Monetary establishments are implementing AI at scale, however logistics needs to be the main target earlier than diving headfirst into rising know-how.
Mac Thompson, chief government of software program supplier White Clay, tells FinAi Information the eight steps he shares with monetary establishment purchasers when approaching AI on this episode of “The Buzz.”
It can also be important to outline AI in phrases that are relevant to your establishment, he says. “Write a one-page definition of what AI means to your monetary establishment, financial institution or credit score union.”
Take heed to “The Buzz” as Thompson explains how FIs can get their establishments prepared for AI.
Register right here for early-bird pricing for the inaugural FinAi Banking Summit 2026, happening March 2-3 in Denver. View the total occasion agenda right here.
The next is a transcript generated by AI know-how that has been flippantly edited however nonetheless accommodates errors.
Whitney McDonald 08:11:48
Matt, hiya and welcome to The Buzz a fin AI information podcast. My title is Whitney McDonald, and I’m the editor of fin AI information. Fin AI information has rebranded for financial institution automation information, marking the subsequent step in our mission to steer the dialog on innovation and Monetary Providers Know-how. Becoming a member of me right this moment, November 25 2025 is Mac Thompson, CEO and founding father of white clay, Mac is right here to debate what monetary establishments should contemplate when implementing rising applied sciences from knowledge technique, fundamental enterprise targets and expertise. Thanks for becoming a member of us. Mac.
Mac Thompson 08:12:19
Superior. Thanks, Whitney, hello. I’m Mac Thompson. I’m CEO and founding father of white clay. We began about 20 years in the past. My associate and I left financial institution of Financial institution of America and our final jobs on the banks earlier than we left. And for about 10 years, we have been a customized software program consulting firm, and we pivoted about 9 years in the past to a extra SaaS mannequin. Took us a pair years to try this, however we’ve been in enterprise. Our purchasers vary from about three 50 million in dimension to 200 billion, and we assist our purchasers construct deeper, extra worthwhile relationships, and one of many methods we do that’s embedding loads of intelligence in regards to the purchasers, using very massive knowledge units from transaction knowledge and account kinds of all types. So very excited to have the dialog. Nice.
Whitney McDonald 08:13:06
Effectively, we’ll get into all of that. Let’s sort of take a step again first. Let’s begin with the state of AI adoption. We’re actually at a spot now the place it’s not a lot if monetary establishments are going to be implementing AI, however reasonably when, clearly it comes all the way down to dimension, capital, sources, priorities. However the place does AI adoption actually stand right this moment?
Speaker 1 08:13:32
Effectively, I believe most likely one of many challenges in answering that’s what? As a result of loads of it is a definitional factor, as a result of AI has been in banking for a very long time, there’s about 20 totally different applied sciences which are sort of AI Synthetic intelligence associated applied sciences, and a few of them I used, we have been utilizing again once I was on the Financial institution of America a very long time in the past. I believe loads of AI now could be extra massive language fashions, generative AI, and that’s how loads of people are defining it. So I believe adoption of some sort is fairly excessive. It might be so simple as somebody on a private degree, signing up for it when it comes to generative or massive language mannequin sort of utilization. However many of the fraud fashions, most and loads of the customer support fashions, chat bots, significantly, and issues of that nature, being utilizing some model of AI for fairly some time, a fraud significantly. And so whereas most banks are utilizing that and it’s extra mature, loads of the smaller ones are moving into it, I believe the large nationals are a lot additional alongside in constructing their very own inner, massive language fashions, educated by themselves, constructed internally, using their very massive, complete, statistically related knowledge units. And so there’s a big variation in that functionality, however the nationals are positively main the way in which when it comes to pure functionality.
Whitney McDonald 08:14:57
Now with regards to questions that your purchasers are asking about implementation, and possibly we are able to sort of lean extra towards the rising AI know-how, what are they asking of you? What are sort of these questions that come throughout your desk that you just sort of see just a little bit time and again
Speaker 1 08:15:15
once more? So I used to have a, I was a CFO once I was on the banks. Is one in every of my jobs. And I converted the, , the darkish income facet, which is much more enjoyable, the darkish facet, sure. So the, one of many questions I ask is, what’s going to be the ROI on this, the return on funding? And I believe it’s a difficult query, particularly the rising AI applied sciences. I imply, the examine from MIT, it got here out in July, mainly that 95% of initiatives don’t generate any discernible monetary profit. They might be advantages, but it surely’s not essentially monetary. These 5% that do them have fairly outsized advantages from it. It’s one of many excessive ranges from that. And I believe once I reply the query about, How do you establish ROI, I stated, I don’t assume you need to be anxious about ROI in the meanwhile. It’s just like the web within the early 90s. Mid 90s, it’s going to mature, it’s going to have a lot better use instances and return on funding instances, however as a company, you’re going to have to consider what it means to be aI empowered, AI powered as an entity, and that’s a journey that’s not simply technical, that’s a Cultural one, and simply how you consider your self, a paradigm virtually. So the ROI query comes up quite a bit as a result of they’re like, Effectively, ought to I am going make investments loads of this? And one of many different issues, for those who’re a really small financial institution, going out and hiring three or 4 AI scientists might be not going to be your greatest return on funding. You understand, you’ve bought 120 folks in your. Firm, you’ve bought extra folks in your AI division than you do in your IT division. In all probability not going to work out nice, so associate up with some folks could be my advice on that. The second factor that most likely comes up greatest is knowledge. And it’s, is my knowledge prepared? And the reply for most folk is, no, it’s a large number. It’s not it’s bought all types of points, and also you’re gonna must work on that. The opposite factor about knowledge, although, is it’s not an finish state. You must begin engaged on it. You must begin utilizing it. By utilizing it, you’re gonna work out what you’ll want to repair. You aren’t have good knowledge earlier than you begin utilizing AI,
Whitney McDonald 08:17:29
yeah, I believe that these are two issues that we’ve positively lined on our facet as nicely, that ROI that needs to be a tough mindset shift, particularly coming from a CFO background, that possibly the ROI doesn’t should be the highest precedence at this actual second. Now, let’s sort of speak via this eight step course of that you’ve, that you just share with purchasers. You could have these, these eight steps that you just share when approaching AI and implementing AI, that needs to be high of thoughts. Are you able to speak us via these?
Speaker 1 08:18:01
Yeah, I’ll form of stroll most likely with you all eight steps. However that actually begins with, what do you attempt to do enterprise clever? So loads of technical purpose why the ROI on loads of applied sciences, together with AI, don’t work, is that the know-how funding wasn’t grounded in a enterprise one thing you have been making an attempt to do. And so, , I believe the MIT article really got here again to the primary problem loads of people are having is integrating these new AI applied sciences into their workflows and the work processes and all that. So the very first thing is work out what you wish to do enterprise clever. After which second a part of that’s decide if there’s any of these belongings you wish to do the place AI could be very useful to you. And also you sort of simply begin with these fundamental enterprise questions, as a result of if there’s probably not something that AI will help you with, and what you wish to do enterprise clever, you bought to consider what you’re doing. In all probability the subsequent two items we simply talked in regards to the knowledge piece. Begin working in your knowledge governance. Begin engaged on a knowledge technique. Begin down that knowledge path. It’s going to be a path. Don’t attempt to bowl the ocean. Don’t exit and rent 12 distributors to work in your knowledge. Begins extra slowly however intentionally, engaged on evolving your your knowledge functionality. However with a knowledge functionality additionally involves folks, is that you just’re going to must you’ve bought massive groups which have labored with you, that like to work, maintain your clients and all of this stuff, it’s important to provide you with a approach to assist develop that expertise. In order you’re creating technique in parallel to that, you’ve bought to develop your group’s human capital functionality to have the ability to begin fascinated by these applied sciences. Not that they must be consultants, however they’ve consciousness and so they can what they should do. You understand, most likely the I’ll really cease, I’ll cease one. There’s one factor I most likely do to begin on all this, although, write a one web page definition of what AI means to your monetary establishment, financial institution or credit score union. So while you’re speaking about AI, are you speaking about generative AI? Are you speaking about massive language, no matter that’s. Simply to search out the phrases, as a result of I’ve been in rooms with 20 folks in there, there’s 5 totally different definitions of AI getting used, and so they don’t know what it’s. In order that that frequent language round what that is, it offers you a foundation to begin engaged on training. However the first is that while you’re utilizing phrases, that everybody is aware of what these phrases imply. And when you’ve got a vendor or somebody coming in, it’s additionally useful, as a result of you may outline the identical phrases. So after they inform you one thing, you could assume they’re saying X after they’re actually saying y. So it’s most likely one of many first issues. Don’t overthink goal, like the place you’re going to be in three years on this? As a result of we don’t know, there’s lots of people arising with AI strategic plans for 5 years, and I don’t know the way on the earth they’re ever as a result of for those who had talked gone again three years, what would we’ve been speaking about, proper? It wouldn’t have been this. So don’t overthink that. Don’t overthink long run tech methods. Except I’m not speaking in regards to the large nationals. I’m not speaking about even a few of the Tremendous Regionals which are making very massive investments, speaking about many of the banks on the market. And doubtless one of many extra necessary items round all of that is the way you begin fascinated by governance, round your knowledge, round fashions you could use this to assist empower selections with does it have any regulatory affect? Are you creating unintentional bias and issues that you just’re doing? And , all these sound sort of difficult, and they’re, nicely, what helps is don’t attempt to clear up every little thing initially and simply begin the journey, as a result of it’s going to be a journey we’re going to be on for some time, and it’s going to take a bunch of various turns. And. It’s all proper, however simply begin. I might say, begin the journey might be the very first thing. I might say,
Whitney McDonald 08:21:57
Yeah, I like what you talked about there about, , you don’t essentially must have that three to 5 yr technique in black and white. Simply begin. And I additionally like what you talked about too, about, , defining what you’re actually making an attempt to unravel for? Create that one web page plan to your establishment particularly. Don’t simply put money into AI for the sake of claiming that you just’re doing it. We’ve seen that, , backfire just a little bit too. However ensuring that you’ve a definition, what are you making an attempt to implement? What are you fixing for? Is it, , not simply utilizing AI as a broader time period, however would you like an agent? Would you like a chat bot? Would you like X, Y or Z? And I believe that having a very simplified, a simplified doc that claims precisely what you’re fixing for is a good place to begin. Do you
Speaker 1 08:22:47
as a result of one of many issues I’ve seen loads of boards are simply we’ve to be an AI. They do not know what which means, however they’re demanding that their financial institution, no matter or credit score union, no matter establishment, be concerned in AI, regardless that they don’t know what which means.
Whitney McDonald 08:23:01
Now looking forward to 2026, we’re seeing extra actual functions. We’re seeing extra effectivity beneficial properties, we’re seeing extra guide processes being changed. What are you looking forward to, for 2026 what are a few of these tangible use instances of AI that you just assume are gonna pop up? What are you enthusiastic about? What are you listening to from, from white clay purchasers?
Speaker 1 08:23:27
Among the ones which are extra tangible are the operational automations of workflows the place we’re pushing paper round, proper? I imply, it sounds humorous, however we banks, we push loads of paper out. Even the place we’ve automated programs, there nonetheless appears to be loads of paper going round. So I believe that this isn’t actually massive language fashions doing this. That is extra textual content paper to textual content to after which the way you embed all of it extra workflow oriented. Tons, numerous people are doing that on a sensible degree, and so they can get some efficiencies, as a result of they’re primarily digitizing processes. One of many issues I believe is a problem is that they’re digitizing the legacy processes, not fascinated by, if I had this know-how, how would I, how would I not even use this course of? I might simply do one thing utterly totally different. And that is banking, and we’ve been doing this for some time. And once we mainly automate cow paths, , the place cows stroll from one vacation spot to the opposite, they construct these paths. And loads of roads are literally constructed on these outdated legacy wilderness paths that animals, Buffalo and whatnot, would create. And loads of what we’re constructing is automating these, digitizing these paths. And I believe the actually massive step this goes again to your corporation. What are you making an attempt to do? In case you actually considered do I even have to do half the stuff that I do is the place there’s large alternative and effectivity and affect, as a result of we, proper now are doing loads of digitizing of legacy issues. So we’re seeing that that’s on the extra operational, making an attempt to get some efficiencies proper now. The opposite factor that’s out there may be this motion from and this has been gone up just a little bit, however we bumped into this headlong you initially take into consideration a spectrum the place you go from affords to insights to suggestions to options. Plenty of people are utilizing AI and different applied sciences to create all these affords, subsequent product, logical product and issues, product pushing on a approach the opposite factor we bought into is we’re producing insights. And right here’s all these insights that we are able to now generate, and our capacity to generate insights has massively outpaced the power of the folks within the area, they’re interacting with purchasers, to do something with these insights. We did this ourselves. We’re responsible of this. We created, , we had couple 100 insights per shopper, and that, , in a department could have 2000 purchasers. And so what do you do with all so what I’m seeing is arising is, how do you’re taking all of this, simplify it, and switch it into one thing that may be actually constructive for each the shopper and the financial institution. And that’s, I believe, the subsequent evolution of all this, and that’s moving into agentic, is one phrase. However agentic, in fact, means 25 various things to all types of various folks, proper? I imply, they Gartner’s symposium down in Orlando. You understand, agentic was, , agentic AI and a Genty internet was buzzwords which are on the market, however what it means actually will depend on the issue the individual. However that idea that we’re going to have the ability to take all of this intelligence and put it in movement, put it into motion, is, I believe, the subsequent evolution, and I see some folks making an attempt to get into that. There’s distributors making an attempt to do it. There’s issues making an attempt. Union is making an attempt to do it, however I believe that agentic evolution is coming, and it most likely can be speaking extra about agentic in 26 than we have been speaking about generative, as a result of it’s mainly, how do you get a private assistant? That’s this agentic agent doing issues for you rather than however as soon as once more, we’re most likely again to automating Cal go, as a result of we’re making an attempt to get them to automate issues that we at the moment do. I believe the subsequent technology, which most likely a 27 factor, is once we’re beginning to get into the agentic internet, the place the net is extra like a useful resource we work together with that we’ve folks go do issues with. What occurs to the net was a extra proactive agent for you, as an alternative of a useful resource, it extra empowers the way you have been considering. It’s only a very totally different approach of interacting with these large knowledge units which are on the market, sort of scary in some methods. I imply, folks run into that, however I believe, that’s sort of long run the place we’re going. However on the whole, it’s the way you begin taking all these capabilities that we’re constructing, that we’ve created and starting to combine them in a approach that makes folks’s lives really less complicated. As a result of proper now, we’re really making life quite a bit tougher for lots of our bankers. We’re making an attempt to assist them, however we’re simply give overloading them with a lot stuff they will’t use it. And the way do you the way do you get that worth out? I believe will rely upon us simplifying it, making it extra actionable, extra easy, and I believe that’s the place we’re going.
Whitney McDonald 08:28:15
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