFI

For decades, it was the dream of every credit union to be the member’s primary financial institution, positioning their credit card top of wallet and their usefulness as a financial resource top of mind. Some succeeded; others didn’t. But that didn’t really matter as long as they tried hard to achieve that PFI status.

Then along came digital/mobile and the whole industry abandoned that dream overnight. Suddenly, becoming anyone’s PFI seemed entirely out of reach.

I can’t tell you how many pundits, experts and wizkids I’ve heard declare that the PFI is dead and credit unions need to be satisfied with the few slivers of the financial pie that they’re able to carve out. Invariably, the response of anyone within earshot is a head nod as if to say, “Duh, of course the PFI is dead.”

Bullshit.

The PFI may be on life support, but it’s not dead. And the only reason it’s on life support is that we got lazy. We failed to truly embrace the technology and adapt to the changing world around us. The silver lining here is that it’s not too late. We have within our grasp all the tools we need to revive the PFI as the new and mighty digital primary financial institution, or DPFI.

The Point Solution Predicament

The “platform versus point solution” debate is nothing new. Platform developers can give you a million reasons why platforms are better, and point solution developers can give you a million more reasons why point solutions are better. The debate has achieved a new relevance, however, because of the incredible proliferation of fintech point solutions. Attend any of the pitch-heavy conferences and you’ll soon discover there are at least 10 point solutions available to address even the most microscopic problem.

Point solutions are a quick and easy fix, to be sure. The bank down the street offers X and some of our members have mentioned X, so let’s plug in a point solution that addresses X.

Indulge me for a moment and reimagine your credit union as a restaurant. Except in this version of the universe, you’re forced to buy spoons from one vendor, forks from another vendor, knives from another vendor, salt from another vendor, and pepper from another vendor. Multiply that by 20 and that’s where we are in today’s point solution frenzy. I’ve had CTOs from larger credit unions tell me they’re now managing 80-100 vendor relationships. That might be more acceptable if all the effort produced a better result.

Ironically, both credit unions and their members find themselves in the exact same predicament – trying to piece together dozens of point solutions in an effort to create a functional user experience. Fix that for your credit union and you fix that for your members. And you become their DPFI.

The Skeuomorphic Trap: From Bob’s to Jobs

Skeuomorphic. There’s a word you don’t hear every day – maybe not even any day. But it’s an important word to this discussion. For the uninitiated, skeuomorphic design is a style where digital or manufactured objects imitate the appearance, texture, or function of their real-world physical counterparts. Allow me to share a couple of examples.

In 1995, Microsoft introduced Bob, billed as the first human PC interface. Bob attempted to simplify Windows for beginners by replacing the standard desktop with a cartoon living room staffed by talking animated pets, where clicking a digital desk launched word processing and clicking a wall calendar opened your schedule.

Bob suffered on two fronts. First, it required a state-of-the-art Intel 80486 processor and (gasp!) 8MB of RAM when most of its target demographic was plugging along on their 386es with 4MB of RAM.

Second, by this point in digital history, common folk understood how to operate their computers. They didn’t need a screenful of idiotic visual metaphors to guide them. It took barely a year for the marketplace to say, “This is stupid. Take it away.”

The brilliant and revered Steve Jobs was also passionate about skeuomorphic design. When Apple launched the iPad in 2010 and with it iBooks, he insisted on polished woodgrain bookshelves, page-curl physics, and faux-leather stitching. After he passed away, Apple discovered that such embellishments were actually reader distractions.

Want a more current example? Think back to the Covid era when virtual conferences replaced (by necessity) in-person events. The near unanimous verdict on virtual conferences: They all sucked. Why did they suck? Because organizers attempted to replicate the IRL experience – virtual general sessions, virtual breakouts, virtual exhibit halls, virtual cocktail hours. They ignored the technology that was available to create an exceptional experience in favor of technology that created a familiar experience. (Incidentally, Finopotamus is working on a fix, but that’s for another discussion.)

I’m not aware of any credit unions that have employed skeuomorphic design. However, I do think most are guilty of skeuomorphic thinking. In the face of the digital revolution, they’ve been trying to figure out how to move that legacy member experience into the virtual world. The question they should be asking is: If I were to start a credit union today, using all the tools I have available and with all I know about my members and their needs, what would that credit union look like? Then they should work toward that.

In Part 2 next week: Why Mint and data aggregators failed, what credit unions can learn from Walmart Supercenters, and how to turn back-office orchestration into the ultimate member experience.

In 1997, after I had left Symitar the first time, I was the editor of a local San Diego computer magazine called ComputorEdge. The magazine had somewhat of a cult following – it gave starts to Dan Gookin, who wrote the first For Dummies book, and Andy Rathbone, who wrote a bunch more For Dummies books. So when Cox Cable launched its home Internet service, my family was chosen to be one of the first households in the Greater San Diego Area to have that blazing fast 2Mbps cable Internet service installed.

The Need for Speed

As a somewhat heavy computer user, I had already grown to hate the chore of installing and updating software via physical media. I remember one of the first thoughts that occurred to me when the Cox installer left was: If “they” get this right, I may never have to install another software update again; it can just come down over the Internet and install itself. And if “they” really get it right, I won’t ever have to install software again, either. I’ll be able to run it over broadband, assured that I’m always running the latest version. Basically, I predicted Google Docs about nine years before Google did. (Don’t be impressed by any of this. It’s more like one of those broken-watch things.)

I didn’t realize at the time that I had become a pioneer in a paradigm shift that would eventually envelop the entire credit union core data processing industry. Neither did I realize that all the small credit unions running their cores in a service bureau environment – the ones that couldn’t run Symitar because it was an in-house solution – were also pioneers in this same movement. I’m talking about the seemingly inevitable and insatiable quest for OPC.

OPC: Just as Important as OPM

OPC, you say? What might that be?

I’m talking about other people’s computers, of course.

I’m willing to bet that you’ve never heard little service bureau credit unions framed as tech pioneers. Maybe that even sounds like something from the Upside Down. But think about it for a minute – or two.

Forty years ago, running your core in-house was the ultimate sign of technological savvy, sovereignty and superiority. Put another way, if you ran a big IT shop with a big IT staff, you were a badass.

And that was fine with your core processor. They didn’t have to invest a dime in data centers and got to completely dodge the operational liability bullet. If a disk blew up, who ya gonna call? Whoever held your hardware maintenance contract. Your processor’s software ran on OPC – except in this case, the “other people” were you and your credit union, and the “computers” were the ones you had to buy and maintain.

Meanwhile, the little service bureau credit unions were content to focus on the business of running a credit union and let OPC do what OPC is supposed to do.

The Big Shift

Thanks largely in part to improvements in bandwidth, things started to change. First came the single-tenant ASP (application service provider) model of OPC. That gave way to the multi-tenant SaaS (software as a service) model. And suddenly, smart credit unions were running more and more ancillary products off-prem.

I think it was about 2010 when Jack Henry decided to offer a hosted version of Episys, which was the Symitar product name at the time. They called the hosted version EASE, or Episys as a Service – a name that I thought up. It was a somewhat easy lift for Jack because they already had a couple of data centers in place running hosted versions of their banking platforms.

At first, it was just a trickle, but gradually, bigger and bigger Symitar credit unions began to migrate to EASE. It was a great double-dip for Jack. Get ‘em once with the hardware, services and software licenses that go with an in-house install, and then lock ‘em in later to a fat monthly service fee for the hosted solution.

Or looked at another way, the bigger credit unions finally figured out what the little service bureau credit unions had known for decades – namely that it’s always better when you can make it work with OPC.

Cores love hosting their own solutions because they love the predictable recurring revenue. As Jimmy Cole once said, it’s the lure of easy money; it’s got a very strong appeal. Except it’s not as easy as it looks. Being someone else’s OPC is expensive in many ways. If you run or have ever run an in-house shop, try multiplying that by 50 or a hundred credit unions.

Which brings us to our current cloud-centric world.

Stick to What You Do Best

Why in the world would any core processor try to out-OPC Google Cloud or Azure or AWS – or even think that they could? It seems like insanity to me.

So there’s my bold prediction. Are hosted core solutions going away? Not a chance. The little service bureau credit unions have known this all along. The question is: Who’s going to host them? Clue: It ain’t gonna be the core providers and their legacy data centers.

At that point, we will have achieved the perfect trinity. OPC providers like Google and Microsoft and Amazon can focus on doing what they do best. Software developers like Corelation and Jack Henry and Fiserv and Mambu can focus on what they do best. And even the biggest credit unions can make like little service bureau credit unions and focus on what they do best.

I hear more and more about alternative credit data and the scoring models it drives. However, it’s always discussed as either an add-on to those legacy three-digit scoring models or a “second chance” workflow for would-be borrowers who didn’t make the first pass with a legacy three-digit scoring model.

Why is that? Alternative underwriting either works or it doesn’t – and it obviously does or I wouldn’t be writing this. And if it works so well that we can use it to underwrite loans that in the past we wouldn’t have touched with a 10-meter cattle prod, why do we even need those legacy three-digit scoring models at all? Isn’t that the true definition of credit democratization – everybody being evaluated the exact same way, based only on their own financial habits, real-time cashflow, and actual capacity to pay?

Super Prime Is Super Sublime

Part of the reason we hold onto legacy scoring is, of course, convenience. It’s familiar and arguably reliable. In other words, it belongs in the “because that’s the way we’ve always done it” filing cabinet. But there’s more to it than that.

Super prime is a marketer’s dream. You see that 850 credit score and you can shower that member with the best credit cards, the most lucrative rewards programs, the most favorable mortgage rates, and all kinds of free bennies that people who actually need some free bennies could never hope to enjoy. Super prime is the lender’s easy button. “You want how much? Of course you’re approved!”

To be clear, I’m not begrudging anything of the super primers out there. If you have an 850 credit score, you legitimately have achieved something notable, at least in terms of the rules laid out by the current financial services industry. That said, I wonder if at least a few super primers would feel cheated if credit scores went away and they no longer had that 850 badge to wear.

The Kenyan Conundrum

But suppose you had to start from scratch, with no legacy scoring behemoths to dictate your path. And what if you were operating in a country where the vast majority of consumers were thin file or no file. That’s where Kenya found itself in the mid-2000s when a few visionaries realized it was time for a major financial technology upgrade.

The whole story is quite interesting and inspiring, but I’ll leave that for another time. The key component here is the decision by SACCOs (savings and credit cooperative organizations, the local term for credit unions) and other financial providers to leverage alternative data for all loan underwriting. If you apply for a loan in Kenya, your SACCO will use AI to analyze things like your M-PESA transaction velocity, airtime purchases, and utility bill habits to underwrite the request.

And it’s all working quite well. Today, a SACCO member can apply for an emergency loan via a mobile app or USSD prompt and have funds deposited into their mobile wallet within seconds. That’s a standard feature, not a spiffy add-on.

Moving Forward, Getting Ahead

At this point, I feel like I need to pull you over in the corner and give you a good talking to about this “second chance” nonsense. Seriously, wtf? “I’m sorry. You didn’t qualify under the system we use for normal people, but if you want, we can run your application through our Second-Class Citizen underwriting program.” No. Just no.

Anyhow, it seems like every technology today comes with a “you’d better not fall behind” warning. You’d better not fall behind on AI. You’d better not fall behind on open banking. You’d better not fall behind on crypto or stablecoins. Does alternative data belong on this list? I think the answer is a resounding yes.

So what’s it going to be, folks? Are we going to push to keep our credit scores and noses up? Or are we going to return to our credit union roots, underwriting based on character and capacity? Alternative data gives us that opportunity.

This episode of TechSolutions4CUs opens with Finopotamus publisher John San Filippo talking with Palmer about the evolution and impact of the Finovate conference series. Palmer shares what sets Finovate apart from traditional mega-conferences—highlighting its fast-paced, 7-minute live-demo format where slides and pre-recorded videos are banned in favor of working technology.

The discussion explores:

• The Finovate Difference: Why the 7-minute live demo format creates a hyper-efficient environment for financial institution executives to evaluate new technology.

• Dedicated Credit Union Focus: Details on the Credit Union Spotlight session taking place on Tuesday, September 8th, designed specifically to bring credit union leaders and fintech innovators together in a collaborative, dedicated space.

• State of Fintech: Palmer's perspective on how venture capital trends post-2020 have produced more battle-tested, business-minded fintech startups focused on immediate value and clear paths to profitability.

• Keys to a Winning Demo: What separates "Best of Show" winners from the crowd, including clear messaging, ease of implementation, and starting a meaningful conversation rather than delivering a high-pressure sales pitch.

• AI and the Consumer Backlash: Palmer’s prediction on why credit unions must balance AI implementation with member-first service to avoid damaging customer satisfaction scores through frustrating automated interactions.

Listeners can save 20% on their registration for FinovateFall by using the promo code FINOPOTAMUS20.

Case Study
noun

1. the act or an instance of analyzing one or more particular cases or case histories with a view to making generalizations

2. a detailed analysis of a person or group, especially as a model of medical, psychiatric, psychological, or social phenomena.

3. an exemplary or cautionary model; an instructive example.

You’d never be able to tell from reading these boring definitions how critical case studies are to your collateral arsenal when you’re marketing financial technology – or really when you’re marketing any B2B product, for that matter. The reason these definitions don’t do case studies justice is that all three of them ignore the most essential component of an effective case study: human emotion.

Perhaps surprisingly if you’ve seen some of the convoluted case studies floating around out there, the formula for eliciting this outpouring of human emotion is actually quite simple and quite repeatable.

Act 1: The Problem

Start any case study by identifying the problem – or ideally, the set of problems – with which the subject of the case study was faced. You need to be careful here, though. Your solution may solve a boatload of problems, and you certainly can’t dig into all of them in 900 words.

The perfect problem for a case study is one that is a) significant and b) common. But what if you have to choose? What if one problem is more significant and the other is more common? You might be tempted to focus on the more significant problem. Don’t. What’s the value in touting how you solved a problem that nobody else has?

A common problem lets you establish a bond with the reader – which is the whole point of the case study. By the time you’ve laid out the entire situation, the reader should be thinking, I can totally relate to that. In fact, I’m experiencing that problem right now.

Act 2: The Solution

Here you simply tell the reader in very straightforward terms how the subject used your product to address the problem. There’s a big temptation at this point to add marketing words to the story. Marketing words are bad in case studies.

What are marketing words? Here’s an example: Last National Bank used the incredibly mind-blowing power and flexibility of Product X to solve the problem. In a case study, this next version will do just fine: Last National Bank used Product X to solve the problem. At this point, the reader will fully understand and appreciate the significance of Product X solving the problem without you adding any fluffy marketing words.

Act 3: The Results

Now the question you need to answer is: So what? What’s the big deal? Show me the money!

Exactly how you showcase the results will vary from product to product. For example, if you market an IT automation product, you might be able to show results in terms of hours saved. If you market home banking software, you might be able to talk about increased customer/member adoption. You get the picture.

The problem is, not every product lends itself well to measurable, empirical results. For example, suppose you’re marketing a fraud-prevention product. It’s pretty much impossible to measure how much of something didn’t happen. But maybe you got high marks from your auditor for deploying Product X. That’s a result a lot of people would like to achieve.

Don’t Blow It

There are a few common mistakes that seem to creep into a lot of case studies. The biggie, as I mentioned earlier, is the use of marketing words. Your role in a case study is to step back, get out of the way, and let the customer tell their story. Sure, you guide the story, but the customer still tells it. When you start using marketing words, you essentially steal the story away from your customer. Shame on you.

I’ve seen some “case studies” that were nothing more than question-and-answer interview pieces. Maybe this would work if you had a couple of thousand words to play with, but there’s no way you can tell a complete and compelling story in 900 words by simply typing out customer answers to four or five questions.

Lastly, don’t get too clever with document features, e.g., charts, graphs and grids. I’m not saying to never use them; just don’t feel like you’re required to use them. Remember, you’re telling a story – or more accurately, your customer is telling a story. Anything you add that doesn’t contribute directly to the telling of that story is a waste of your time and, more significantly, a waste of your prospect’s time.

In this episode of TechSolutions4CUs, host John San Filippo sits down with Jim Perry, Senior Strategist at Market Insights, for a wide-ranging, candid conversation about why complacency is the single greatest threat to the industry today. Jim brings 21 years of industry experience to the table to dismantle assumptions and look closely at the hard evidence driving modern consumer behavior.

John and Jim dive deep into the converging trends that credit union executives can no longer afford to put on the back burner.

What We Discuss:

• The Reality of Agentic AI: Why "human in the loop" is losing its meaning, and why credit unions must demand vendor accountability instead of just collecting buzzwords.

• The Stablecoin Wake-Up Call: Why a new 140-business payment platform—featuring major players but zero credit unions—means CUs need a real digital asset strategy right now.

• Cleaning Up the "Dirty Data Lake": How real-world transactional data can prevent massive relationship-building misses (including Jim's personal mortgage-payoff story).

• Reaching Gen Z Beyond Tech: Why trying to out-tech mega-banks is a losing game, and how credit unions can win by aligning with Gen Z's passion for community causes.

• A Bold Decade-End Prediction: Why we could see up to 500 fewer credit unions in the next four years if leaders refuse to step outside their comfortable boundaries.

Step out of the comfort zone and tune in for an episode packed with actionable strategy, sharp insights, and a much-needed reality check for credit union leadership.

This article originally appeared on Finopotamus.

If you’ve worked in credit union technology for any length of time, you’ve probably worked on a John Landis-architected core data processing platform. He’s created three of them, all of which are still in service today. They are, in order of appearance, Fiserv Galaxy, Jack Henry Symitar, and his current venture, Corelation KeyStone.

Finopotamus met with Landis at Corelation’s now largely empty headquarters in the Liberty Station area of San Diego. The facility was designed to accommodate hundreds, but the company went remote during the pandemic and never looked back. Now, except for semiannual company meetings that bring everyone together, only a handful of employees work from the office on a regular basis.

It’s impossible to separate the story of John Landis from the history of credit union core data processing in the United States. To truly understand his impact, one must look at how the evolution of financial technology has mirrored his professional journey, from the era of punched paper tapes to the modern landscape of open APIs and cloud-capable environments.

The Era of Mainframes, Paper Tapes, and BASIC

Landis did not set out to revolutionize the credit union movement. Fresh out of college, he was working at Ektelon, a sporting goods manufacturing company owned by his best friend David Held’s father. The business had purchased a Data General computer system. “David’s dad had bought a computer system and we thought, ooh, that would be fun to find out about,” Landis recalled.

The two quickly became self-taught experts on Data General hardware. In the mid-to-late 1970s, computer power was unimaginably constrained by today’s standards. “These were Novas and the early Eclipses,” noted Landis, referring to some of the earliest Data General models. “You had 64K of memory and 10 megabytes of disk space.” At the time, a company called World Computer had introduced the first minicomputer-based in-house system for credit unions, disrupting a marketplace previously dominated by mainframe service bureaus.

A small San Diego data processor called Complete Business Services, Inc. (CBSI) noticed World Computer’s success and decided to shift from its Burroughs mainframe shop into the minicomputer market. A Data General salesman sold CBSI on the necessary hardware and subsequently recruited Landis on behalf of CBSI to build the software.

“I didn’t know what a credit union was,” admitted Landis. “I had no clue, but I picked it up and wrote them a system that eventually went through two or three acquisitions.”

The technology landscape of the late 1970s was deeply primitive, he added. Some payroll deposit distributions from employers still arrived at credit unions on punched paper tape, requiring a dedicated paper tape reader. Core functionality was straightforward. “Things were pretty simple back then,” Landis explained, “It was basically a teller line, batch ATM, posted dividends, statements.” Automated clearing house (ACH) records and batch ATM transactions were processed via reel-to-reel tapes delivered by couriers.

Landis developed this first system in BASIC because it was the only language available on minicomputers that could support multiple CRT terminals simultaneously. Through successive corporate acquisitions—first by ICCI, then by Citicorp Information Resources—this platform matured and became known as Galaxy (later acquired by Fiserv).

A Meeting at Wendy’s and the Genesis of Symitar

By the early 1980s, corporate consolidation had fundamentally changed the workplace dynamic at Citicorp. Landis brought his friend Held into the company, but frequent corporate restructurings created persistent internal friction. Landis described the management culture as “boss du jour,” adding, “We reported to somebody different about once a month. It was just chaos and not user-friendly to the clients.”

The turning point occurred during a now-legendary lunch invitation at a local Wendy’s restaurant. Manny Prupes, who managed the in-house division, asked Landis to join him in launching a new venture. Landis reflected, “I never would have done it the first time by myself.” He credited his career trajectory to two individuals: the Data General salesman who introduced him to credit unions, and Prupes, who provided the entrepreneurial push.

In the spring of 1984, Landis, Prupes, and Held left Citicorp to found Symitar, establishing equal ownership among the three founders. They hired Theresa Benavidez, who had worked alongside Landis since the late 1970s as a trainer and conversion specialist, as employee number one. Working out of Landis’s home closet and bedroom on a 16-bit computer, he and Held engineered the software from scratch. They converted their first credit union client on January 1, 1985.

In launching Symitar, the founders didn’t focus on bleeding-edge technology as a key differentiator. Credit union cores were still relatively simple, making it difficult to differentiate on technology. Instead, their primary motivation was an unwavering commitment to customer service. They believed that providing superior support and treating clients like family would separate them from large, bureaucratic corporate entities.

Technologically, they migrated from BASIC to PL/I, a compiled mainframe language that delivered the highest performance on Data General hardware at the time. Symitar experienced significant market tailwinds when World Computer struggled with a problematic software rewrite called WorldWorks, which became known in the industry as “World Doesn’t Work” according to Landis, allowing Symitar to steadily capture market share.

Navigating Major Hardware Transitions and Scale Limitations

As the 1980s transitioned into the 1990s, computer hardware underwent a massive structural shift. Proprietary minicomputer architecture was reaching its physical limits. Landis told Finopotamus that core processors of that era were massive circuit boards soldered with numerous integrated circuits, before miniaturization consolidated systems onto a single silicon chip. Data General struggled to exceed clock speeds of 100 MHz, while newer Reduced Instruction Set Computer (RISC) chips quickly bypassed those limitations.

To maintain performance scalability, Symitar decided to look at the RISC-based IBM RS/6000 platform. Landis recalled, “We benchmarked the IBM RS/6000 and went, ‘Holy crap! This thing is so much faster!’”

This shift required moving away from Data General’s proprietary operating system, AOS/VS, to IBM’s variant of UNIX, known as AIX. This transition provided a more standardized environment and drastically expanded computing speeds. Within five to six years, Symitar completely phased out its Data General hardware footprint.

Following the passing of Prupes, the remaining owners decided to sell the company to Jack Henry & Associates in the spring of 2000. At the time of the sale, Symitar had roughly 250 employees and 250 clients. Landis agreed to stay with Jack Henry for five years to oversee critical engineering initiatives.

The most prominent engineering challenge stemmed from an architectural decision made in 1985. Symitar had been built utilizing a 32-bit integer system for financial balances, meaning account values capped out at approximately $21 million. While sufficient in the mid-1980s, this limit restricted scalability for larger institutions. Landis personally engineered the data expansion project, restructuring the fields, transactions, and balances across the system to accommodate asset sizes reaching into the trillions.

Act 3: Corelation KeyStone

By 2005, corporate alignment diverged, and Landis chose to depart Jack Henry. After resting for a few months, he rented a modest 100 square foot office, purchased an IBM RS/6000 server, and began coding the foundation of his third core system, KeyStone. He worked solo for two years before hiring Jeff Dent as employee number one to design the user interface, while Landis focused on backend architecture. Benavidez joined shortly thereafter as employee number two, followed by Landis’ son, Rob, currently the company CEO, as employee number three.

Corelation was founded with both a service-first philosophy and a radically superior technological blueprint. Rather than relying on homegrown databases or proprietary constraints, Landis utilized universal, modern industry building blocks. KeyStone was written in C++ and designed with a pure, browser-based user interface.

While the architecture stack was built to be completely swappable from day one to ensure the platform remained future-proof, it was originally designed for IBM Power Series servers running the AIX operating system. Over time, as Intel and AMD x86-64 hardware and Linux proved to be the platforms of the future, Corelation officially announced support for that environment. Today, all new on-prem conversions run KeyStone natively in this x86/Linux environment with absolutely no difference at the application layer.

Architecturally, the platform was compiled from the ground up to support native multi-threading and uninterrupted 24/7 operations. Landis built extreme structural resilience into the system, ensuring that if power was abruptly severed, the core could simply reboot and resume processing transactions without corruption.

A central feature of KeyStone’s market success is its KeyBridge API. This tool emerged naturally from Landis’s desire to isolate the web-browser user interface from the backend business logic. By building an identical API channel for internal and third-party use, Corelation pioneered an “API-first” framework long before it became an industry-wide mandate.

An Open Playing Field and a Nationwide Workforce

Corelation established an intentionally disruptive business strategy within the financial technology sector: a third-party agnostic approach. Unlike traditional legacy core processors that monetize ancillary applications or charge steep integration fees, Corelation deliberately chose not to charge credit unions or vendors for utilizing the KeyBridge API.

Landis asserted, “We provide the connection. You can connect up anything else you want.”

By refusing to compete directly against specialized third-party vendors for ancillary software packages, Corelation preserves an entirely level playing field. This framework empowers credit unions to seamlessly implement a best-of-breed technology stack without incurring punitive core integration expenses.

This progressive philosophy extends directly into Corelation’s operational environment. Following the disruption of the COVID-19 pandemic, the firm embraced a remote-first organizational model. This strategic pivot lifted geographical hiring constraints, allowing Corelation to source top-tier engineering, conversion, and support talent across the entire United States.

While Landis acknowledged that remote operations lose the spontaneous “water cooler” collaboration of a physical office, the operational gains have been immense. Staff morale remains high due to eliminated daily commutes, and the company reinforces corporate alignment by flying its entire nationwide workforce to San Diego twice a year for comprehensive team-building and strategic meetings.

Reflections on a Lasting Legacy

Today, Corelation services roughly 300 signed credit union clients, managing monumental transitions like the recent migration of Mountain America Credit Union – an institution three times larger than any client the company had previously converted.

As Landis shifts into a part-time capacity to focus on his long-term health, he deliberately avoids immersing himself in new technology cycles. He joked that adding items to a technology bucket list would inevitably sentence him to the grueling schedule he endured during KeyStone’s peak development phase, when he averaged 11-hour days, seven days a week, for 11 straight months.

When reflecting on a multi-decade career that drove the credit union industry from 1 MHz single-core minicomputers to massive multi-core Linux server clusters handling terabytes of memory, Landis remains characteristically modest. He traces his unparalleled career back to a few minor, unpredictable decisions that completely shifted his path.

Beyond the lines of code, compiled databases, and open APIs, Landis occasionally contemplates the human element of his legacy. The corporate cultures he fostered gave rise to lifelong friendships, professional mentorships, and even marriages and families among the employees who helped build his companies.

Throughout it all, Landis has never lost sight of the primary lesson he absorbed from Prupes: Technology is merely a vehicle. True success is dictated entirely by client service. Landis summarized this foundational philosophy cleanly: “The product is only one piece of the puzzle. You’ve got to have a good product, but you can’t have a good product and bad service.”

Redefining the MSP Model

Finkenbinder explained that traditional MSPs typically require a credit union to fully outsource a specific tech stack or function, which often leads to vendor lock-in and a loss of technology ownership. Veritium differentiates itself by ensuring that clients retain full ownership of their environments. Finkenbinder noted, "We're really trying to co-manage these environments with our customers and enable them, if they should want to develop the appropriate skill sets with the solutions we provide."  

For instance, under their cloud networking solution, Veritium helps clients directly acquire their own data circuits and hardware infrastructure rather than leasing them through the provider. This approach allows institutions the flexibility to swap out specific services or vendors without having to replace their entire technical setup. 

Zero Installation Fees and Outcome-Based Pricing

A primary element of Veritium’s business model is the complete elimination of upfront integration and installation fees. Instead of billing for hours spent on architecture and migration, the company charges a flat percentage based on the client's cloud spend. Finkenbinder stated, "We think you should pay for outcomes, not billable hours."  

This fee structure ties Veritium's revenue directly to the client's financial performance. When Veritium actively monitors and optimizes an environment to decrease cloud spend, the amount the client pays to Veritium decreases as well. Finkenbinder highlighted this risk-sharing philosophy by offering an example of a client who chose to turn off an AWS cloud solution after a leadership change. Because the cloud spend dropped to zero, Veritium received no payment for the upfront setup work. However, this transparency avoided locking the client into a restrictive contract, preserving a partnership that eventually led to other projects. 

Navigating AI and Compliance

Finkenbinder discussed how mid-tier and smaller credit unions frequently struggle to staff specialized technical roles for advanced projects like artificial intelligence (AI) and data analytics. Veritium mitigates this by providing access to its own global workforce to act as an extension of the credit union's staff. 

When implementing AI internally or assisting clients with governance, Finkenbinder emphasized that human oversight remains critical. He stated, "Whoever is leveraging it is it needs to be the person responsible for the output."  

Furthermore, the podcast touched upon regulatory compliance. Veritium maintains SOC compliance, undergoing annual audits and utilizing continuous AI-driven testing to monitor its internal systems. Finkenbinder concluded with the prediction that the financial industry is only at the beginning of the AI journey, comparing its ultimate societal impact to the introduction of the Internet. 

As I go through life interacting with various chatbots on various customer/member service phone lines, I make a mental note of each experience in an effort to track the progress of the technology. Most often, the experience falls somewhere between this sucks and this really sucks.

I should preface this by noting that I’ve been a California driver for nearly 50 years. And based on decades of experience dealing with the California Department of Motor Vehicles, I’ve come to expect very little from this esteemed organization. I’ve found that most interactions with the DMV are some combination of woefully boring, painfully time-consuming, and ridiculously expensive.

Well, just the other day, I was looking at the registration renewal for my personal vehicle and noticed that it was marked as a commercial vehicle. I looked back at my current registration card and it was marked the same way. It’s an error I just never noticed before. So I braced myself for a this really sucks phone experience and dialed the DMV.

An Unexpectedly Perfect AI Hand-Off

Imagine my surprise and delight when I reached the absolute best chatbot I’ve ever encountered. I sh*t you not. She was awesome. She was able to understand every word I spoke and respond with complete, human-like sentences.

She informed me that unfortunately she can’t make such changes herself and that I’d need to speak with a live agent. However, since no live agents were currently available, she’d be sure to have one call me later. What’s more, to ensure that I didn’t miss the live agent, she promised to send me a text message when the agent was ready to dial so I’d know the next call would be from the DMV.

Absolutely fabulous! Or so I thought. The problem was what happened next—or should I say, what didn’t happen next.

You see, I never heard from the live agent. And I know I didn’t miss their call because I also never received that text—a text I assume was supposed to be automatically triggered by the agent preparing to call me.

Was this a technology failure? A human failure? A little of both? I don’t know. But I do know that from a user standpoint, it was the live agent who let me down.

Where the Loop Breaks Down

I’ve written about “human in the loop,” or HITL, numerous times. It’s a concept that seems tailor-made for the credit union movement. We pride ourselves on the “human touch.” Using advanced AI to handle the mundane tasks while routing the complex, high-value interactions to live staff has become the gold standard of modern member service.

But here is the hard truth: It only works if the humans in your loop actually do their part to fulfill the promise of a better, AI-powered world.

It’s not complicated. Write a big enough check and I’m sure you can have the same awesome chatbot as the DMV. Likewise, fail to train your employees on the importance of the digital handoff and you’ll achieve the same end result as the DMV.

Your members deserve better.

The bottom line: Don’t be the DMV. If you’re going to build a high-tech loop, make sure your humans are fully awake and ready to steer when it’s their turn at the wheel.

Together, the panel explores how credit unions can successfully compete against major banking institutions, transition away from manual processes, and leverage next-generation technology to safeguard their portfolios.

Key Discussion Highlights

• The Credit Union Opportunity: While credit unions traditionally focus on consumer lending, the commercial space offers a prime avenue for driving yield and gathering deposits. Larger credit unions have excelled here for decades, and many are now efficiently scaling their operations—even acquiring community banks to absorb established commercial lending teams.

• Fierce Competition & Relationship Banking: Competing against massive national banks requires a strategic approach. While the heavy hitters dominate commercial and industrial (C&I) lending, credit unions can find immense success in commercial real estate (CRE). Credit unions hold a distinct advantage through true relationship banking—building deep, trust-based partnerships over a cup of coffee—that larger institutions struggle to replicate.

• The Danger of Excel and the Shift to Tech: For institutions managing just a few CRE deals, spreadsheets might suffice. However, as a portfolio scales past a couple hundred million dollars, technology becomes critical. The experts discuss why relying on manual spreadsheets is unsustainable and risky, as a single multi-million-dollar bad loan impacts an institution far differently than a standard auto loan default.

• Core Integration & Eliminating Human Error: A seamless two-way flow of data between a loan origination system (LOS) and the credit union's core platform is vital. The guests explain how mapping hundreds of data fields reduces hours of redundant manual data entry, cuts down on human error during loan booking, and gives underwriting committees a comprehensive view of a member's entire relationship.

• AI as an Enablement Tool: Looking toward the future, artificial intelligence is highlighted not as a replacement for relationship bankers, but as a powerful tool to eliminate administrative friction. From automating the spreading of tax documents in milliseconds to providing early warning indicators for portfolio monitoring, AI allows lean teams to cover more ground and proactively manage risk.

It isn’t every day that the Vatican weighs in on tech stack ethics, but Pope Leo XIV’s recent encyclical, Magnifica Humanitas, managed to strike a chord that resonates far beyond the walls of Saint Peter’s. In his address, the Pope called for humanity to “disarm” artificial intelligence.

Before you lose your mind, he wasn’t advocating for a return to the dark ages or suggesting we smash all our server farms. Instead, he warned against an “armed logic of competition” driven by pure commercial dominance – a world where a technocratic elite holds all the keys, ultimately widening the gap between the technologically included and the excluded.

This seems to be a discussion that has credit union written all over it.

We often talk about the fintech “arms race” in purely existential terms: If we don’t adopt the latest shiny thing, we risk obsolescence. But the Pope’s perspective forces a deeper question: Who are we arming ourselves against, and at what cost to our core mission?

Right now, the AI landscape is heavily consolidated. A handful of massive tech giants control the primary infrastructure, while the nation’s largest megabanks spend billions to monopolize automated efficiencies. If credit unions simply buy into closed, black-box AI models off the shelf, we aren’t leveling the playing field; we’re climbing the fence and sneaking onto somebody else’s field. (It is baseball season, after all.)

True “disarmament” in fintech means rejecting the hyper-aggressive, growth-at-all-costs mindset of big tech. It means demanding open-source, democratized AI tools that smaller institutions can actually access, understand, and control.

More importantly, it requires us to double down on what the encyclical calls the spaces where machines cannot mature: relationships, empathy, and responsibility – areas where credit unions already lead.

When a megabank deploys AI, the goal is often total automation – eliminating human friction to maximize transaction volume. When a credit union deploys AI, the goal should be the exact opposite. We should use automation to absorb back-office friction precisely so our people have more time to engage in the human-centric, relationship-backed financial guidance that defines our movement.

As we navigate the next wave of technological disruption, let’s ensure we use AI as a force multiplier to empower local communities, rather than an algorithmic weapon that alienates them.

In our quest to be more agile and more nimble and more buzzword compliant, we seem to have become convinced of the value of “failing fast.” It makes sense, right? If you’re going to fail, do it quickly so you can move on to the next thing without wasting too much time or money. It sounds pragmatic, even sophisticated. But let’s be honest with ourselves. The operative word in “failing fast” is still failing.

Like it or not, tech success is often a function of budget. And when you consider that Chase and Wells and Citi probably spend more on toilet paper for the employee restrooms than you spend on tech, doesn’t it make more sense to devote your limited resources to succeeding fast instead of failing fast?

The Myth of Productive Failure

The idea that it’s ok to fail – fast, slow or somewhere in between – can be used as cover for a lot of deficiencies. It wasn’t poor planning; we just failed fast like we’re supposed to. We didn’t lack conviction; we just wanted to fail fast and move on. Our MVP missed on the V part? We just made sure we failed fast. You’re supposed to learn from all these failures, but quite frankly, I don’t think the credit union industry can afford to provide on-the-job training in failure to anyone.

I’d like to remind all the credit union technologists and fintech wiz kids out there that in our unforgiving, even cutthroat world, there are no participation trophies. Nobody will ever say, “Well sure, they failed, but at least give them credit for failing fast.” In short, nobody cares if you almost had a good idea.

The Risk of Failing Too Fast

We all know that speed kills. But have you ever stopped to consider that speed kills good ideas? When you get into a cycle of implement-fail-rush to the next failure, you may be throwing out the baby with the bathwater.

Anybody remember Ronald Wayne? I didn’t think so. Wayne was one of the three co-founders of Apple Computer. He owned a 10% stake, but got a little skittish over a $15,000 loan that Steve Jobs had taken out. So 12 days after co-founding Apple, he sold his shares back to Jobs and Wozniak for $800. I’ll let you do the exact math if you want, but my point is, failing fast cost Wayne tens of millions of dollars.

Isn’t there a chance that one of your “failures” could have been a massive success with just a little more effort and discipline? If you’re always instinctively headed for the exit door, your chances of getting called up to the winner’s podium are slim. Real innovation requires the stamina to work through the friction, not just the speed to run away from it.

The Opportunity Cost of Failure

We can’t ignore the time factor here, either. There are only so many hours in a day. If you spend all your time failing, how much time does that leave for succeeding?

When we celebrate the alleged lesson learned from a failure without scrutinizing the time lost, we’re not considering the true cost of that failure. Your board of directors and your members don’t pay for expensive lessons; they pay for results. Every hour spent pivoting away from a fast failure is an hour you didn’t spend building something that actually works.

AI: Failing at Scale

This problem is only getting worse with the rise of generative AI. That’s right. I said worse.

Today, AI gives everyone the power to fail faster than ever before. It allows teams to churn out mediocre code, “slopaganda” content, and half-baked strategies at a volume that used to take months of human effort.

We’re mistaking the speed of iteration for the quality of innovation. Just because you can automate a thousand pivots doesn’t mean you have moved an inch closer to a win; it just means you’re getting lost at the speed of light. AI should be a tool for precision, not a factory for digital participation trophies that allows us to be reckless at scale. Use AI to succeed faster than ever before, not fail faster than ever before.

The Effort to Win

“Winning isn’t everything; it’s the only thing.” That’s the most famous quote from the great Vince Lombardi: However, many people forget he tempered that with a dose of reality in this quote: “You can’t always be first, but you have to believe that you should have been – that you were never beaten – that time just ran out on you.”

What does this have to do with credit unions and fintechs? When you go into a project with the safety net of failing fast, you lose the edge that comes from needing to win. If you are not putting in the effort to win – and win big – from the get-go, you’re just practicing how to lose.

Lessons from the GOAT

I had the privilege of being invited to Velera LIVE in March. Certainly, one of the highlights for me was a keynote by Tom Brady. Not surprisingly, Brady didn’t talk about the virtues of failing fast so he could get to the next Super Bowl. He focused on the relentless, almost obsessive preparation required to ensure he did not fail at all.

Brady noted that later in his career, he thought about how he could use his time in the most efficient way to be as prepared as possible for those moments on Sunday. He explained, “It always came down, in my mind, to the processes over the outcomes.” He told the audience that when you prepare your best, you do everything to not leave the game to chance.

The Opponent in the Mirror

There is, of course, a fundamental difference between the gridiron and the boardroom. On the field, the enemy has a face and a jersey. In credit union fintech, there is rarely a head-to-head opponent trying to tackle you. In one sense, it’s you against the world; in another, it’s you against nobody but yourself.

That makes the “will to win” even more critical. When there is no visible adversary pushing you, the temptation to succumb to inertia is overwhelming. But in a world where we are our own toughest competition, winning requires a level of internal standards that perhaps doesn’t put too much emphasis on failing fast.

The Will to Win

I’ve always said that if I’m down by 17 points going into the fourth quarter, there are only three people I want handling the ball: Michael Jordan, Kobe Bryant, or Tom Brady.

It’s not because of how they played the game. It’s because of their will to win the game. Brady reminded us of this talking about his 28-3 comeback against Atlanta, noting that while there might have been a 99.9% chance the Patriots were going to lose, that probability would only have become 100% had they given up. He told his teammates that they might run out of time or they might lose, but they were not going to embarrass themselves by quitting.

Success is ultimately measured by whether you actually succeed. We need to stop celebrating the “fast fall” and start demanding the “fast win.” Because let’s be honest – if you’re not playing to win, you might as well stay home.

PS to TB12: One F bomb in a presentation like yours might seem edgy and provocative. Three of them, coupled with 10 S bombs, seem excessive and unprofessional, even to a shit-talker like me.

The conversation explores Elizabeth’s diverse background, including her time at State Street, her role in scaling Belmont Savings Bank from $800 million to over $3 billion, and her eventually finding her "professional home" within the credit union movement. Elizabeth also discusses her landmark testimony before Congress regarding the ethical use of Artificial Intelligence in financial services.

Key Discussion Points

• A Non-Linear Path to Tech: Elizabeth reveals how she pivoted from journalism and accounting to find her passion in business leadership and technology implementation.

• The Shift to Credit Unions: Discover why Elizabeth initially thought credit unions might be "sleepy" and how her experience at Great Lakes Credit Union completely changed her perspective.

• AI and Advocacy: Elizabeth details her journey to the House Financial Services Committee, where she testified on the impact of AI and the need for balanced regulation that doesn't "handcuff" innovation.

• The "Amazon Effect" in Banking: A deep dive into the technological challenges facing credit unions today, including the need for seamless member journeys and competing with agile fintechs like Chime.

• Women in Fintech: Elizabeth makes a passionate plea for more women to take risks and pursue leadership roles in technology, emphasizing the importance of mentorship for the next generation.

About the Guest

Elizabeth Osborne is a seasoned financial services leader with extensive experience in technology, M&A, and strategic operations. After serving as the COO at Great Lakes Credit Union, she joined Jack Henry to oversee infrastructure, hosted services, and support for the credit union side of the business. She is a frequent speaker on digital transformation and a dedicated advocate for female empowerment in the tech industry.

Featured Quotes

• "Try something new, be a little uncomfortable, that's okay. Because I really believe that that will help open up a lot of doors."

• "I always say there's vendors and there's partners... Jack Henry was always a partner."

We’ve been living the future for nearly 20 years.

Let me take you back to the year 2004 as we thumb through the pages of a new book from psychologist Barry Schwartz called The Paradox of Choice: Why More Is Less. Backed by research, Barry’s premise was simple: While some choice is better than no choice at all, too much choice can be even worse, leading to all sorts of misery, namely …

• Analysis Paralysis: If you’re given a thousand options and you’re expected to choose just one, the effort can be so mentally exhausting, you end up not choosing at all.

• Anticipated Regret: Also known as buyer’s remorse, if you finally do make a choice, you may be haunted by the possibility that you really didn’t make the best choice.

• Escalation of Expectations: If you put in all that effort to choose, you’re going to expect a great choice. But what if you only make a good choice? You may come to look on your good choice as a bad choice.

It all makes sense … to a point.

Netflix: The Case Study

A mere three years later, Netflix launched its streaming service and the world changed forever. Eventually, Netflix came to be seen by people smarter than I as proof-positive of Barry’s paradox. They even coined the term “Netflix Syndrome,” where you spend an hour scrolling and clicking and reading descriptions, but never watching, instead giving up in frustration and hitting the sack.

I dunno. Is that really the user experience that 250 million+ people are paying anywhere from $8 to $25 or more a month to “enjoy”? Maybe Netflix Syndrome was a thing 15 years ago, but I believe that people have become accustomed to having a seemingly infinite number of choices. In fact, dare I say, they even expect it. With that thought in mind, I posit that Netflix is, in fact, a fully composable digital entertainment platform – a true pioneer in composability.

Can you see where I’m headed with this?

The Future of Core Processing

Composability is one of the hottest topics in core data processing – and with good reason. In an era when every tech vendor under the sun promises to “future proof” your credit union, a composable core truly delivers on that promise.

Although Mambu is new to the US credit union space, their composable core platform is already deployed globally in a wide range of financial institutions. Jack Henry is building its composable core, the Jack Henry Platform, from the ground up. And Fiserv is starting to figure out how its latest acquisition, Finxact, will play in the Fiserv ecosystem.

What’s the big deal about a composable core? Why are major players making this pivot?

Think of your legacy core as a Barbie Dream House. It’s big and it’s beautiful and it’s everything you’d expect a Dream House to be. But in a crowded market where the only thing you really have to offer is anything that differentiates you, why would you want the same Dream House as every other Barbie in town?

Now think of the composable core as a LEGO set. You start with an empty baseplate and then build it out any way you see fit. If you’re really ambitious, you can grab a handful of bricks and get down to business. Or if you prefer, you can buy a predesigned rocket ship, knowing it will snap right into place on that LEGO baseplate.

The point is, a composable core gives you back (assuming you had it at some point) your technological sovereignty. You can architect exactly the core platform that you and your specific members need – a unique environment that wouldn’t be right for any other credit union but yours. And if you need a new rocket later, just unplug the old one and go. That’s what I call future-proof.

The nifty thing is, you can begin to take advantage of a composable core without the pain and anguish of a full-blown core conversion. Because composable cores are built the way they are, you can deploy one in a so-called speedboat setting where you keep running your legacy core but rely on your composable core do handle all the cool stuff your legacy core can’t, the thinking being that eventually you won’t need the legacy core at all.

But …

Why Stop at Core?

Composable isn’t just a good idea for movie night and data processing. IMHO, it’s a good idea for technology in general.

In my worldview, a composable architecture is even more important for a digital banking platform. Think about it.

Composable technology lets you truly differentiate yourself, right? Who are you trying to differentiate yourself to? Duh. Your members. What’s the most common touchpoint for your members in 2026? Digital banking. So where is it most important to differentiate your credit union for members? Again, digital banking. BAM!

I Couldn’t Stop There

Just as I was basking in the brilliance of my newfound realization about composable digital banking, I got into a discussion with a fintechnologist about the future of AI. He contended that over time, the horizontals (Gemini, ChatGPT, etc.) would become so capable, the specialized vertical AIs would become obsolete. I countered that there would always be a need for specialized knowledge and experience that a general AI could never train on.

Later, while reflecting on that conversation, it hit me like a ton of LEGO bricks. That’s where AI is inevitably headed. Gemini and ChatGPT will evolve into composable AI platforms. They’ll serve as the AI baseplates onto which you can snap any specialized module you need. Double BAM!

There’s my prediction for this week. All technology will eventually become composable. You heard it here first.

Author’s Note: As I was wrapping this up, an image of a composable kitchen appliance popped into my head. Of course, I’m talking about my amazing KitchenAid stand mixer. But I’ll save that discussion for another time. And maybe another newsletter entirely.

This is the text of a keynote I delivered at FinovateSpring 2026 in San Diego.

As most of you learned at breakfast, I’m John San Filippo, publisher of Finopotamus – Fintech News for Hungry CUs. I’ve been in the credit union technology space for 37 years. Back in the day, I was Symitar’s 54^th employee. I worked for Symitar three different times, worked for Bluepoint Solutions, since purchased by Alogent. And somewhere in there I also started another magazine, Credit Union Business. So yeah, this ain’t my first rodeo.

Before we get started, I have a couple of important disclaimers. First, I don’t have a slide deck today. Some people are masterful at conveying their message via PowerPoint. I’m not one of them. I may dazzle you with my words of wisdom or I may put you to sleep, but either way, it’ll be all me.

Second, I’ll be pretty much glued to this podium. Again, some people look very natural and relaxed roaming around the stage. Again, I’m not one of them. For better or worse, I have two titanium knees that I don’t fully trust and I would rather not end up in somebody’s lap.

In the Olden Days

So in my nearly 40 years in this space, there was one immutable rule that seemed almost chiseled in stone. If you hit a brick wall with your current core platform in terms of feature/functionality – or service, for that matter – you had two options. Option 1: Become a master of work-arounds and make do with what you have. I’ve seen people do it. I wouldn’t recommend it. Or Option 2: Go out shopping for a new core to replace the old one.

We all know Option 2 is easier said than done. We’ve heard – or maybe even lived – the horror stories. In fact, I’ve heard a core conversion likened to performing open-heart surgery on a patient as they’re headed for the finish line at the Cherry Blossom 10 miler.

I have some good news, my friends. As you embark on your quest for core modernization, boldly marching into our brave, new, API-first world, there is now a third option. It’s called a sidecar strategy. Or you might hear it as a speedboat strategy. Same thing.

What Is a Sidecar Strategy?

How many people are familiar with the term sidecar as a core modernization strategy.

Incidentally, in terms of metaphors, I prefer speedboat. I mean, think about it. I sidecar can only go as fast as the motorcycle it’s connected to. On the other hand, a speedboat can go … well … pretty damned fast, all on its own. But whatever. Sidecar is the more common term, so we’ll stick with that today.

So what is a sidecar strategy? Instead of finding a new core to replace your old core, you find a new core to add to your old core. Your heard me right. You voluntarily elect to run two cores in tandem.

I know what you’re thinking. John, why on God’s green earth would I possibly want to run two cores? It’s hard enough just running the one.

The answer boils down to speed to market, because in the world today, it’s not only what you offer; it’s also how quickly you can offer it.

Following Fast Isn’t Fast Enough

For years, I’ve heard credit unions almost brag about being so-called fast followers. I’ll keep my eye on this Internet banking thing for a couple of years and if it catches on, I’m all over it. Well, I have some bad news, Skippy. Today you don’t have two years to wait and see. You might not even have two months to wait and see. So go ahead and be a fast follower. Just promise me you’ll adjust your definition of fast down to a matter of weeks or even days.

That brings us to the first major advantage of a sidecar core. It’s not the functionality it brings to your credit union; it’s the functionality it brings to your credit union now. Think about it. How long does a core search take? Then if you’re looking at a popular core, your conversion date might be a couple of years out. From the time you say, “Holy crap, we need a new core,” to the time you actually have one can easily be three years or more. What happens when you’re forced to wait three years to innovate? I can almost promise that the world will pass you by as you’re stuck in that pre-conversion holding pattern. You simply do not have that kind of time to waste.

On the other hand, tech providers that specialize in this area can stand up a sidecar core in a matter of weeks if pressed to do so. Since you’re keeping your old core, your employees will continue to work as they always have. In the meantime, you have a powerful new platform with which to innovate, iterate, collaborate and get as crazy as you want – all with very little long-term risk.

How About Some Use Cases

What are some of the most popular use cases for a sidecar strategy? At the top of the list is the ability to power a niche banking initiative with no disruption to your existing brand or operation. I’m talking about creating a discreet digital brand that caters to some market niche. You’ve seen those digital-only banks that cater to gig workers or doctors or freelancers. That could be you. Or when you consider that 30% of retail credit union accounts are really small business accounts in disguise, maybe it makes sense to give those businesses their own dedicated brand with their own dedicated business tools.

Even if you decide you want to support businesses through your primary brand, your legacy core may not have all the features you need to do so in 2026. A sidecar core with good commercial banking chops can take care of that for you.

We all know there’s real real time and fake real time. Any core can handle fake real time, but when it comes to real real time, not every legacy core is ready to face the challenge. Payments are a good example. I imagine just about any core could handle a fake real-time payments scheme like Zelle. But when you get into real real-time payments like FedNow or RTP, a sidecar core may be able to handle the job more efficiently.

Then there’s the potentially big money maker: banking as a service, or BaaS. All those B2C fintechs out there need some sort of real financial institution at the back end to handle all the banky stuff. Do you know who the sponsor bank for CashApp is? It’s Sutton Bank. Never heard of them. How about Affirm? Ever hear of Cross River Bank. Me neither. My point here is, you don’t need to be a Chase or a Citi or a Wells to be a sponsor institution for a fintech. You just need a valid charter and the right tech stack. With those two things, the sky is truly the limit.

Devil’s Advocate

There are plenty of core providers out there who will gladly offer you more detail on the benefits of a sidecar strategy. Mambu comes to mind. Nymbus comes to mind. Even Jack Henry and Fiserv come to mind. I’m sure there are others. Since these companies have the cheerleading squad covered, I’ll mix a metaphor and serve as devil’s advocate for a moment. What are some of the challenges of a sidecar strategy?

The obvious one is cost. If you spend X running your current core, you’re going to spend X plus Y running two cores at the same time. Is it worth it? Of course you need to do all the ROI math. Compare your TCO to the projected revenue from your sidecar-based initiatives. Crunch the numbers. Etcetera, etcetera, etcetera.

However, you also need to keep in mind that there’s one thing it’s impossible to measure. That’s the value of the member who didn’t move to the bank down the street because you were able to offer the right product at the right time. Put another way, you can’t measure something that didn’t happen. And with the right sidecar strategy, there should be a lot of member defections not happening.

That’s something I learned from Jack Henry – I’m talking about the man, not the company – and it’s something credit unions know better than anybody – if you focus on doing what’s right for the customer/member, the money will follow. It always does. I’ve never seen that not be true.

Let’s not overlook the investment in time and talent that’s required to pull off something like this. Just like it takes more money to run two cores, it takes more people to run two cores. Or does it?

Remember how we’ve been telling our employees that AI won’t replace them – how AI will only relieve them of their more mundane tasks so they can focus on more strategic initiatives? I can’t think of many initiatives that are more strategic than successfully deploying a sidecar strategy. This could be the perfect confluence of AI providing you with more available humans at the exact moment you actually need more humans in the loop for a very specific strategic initiative. Play your AI cards right and you could get through this whole thing without adding a single FTE.

Big Data Is the Big Problem

Of course, by far the biggest challenge in deploying a sidecar core is getting a handle on all the data. It was probably 20 years ago when I first heard a conference presenter telling credit unions about the treasure trove of data that was hidden away in their cores and how it was being grossly under-utilized. Quite frankly, I’m stunned at how little progress has been made in this area in the ensuing two decades. Credit unions do recognize that they have this valuable data at their fingertips, but they still struggle with what to do with it. Now factor in data coming from a second core and you have the potential for a real cluster.

But it’s not just a matter of keeping your data organized; it needs to stay synchronized. After all, in the end there can be only one version of the truth. That’s Data Analytics 101. If the sidecar says the member has $500 and the legacy core says $450 because of some batch delay, which one wins? If you don’t have an immediate answer, you don’t have a strategy; you have a lawsuit waiting to happen.

Data management really is the single most important component in any successful sidecar deployment. Get it right and you’re off to the races. Get it wrong and you’re in a ditch on the side of the road spinning your wheels in the mud.

If you’re already in a good place with your data, you have a great foundation for sidecar success. If you’re struggling with your data, you need to fix that now so that you’re ready when your sidecar gets introduced into the mix. And don’t be afraid to ask for a little help from your friends. Your sidecar provider has special expertise dealing with data issues as they relate to this type of project. Likewise, there are plenty of great data consultants out there in Credit Union Land. And the one thing all these potential tech partners have in common is that they want to see you succeed.

Planning for the Future

The last point I want to drive home is that a sidecar strategy is intended to address a current need. It’s not intended to be a permanent fix for anything. As your operation becomes more and more sophisticated, you’re going to want less and less to be juggling two cores. I guess what I’m saying is, when you go shopping for a new sidecar partner, you’re really shopping for your next core platform.

It’s just that unlike the days of yore, you can ease into your new core on your schedule, without a nasty traditional core conversion, while still taking advantage right now of all the feature functionality that core has to offer.

Is “rip and replace” officially dead? It’s probably too soon to ring the death knell just yet. But does “rip and replace” need to make room for sidecar as a viable core modernization option? Absolutely.

Thanks for your time.

This article was first published on LinkedIn Mar. 7, 2026

Democratization and sovereignty are two buzzwords that seem to be popping up everywhere I look. Specifically, I hear a lot of chatter about how the SoFis and Chimes of the world have democratized consumer finance by creating a better user experience. They got rid of so-called banker’s hours, streamlined complex paperwork, eliminated high account minimums, and made high-yield savings and fractional investing accessible to anyone with a smartphone.

Those are all cool features, but is that really what you’d call democracy? I’ll go ahead and say it out loud. I’m calling bullshit. That’s not democracy; that’s figuring out a more efficient way to get consumers to part with their money.

Now consider credit unions. Every member is an owner. One person, one vote, regardless of the size of their balance. This is democracy at the foundational level. The “profits” aren’t paid to large, distant shareholders; they are returned to members through lower interest rates and higher dividends. Seriously, what could be more democratic than that?

But do you know how many times I’ve seen a credit union actually play the democratization card that they all carry in their hip pocket? Zero.

We’re Fighting the Wrong Fight

Executives from credit unions large and small are getting all spun up trying to figure out how to attract Gen Z. The answer, or at least the popular thinking? Throw money at the problem by taking on the digital banks feature for feature.

I’m sorry to burst your bubble, but you will never, ever win a features war with SoFi or Chime, not to mention any of the mega banks. You may be able to play to a draw if you’re really good at it, but you’ll never outright win.

What does that mean to the future of credit unions? Are they doomed because they’ll always be outdigitized by giant, for-profit monsters? Instead of trying to be just like a bank except smaller and happier, how about leaning into the competitive differentiators that make credit unions credit unions – like the ideas of democratization and financial sovereignty?

You’ve seen more than enough research on this topic.

• From EY: 51% of Gen Z respondents cited ESG (Environmental, Social, and Governance) factors as a primary reason for choosing a financial provider.

• From Fiserv: 84% of Gen Z say they make purchasing decisions based on their personal beliefs.

These are just a couple of examples. The point is, Gen Z seems to have found a balance between heart and head. And in a world asking for ethics, transparency, social purpose and democracy in financial services, for-profit banks will only ever be posers. In the meantime, credit unions always have been, are now and always will be the real deal.

Setting Expectations

I can’t tell you how many times I’ve heard someone at a conference tell a credit union audience that their members’ expectations are being set by Amazon and Venmo and the like. Frankly, I think that sets a pretty low bar. How many times has your same-day Amazon delivery shown up three days later? And don’t even get me going on trying to dispute a charge on your Venmo debit card.

So let’s stop chasing the SoFis and the Chimes, and instead beat them at the game only credit unions can win. I think credit unions have almost everything they need to position themselves as the gold standard in consumer financial services. They just need to add a few tech pieces that are uniquely credit union. After all, if your tech stack forces you to walk like a bank and quack like a bank, well …

The Grand Prediction

One day, there’s going to be a secret meeting at Amazon HQ. Jeff Bezos will be presented with a slide deck that suggests the company needs to up its game to keep pace with the expectations set by credit unions. His face will become ashen and his shoulders will slump as he realizes credit unions have something Amazon never will: trust born of ownership, not algorithms.

Mark my words. You heard it here first.

It’s been at least a decade since the tech world became obsessed with creating a “frictionless” user experience. To be sure, frictionless beats the heck out of the alternative. However, more often than not, we define friction as entirely a process problem. We assume that if we streamline the process, the friction goes away.

Not necessarily. While we put all our effort into addressing functional friction, we often ignore cognitive friction – the mental tax of confusion and anxiety.

The Brenda-to-Cesar Hand-Off

I was reminded of this just the other night. My son and his family were over for our usual Monday night dinner. That’s eight people total. I usually cook, but we decided to have Jersey Mike’s delivered – which is normally a solid choice with this crew.

The process was indeed frictionless. I ordered eight sandwiches on the app, carefully identifying each one by the eater’s name so the Jersey Mike’s staff could mark them accordingly. Including the Ticketmaster-style fees, the bill came to about $100, which I paid with ApplePay. Seconds later, I got a text message from DoorDash providing a link to the order tracker.

Our dinner was on its way. Or so we thought.

A few minutes later, the tracker told me that “Brenda” was on her way to the store to pick up our food. At this point, the order was still more or less on schedule. Then, according to the tracker, Brenda arrived at the store and was waiting for my order. A couple of minutes later when I checked, Brenda had vanished. As far as the tracker was concerned, she no longer existed.

In her place, “Cesar” was on his way to the store to pick up my food, but he was about a mile and a half out. My assumption is that Brenda got to the store, the order wasn’t ready, and so she had to bail to make her next order, with the DoorDash system handing off responsibility to Cesar.

The Visibility Gap

I’m sure the technology worked exactly as designed. I had the option to text Cesar, which I did. Not surprisingly, he did not respond. So I called Jersey Mike’s to see what was going on.

Speaking with a very polite gentleman, I learned a couple of interesting things from this call. First, the store had no visibility into the delivery system. In fact, I knew more about my order’s fate than he did. He didn’t know I had ordered through the Jersey Mike’s app nor did he know DoorDash was picking up the order. He only knew that some delivery service was picking it up.

“Your order is ready to go, so it’s all up to DoorDash now,” the Jersey Mike’s employee told me.

That led to an obvious question. My son and I had both ordered Hot Italians (because why wouldn’t we), so I asked whether my hot sandwiches would actually arrive hot. The employee made a specific promise: “If DoorDash doesn’t show up in the next couple of minutes, I will personally remake those hot sandwiches.”

When Efficiency Breeds Failure

Well, Cesar didn’t show up within a couple of minutes and I’m pretty sure that employee did not remake our hot sandwiches. They were cold and gross upon arrival. And as if to add insult to injury, the sandwich maker apparently decided it was too much trouble to write each person’s name on their sandwich.

This may not have seemed like a big deal to the sandwich maker, but to eight hungry people who were eating 45 minutes later than expected, it was a very big deal. Yes, even the humans in the loop failed me.

I’m sure the APIs were firing on all cylinders, and the process did precisely what the engineers intended. Yet, I ended up confused (What the hell happened to Brenda?) and frustrated (Why was my cold hot sandwich 45 minutes later?). Was this a Jersey Mike’s issue or a DoorDash issue? I’ll never know for sure. But I do know that I’m a Jersey Mike’s customer, not a DoorDash customer, which means I will use my wallet to hold Jersey Mike’s responsible.

The Accountability Lesson for Credit Unions

Therein lies the biggest lesson for credit unions and the fintechs that serve them. If something goes south, the member doesn’t care if there’s some behind-the-scenes tech provider at fault. You chose that tech provider, so you need to shoulder the responsibility.

Functional friction is still an issue that you must address, but it’s only one side of that friction coin. If you can eliminate member confusion and member frustration, you’ve won. Period. No member will switch to a megabank because they have a streamlined billpay system that makes no sense or a cutting-edge voicebot that refuses to let you speak with a live agent.

It’s not about how many steps you can eliminate. In the end, it’s about how you make your members feel—just like it has been since Moses was a boy. When you outsource the process, you aren’t outsourcing the accountability. If the “hot” experience you promised arrives cold, the slickest API in the world won’t save your brand.

Stay frictionless, my friends.

Defining a New Resource: Credit Union AI News

Church-Adams discusses the genesis of his new platform, explaining that the pace of AI development is so extreme that traditional news cycles can't keep up. With major updates from entities like OpenAI, Google, and Anthropic happening weekly—if not daily—credit union leaders need a "filter" to understand what these changes mean specifically for their members and their mission. The platform serves as this dedicated portal, offering everything from short, commute-ready audio snippets to deep-dive technical analysis.

AI Across the Entire Organization

A central theme of the conversation is that AI is no longer a "siloed" technology for the IT department. Church-Adams argues that every leader, from HR to Marketing to the Board of Directors, now essentially acts as their own Chief Technology Officer.

• Marketing Revolution: AI allows small teams to create high-quality content and personalized member communications at a speed previously reserved for big-budget banks.

• Lending Efficiency: By integrating AI into backend automation, lending teams can drastically increase approval rates and processing speeds.

• The Executive "Thought Partner": One of the most futuristic concepts discussed is using AI as a strategic collaborator. Church-Adams envisions a "Credit Union AI Employee Number One"—a persona that sits in virtual meetings, identifies risks, suggests process improvements, and builds on the human team's experience.

The Great Equalizer for Small Credit Unions

For smaller institutions, Church-Adams highlights AI as a massive competitive advantage. He points out that a small credit union with limited staff can "gain 10 to 15 new employees" worth of productivity simply by adopting AI tools. Instead of being intimidated by the technical barrier, small teams are encouraged to stand up dedicated "AI teams" of even just a few people to focus on organization-wide implementation and road-mapping.

Orchestration and Screenless Banking

As the industry matures, the focus shifts toward the "orchestration layer." Larger credit unions are encouraged to look at how different AI tools communicate with existing cores and payment processors. Church-Adams also offers a provocative look into the future of agentic AI. He predicts that within the next 15 months, we may see a shift toward screenless banking, where members interact with their accounts through voice-driven AI partners in their earpieces, asking for balances or making payments without ever touching a phone or web browser.

A Prediction Rooted in Mission

The episode concludes with a look at the cultural impact of AI. While big banks may use automation primarily to cut costs and serve shareholders, credit unions are uniquely positioned to use AI to further their mission of "people helping people." Church-Adams believes that if credit union leaders embrace this technology wholeheartedly, they will gain a much larger seat at the financial table, leveraging AI to empower their members in a future economy centered on "compute."