520. Robert M. Reed | Banks That Treat Compliance as a Checklist Are Creating Bigger Operational Risks

Email: contact@bolog.io

In this episode, host Bidemi Ologunde speaks with Robert M. Reed, COO of the International Bank of Chicago and founder of Reed Advancements, about the intersection of AI, banking compliance, operational resilience, and trust.

Why do compliance programs still fail even as technology improves? Where should banks automate, and where should human judgment remain essential? What makes an AI-driven compliance system truly audit-ready? Robert draws on decades of experience across financial services, crisis response, AML, operations, and regulatory compliance to explain why many compliance failures begin as operational failures, how institutions can use AI without creating new risks, and what leaders should do now to strengthen controls before weaknesses become regulatory or reputational problems.

Listeners can also download the companion AI, Compliance & Operational Resilience Worksheet from the episode resources/show notes to assess their own processes, controls, AI readiness, and next steps.

Transcript

SPEAKER_01 0:00

Listeners of this episode can download the companion AI compliance and operational resilience worksheets from the episode show notes in order to assess their own processes, controls, AI readiness, and next steps. Thank you. So thanks for joining me once again on another episode of the Bait Picture Podcast. I have a special guest from up in Chicago, Illinois. Over to you, sir.

SPEAKER_00 0:40

Hi, Robert Reid. Very good to meet you. Happy to be here. Thank you, sir. Thank you, sir.

SPEAKER_01 0:45

So to jump right into it, you started on the floor of the Chicago Stock Exchange. Um what did that environment teach you about how people actually make decisions under pressure?

SPEAKER_00 0:59

You know, I think it it taught me that not everybody can handle that type of pressure. I think that's what it taught me more than anything. I think you can go to school, you can understand the, you know, the background of finances, you can understand the background of stocks and and everything else. But when you're on that floor, when you're when you're when it's live in your face, um, it's not something that you can really mimic anywhere else in the financial service industry. I mean, obviously a lot has changed since then, right? So, you know, we're talking, you know, roughly 1998, 1999. We're talking, you know, when we were still trading in fractions instead of decimals like we trade today. Um, but you know, it it's it's something that uh not everybody is cut out for and maybe doesn't want to be a part of either. I mean, there would be people that would come onto the floor their first day and at lunchtime they would say, I'm not coming back, I don't like it, it's not for me. And and again, that's fine, right? I I think that that there's there's something inside of you to be secure enough to say that this isn't for me. That's that's a good thing.

SPEAKER_01 2:04

So, what habits from that era still shows up in your walks today?

SPEAKER_00 2:09

Well, two things. One, I still crumple up paper and throw it on the ground sometimes when I'm not paying attention. Uh drives my wife crazy because you know I leave paper all over the place and I don't necessarily remember doing it. Uh, that's number one. But I think I think the the second thing it really does is is staying calm under pressure. Um when those uh ticks are happening against you uh and they're in your face and you're losing money with every second, literally. Um keeping a calm head and being able to realize what's going on, what you need to do uh to get yourself out of it is something that I think I still maintain to this day when I when I need to and want to.

SPEAKER_01 2:49

So to touch on some parts of your early experience, um to set that question up, I was gonna say we see every now and then institutions losing control of their narrative, of their story. Maybe it's a scandal, maybe it's something adjacent to a regular government regulation and so on. And you specifically, you've lived through the bare sterns collapse and some crisis operations at JP Morgan. So, what did those moments teach you about the first signs that an institution is losing control of their own narrative?

SPEAKER_00 3:27

Well, I think the first sign is really uh something that we won't see, right? It's not something that's gonna be in the public. Uh, I would imagine, um, you know, having worked for a large uh financial institution like JP Morgan, that a Bear Stearns, a Lehman Brothers, all these financial institutions that we saw just collapse, you know, uh late uh, you know, or early 2000s, I should say, really, um, you know, really uh should have known about these things beforehand. And they should have seen those things coming um well in advance of it getting as bad as it is. Um, I think the movies that are out there like Too Big to Fail and you know Wall Street and you know, all those other things that kind of glorify some of the things that went on. I don't know that that's you know realistically how I see it when I've been into large financial institutions that were having you know problems, but nothing of that magnitude, right? I mean, you you can still have a red metric, so to speak, or a red KRI, um, and then not take down the entire financial institution, right? Like there's there's hopefully things that are being caught well in advance uh prior to doing that. So I think it's it's uh going through the exercise of understanding your key risk indicators, your key performance indicators, whatever you want to talk about. But it's not the exercise of just going through them for the sake of going through them. It's making sure that whoever is monitoring them truly understands the impact of those going off the rails and uh making people aware of it uh as quickly as possible to do something about it. Because, you know, going back to my stock exchange example, um, there were guys that were just having bad days trading, and they would call out for help from other guys in their pit and and they take over so that you know they they knew they just weren't in the right space for it for whatever reason, and you take over and you get it back under control, and then you take a breath and you you hop back on, so to speak, and you keep going. So um, you know, I think there's a lot to be said for again self-awareness in this environment, uh, when you're especially when you're talking about financial, you know, uh industry or market and and technology. So understanding all those things I think is just key in this in this space. Thanks, thanks.

SPEAKER_01 5:43

So for people meeting read advancements for the first time, um, what's the problem your firm is built to solve that traditional consultants or software vendors usually miss?

SPEAKER_00 5:57

I think, you know, when you're talking about traditional consulting firms or vendors, um, they all have a lot of individuals in that firm that have experience in in some specific niche, you know, area, right? You've got former regulators, you have, you know, former operations people, you have former, you know, X, Y, and Z. I think what we do uniquely um is that uh, you know, myself included, I I have years of experience from every angle of the financial service industry from front to back office, right? So I've sat in the front office selling, I've sat in the back office operations, and I've sat in that kind of middle world where you're working with everybody to do everything. Um, I think the other thing that we do well is that uh we we don't sugarcoat it to keep keep the job. I think I've seen in my career, and again, you know, it's there's there's good and bad in everything in the world, but I've seen places don't necessarily uh uh put the the punch in the reports that they need to uh to show really what's happening in the in the say the the firm or the the the financial industry that they're working in. And then it allows kind of those things to go back off the rails because they're not being again monitored like they should have been to begin with. I think the fact that I'm willing to necessarily lose a sale or repeat customer if I have to to make sure that my integrity and what we identify is fully known and fully aware versus what the board or maybe a senior leader would want to hear, uh, to say, provide me with a repeat, you know, request. I think that's where the the difference in my firm is. I think that's where we sit. I there's there's ways to tell the truth tactfully, uh respectfully, um, but you have to you have to be fully uh committed to providing that full scope or that full insight into what you found. Otherwise you you're not doing the doing the client justice either.

SPEAKER_01 7:53

Wow, well I like how you described your willingness to basically operate at a disadvantage to yourself if it means keeping your integrity. And just reading the news or listening to the news nowadays, we see a lot of people skipping that part saying, Well, I would rather make my ego intact or keep my bottom line intact and skip on integrity and cut corners and so on, which I don't know, comes down to that operational integrity background you have that says the sky might be falling, but we still have to do the right thing the right way, the right time. So your public profile spans across so many diverse, you know, um areas securities, anti-money laundering, transaction monitoring, know your customer sanctions, and most recently AI analytics. At what point did you realize that your edge was not just technical knowledge, but being able to connect all these different worlds?

SPEAKER_00 9:00

It's kind of how I set up my entire career, if I'm being honest. I I had uh I had an amazing sixth grade teacher who held a mirror in front of me. Um, I still talk to her to this day. Um, she held the mirror in front of me one time, and uh it uh turned around and made me love or have a love for the markets. That's how I got involved into the you know, Chicago stock exchange and that world. And from the beginning, we're talking, you know, 12-year-old me sitting there, um, you know, uh having that love uh of the market and having that love and understanding of what it was, uh, going through those components and and stepping through the various stages of my career to make sure that I understood the full scope of the industry from from again, front to back office, right? I wanted to understand it from an exchange level. I wanted to understand it from a from a brokerage house level, from a bank level, from all these different levels and angles, so that as I moved into the you know, part of my career now where I do board advisory and uh you know fintech advisory, um, that they know that I've been through the ringer, right? Like there's something to be said about uh, you know, quote unquote being in the trenches with somebody, um, like you say would in a MBA program or you know, in a job where you know, like the whole industry around you is collapsing and you're still sitting there, right? Um there's something to be said about that, keeping your cool, having survived, and then and then ultimately being able to advise on those topics at the same time. And I I, you know, again, that's that's where my love of this uh kind of tech comes into place and where I want to go with everything that I do and why I've started to look to build my own AI and my own uh you know uh products, if you will, or software packages so that I can help not just the regulatory side of the the financial institution space, but also it its operational side. I mean, you know, I I think that it's noble that that a lot of us out here in this industry want to, you know, build the better mousetrap and and uh you know AI find the next terrorist and AI do this and AI do that. But the reality of the situation is, you know, it's it's a guess at best. And you're utilizing data to guess at this. Instead of utilizing, you know, AI to try and find the needle in the stack of needles, use the AI to help build out your operations and provide scalability to your organization so that you can have the smart people trying to find that needle in that stack of needles. And that's that's where again I think I come in with the the read advancement organization, because I I'm not here to tell you you need to buy a software package. I'm not here to tell you that uh, you know, this this uh operationally will be better for you or not. I'm I'm there to first and foremost understand what your operation is, where your pain points are, where your time delays are, where all those things exist, and then provide insight as to what tools might help you, regardless of it being a tool that I've been a part of building or somebody else's. I mean, I've been fortunate enough, as you've laid out uh a few moments ago, to be a part of sanctions and and transaction monitoring and you know consulting and everything else. And because of that, I've I've had a lot of access to various, you know, software packages and systems and and everything else, from you know, actimize to Thompson Reuters to Lexus Nexus, all these big names and financial technology, I've gotten uh to use uh a good portion of them uh in the industry. And I think, you know, having that background and and living through those those wars, so to speak, and and then coming out on the other side uh having survived, um that again just leads credence to what you're trying to set up from an operational standpoint in that regulatory space.

SPEAKER_01 13:20

Nice, nice. Thank you for sharing that. And you mentioned something a moment ago, financial operations, fintech advisory. So read advancement is fully embedded within fintech, financial operations, fintech advisory. Which of those areas is most misunderstood by both boards and founders in 2026?

SPEAKER_00 13:46

I think what's most misunderstood is is how you really should use the AI to begin with, right? I mean, I think a lot of people have become very familiar and comfortable in the space with Chat GPT type, you know, fintech, uh writing reports and things of that nature, right? I think where where they're not comfortable at this point in time or where where boards need to get more comfortable is what it can do from an operational standpoint for you as well. Right? You wanna you wanna flip the script. The the old adage back in in anti-money laundering was you spend 80 time, uh 80% of the time collecting data to do 20% time analysis. I want to flip that, right? I want to flip that with what we build through our EDD profiler program or through our our Ragmodel bots to do analysis on policy and procedure where you're giving this this AI, this tool, the information, it's providing you with input just like any other person or or or product would. But at the end of the day, you're the one that's still gonna know the risk the best. You're theoretically gonna glitch the least, right? Compared to you know, a chat GPT or something else. So, because of that, I want to flip that script and make sure that whatever tool you're using, as I say, whether it's one that you know I've I've been a part of building or not, it it's helping you give the people to do the the the tough or the thinking, the ability to have more time to do the thinking and less time doing the monotony of pulling data, doing calculations, things like that.

SPEAKER_01 15:16

So I want to quote you here. Um, this is something you've said a few times. Quote, I'm in compliance with an operational mindset. Where did that mindset come from?

SPEAKER_00 15:28

It was forced on me. I'll be honest with you. Um you know, when you when you're on the floor of the Chicago Stock Exchange or any exchange uh that I've ever witnessed, um, you know, it's they're they're called SROs or self-regulatory organizations. So you're passing, in essence, exchange tests and and training to in order to be able to be a trader to begin with. Um you can't be a part of financial technology industry market without being under the scrutiny of some regulatory body here in the United States. I mean, it just depends on what type of entity you're in and then what you know three or four-letter acronym is going to guide you over that, right? So when you're learning about all the different backgrounds of the of the industry, whether you're talking about being in the mortgage-backed security group or you're talking about you talk about being in the anti-money laundering uh kind of finance terrorism group, um, there are rules and regs that that address to some degree, uh, in a very grave manner most of the time, what what you can and can't do, and then what needs to come out of that from a monitoring perspective. And I think that um, you know, when you when you go through that, you have to to understand what the requirements are, and then you've got to make that operationally work for the organization, right? Uh organizations don't provide you with infinite resources. Uh, we know this, right? We can we can have an argument anytime you want on capitalism, but at the end of the day, this is the way the system works right now. Um you know, uh, you have to justify your your, you know, say wants for new technology or or new spends or new staff or you know, whatever that is. And you can't possibly provide a good enough argument if you don't understand the operations of the situation and the regulatory requirements of that operation. And I've built the whole mindset around this with Reed Advancements that uh you know, you have to understand the operations first, what regulatory agencies you fall within and under in that, what are your control points, what are your indicators that those control points aren't working, and then ultimately come up with a program that then can be scaled as the business grows, because that's what everybody worries about. It's it's the scalability. Anyone can do a staffing assessment and figure out where they need to be at that point in time, but projecting what that scalability needs to look like when it's you know 20 more clients or 50 more clients or you know, whatever that number is that increases, that's the that's the key indicator, the key piece that makes this different uh in what I do.

SPEAKER_01 18:09

Um, in your anti-money laundering work, you've pointed to recurring failures around KYC that know your customer, as well as transaction monitoring. Why do these same weaknesses keep resurfacing even after fines and bad headlines and years of modernization, especially most recently, AI modernization?

SPEAKER_00 18:32

I think there's a couple of reasons. And I was actually discussing this with somebody else earlier today. In order to provide a transparent financial market, the thing that the regulators do the best is they project and and lay out all the rules and regulations and thresholds in which we do things.

unknown 18:49

Right?

SPEAKER_00 18:50

So, for example, currency transaction reports, everybody knows the threshold, everybody knows the limit. It doesn't take Chat GPT for you to Google that, understand what those are, and understand what the laws and requirements are, and then to skirt around those. The same thing with transaction monitoring. I mean, you know, anybody that really wants to get around any of this stuff could spend a day or two reading white papers from you know consulting firms and experts and everything else about how you know they try to detect money laundering in a better way, and then just do something that would get around that to begin with. I I'm I'm I I hate to say it's that simple, but to some degree it really is that simple. Um and again, a lot of times, depending upon what you're talking about, the money's out the door from the financial institution before anybody is even aware that the transaction occurred, right? Anti-money laundering works in the rears, meaning I'm not looking at that transaction that occurred today until tomorrow when my my system generates the alert that's going to have somebody stop and look at that. I may have the money out of the bank before that even, you know, that even gets a look at. And again, I think we've made it very much aware, or we've made everybody very much aware in the industry of how this stuff works. And you know, the bad guys are always looking for ways to get around the better mousetrap that we build. I think the other aspect of this too is the rules in a lot of cases are are gray, right? And what I mean by that is a lot of things in money laundering and and uh CFT start off with on a risk-based approach. Well, my idea risk, your idea risk, that regulator's idea risk, that's a very open way to perceive something. And what if we disagree on what that risk is? How are you capturing those things? So, you know, I kind of bring it all back and say, you know, that the fines, um, although try to deter the behavior, but the behavior of the bad guy, quote unquote, uh, they're always looking for a way to get around that. So every time we announce a new product, every time we announce a new, you know, uh uh scenario or algorithm that's gonna help find this, they just find a way to skirt around it. So, you know, in fact, uh, you know, I don't I don't know how much you're aware of this world, but there are there are industries uh to launder money where they don't use the financial system at all. People in various locations keep ledger books on paper, right? And then hand out cash to people, right? Like and they and they yeah. So, you know, it's again, it's not uh unfortunately, it's not as clear-cut as I think we like to think it is in the world and the in the industry of of say banking and monitoring transactions, where you can just point at it and say these the this is true, so therefore the rest of it's true, right? I mean, we we also tend to live in a world where we believe everything is a zero-sum game, right? So if I'm building a better transaction monitoring system, I also cannot be focusing on building a better sanction screening program or or whatever it is, right? Everything's one or the other. It's it's it's this or that. And that's just not the case. And I think that that's where, you know, again, having the the background and experience in the industry and understanding that all these things can be occurring at one time and breaking it apart and taking the time to do it right is is more helpful than than anything else you can do in this in the world right now with this stuff. I mean, uh what is it now? We we anticipate or think we catch thirty percent of the money laundered through the financial system. I mean You know, and and again, I'm not knocking on anybody. It you you are trying to predict the future, right? I mean, it's kind of like being a weatherman, but with like this crazy, you know, um dollar stakes at at hand versus you know, just oh, I got rained on, right? So it it's it's a it's a crazy, it's a crazy thing that you're trying to accomplish uh in doing this um to begin with. And again, unfortunately, because of the way the the systems and the industry work, you're doing it on the rears. And I think that's that's part of the challenge. You have you know pretend preventative controls that that stop and deter the behavior, right? That's the fines, that's the jail time, that's the this and that's the that. But the reality is is from a money laundering standpoint, unless the transaction occurs, you don't know that money's been laundered, right? It has to be laundered in order for you to detect it. And by the time you detect it, that money could be long gone and out the door. So, you know, when we go back and look at things like, you know, the perpetrators of 9-11 and and some of those things. I mean, we learned a lot of how this was worked and done, but again, you know, the the value and volume of what would need to occur and the and the amount of people, the sheer volume of people to look at all those types of transactions and everything else is is just staggering when you when you really break it down and think about it. That's why everybody's trying the next find the next best, you know, algorithm. What's the next best thing that's gonna prevent me from you know uh having to have 35 people look at transaction monitoring versus 10 people look at transaction monitoring, uh, because again, you know, you ultimately end up with a lot of noise in these systems, and and there's just no great way around it. You can you can continue to test and tune, uh validate to make sure your data is quality and make sure you know you have all the proper things going through it, but but at the end of the day, you're not gonna catch everything. It's just not feasible in in the industry at this point in time. So you've got to find those operational controls that are going to help you find those things right away.

SPEAKER_01 24:39

So when a bank or a fintech tells you that their compliance program is fine, what's the first workflow or handoff that you look at to see whether that statement is actually true?

SPEAKER_00 24:50

Yeah, I mean, if we're talking about a financial uh service industry like a bank, I'm gonna look at their transaction monitoring every time. And what I'm gonna look at first and foremost is the alerts that were generated by the system in which they didn't file a SAR. So, in other words, the system said, Hey, look at this. There's something going on here. The system does not determine it's suspicious, right? The system just says, Hey, this sits outside the norm of this, you know, corporation or individual's patterns. You need to take a look at this.

SPEAKER_01 25:24

And then so that's a suspicious activity report.

SPEAKER_00 25:28

No, no, that is just an alert from the transaction monitoring system. Okay. So you get this indicator from the system saying, hey, look at this, something's not right. And then you dig into it, and then you determine if it is actually suspicious or not, and then you file the SAR ultimately. Uh I'll give you an example I like to use. You know, if you're sitting in a bank and you've got a pizza uh parlor, and every Monday afternoon they deposit roughly $2,000 in cash. Okay. Every week, $2,000, $2,000. So that is, you know, their pattern, right? And if you go back to their KYC or know your customer and their customer due diligence, meaning how they're going to use the account, what's going to occur in that, what type of activity should you see, you see that, okay, based on what they're saying is it's their operational account, they're bringing in their cash from their receipts, so on and so forth. Okay, $2,000. Now Monday comes along and they deposit $10,000 in there. So of course the system's gonna alert on that, right? The system's gonna say, hey, this is outside the norm. Okay, is that suspicious?

SPEAKER_01 26:37

What if it was Supable weekend?

SPEAKER_00 26:39

Well, you're you're already you're already giving me where I'm going, right? So here's the challenge with this, right? So now you look at that ten thousand dollars and you say, Yeah, that's not right. But then you have to dig into the transactional history. Well, then it turns out they haven't deposited for three weeks. Okay, so then you go in your head and you say, Okay, that's roughly six thousand dollars. So still not ten, but still, you know, okay, but more feasible, less suspicious now. And then you realize, because you're looking at this again in the rears, that it's the Monday after Christmas and New Year's. Well, now all of a sudden ten thousand dollars seem so suspicious anymore. And you don't file that SAR. But where I'd come from then at that point is I would say, okay, that sounds great on paper, and you're probably right, but what did they deposit that same time last year? And then you go back last year and you find out they did roughly 9,500, and you go, okay, look, you know, this is not suspicious at this point, but those are the ones, those those alerts that don't get turned into SARS are the ones where I think you'll find the greatest weaknesses off the off the bat, the quickest. Um I think the challenge too with SARS in particular, if I'm being honest, is people file a lot of defensive SARS now. Meaning they're not sure it's truly suspicious, but it's it's not easily, you know, managed a way enough for you to feel comfortable just not doing anything. So you notify the you notify the the government anyways, right? And that's where you you find out that you know, I I I forget the number, don't quote me, I apologize, but it's you know, something like 350,000 SARS get filed a month from financial institutions in the United States. I mean 350,000. And then the government has to in some way, shape, or form go through all that and figure out what they want to investigate and everything else. I mean, the system again to some degree is not set up in a way to necessarily be um successful from that standpoint and and finding uh, you know, what I'll say, the the the the bigger cases uh when it's tied to little dollar amounts. And I think that's where most of the money gets laundered. It's it's not the guy trying to sneak a million dollars in that's gonna stick out like a sore thumb. It's it's like it's like Ozarks, if you ever watched Ozarks. I mean, uh, you know, Netflix, like, like, like that guy would have got caught in a heartbeat, no doubt about it, right? Like the dollar, the dollar values were just so far out of whack. But if he was doing $2,000 a week and he was doing it at a couple different banks, I don't know that any system in the world would have caught him. Like, like that's where the challenge comes in for the board and the say the BSA email officers in this case, and making sure that their financial technology is tuned into these things to make sure that their customer due diligence really informs them of what that that account activity should really look like. And again, the ones that they don't file SARS on are where you can find those indicators and whether or not they're totally using that that customer due diligence or CDD information and find a lot of gaps. Um, you know, hopefully you don't, right? And then you move on to you know some of the other aspects of it where you did file SARS and you know, should you really file the SAR? Do you are you overfiling, so on and so forth. So you step through a a series of things um, you know, for that. The the place that I also like to start um before I'd even really get into transaction monitoring, though, would really be around their risk assessments and and what do they feel the risk of their financial organization is? And and hopefully that has values and volumes and and all the other indicators in it that we need to make sure that we understand what's happening there so that you know we can properly advise them as what they're doing and what's happening.

SPEAKER_01 30:29

Nice, nice, nice. So, as the COO of International Bank of Chicago, um, how do you translate board level priorities into day-to-day operating discipline without creating um, I guess, a bureaucracy that slows everything down?

SPEAKER_00 30:46

Yeah, I think, you know, I like to use the term slicing, right? I mean, I I think you know, people like to use the term boil the ocean, and that's how it feels like sometimes, right? When you get these mandates coming down from a strategic position. And I think taking it in slices, um, and saying, okay, in order for XYZ to be successful, what do we really need to do? And understanding those components, and then taking those in slices across the, you know, across the program, uh, whatever program that is, right? Whether you're monitoring for OFEC or monitoring for fraud or or anything else, is making sure that each of those components um are at the the peak they can be with what you have and know. Um, and then always constantly looking to improve. I I like to say uh from a former mentor of mine who who said this a lot, I always reserve the right to get smarter. And and it it was so uh so uh simple to some degree, but so thoughtful that as we get better, we're going to learn more to make us better. It's a continuous improvement type situation. So making sure that you're taking the time to effectively challenge one another, uh going through the process of of always trying to build the better mousetrap as cliche as that says, you know, sounds, uh, I think is the best way to go about doing it.

SPEAKER_01 32:09

We all know compliance programs uh pretty much always playing catch up, even as technology keeps getting better. So, in your opinion, why do compliance programs still break, even with technology just advancing every week at this point?

SPEAKER_00 32:26

I think it's it's the lack of use of it. I think in some areas, depending upon what your industry is, it's it's being able to take uh that talk that technology, that AI, and and utilize it for again the operational needs. In my mind, you know, uh AI is there to do the heavy lifting, not do the real thinking. And I think that's where I kind of differ from a lot of people with AI. I uh yes, there are definitely some areas where if we're talking about mass calculations and everything else, sure, give it to the AI, right? But but when you're talking about something gray like compliance, where I go back to the pizza example, um, that's a lot of AI programming to get that that AI bought uh to understand that that $10,000 really isn't suspicious anymore based on everything that we walk through. And you as a board, as the owner of say the risk of an AML program or a fraud program or anything else, you have to be careful or uh careful um not to over uh rely on the AI. Um, and I think because people are so concerned about over-reliance on AI that they tend not to use AI at all, which of course then doesn't allow the technology to really help you in the way it should. And I think that's where a lot of the the falling down, so to speak, as you say, is really occurring. I think I think that's where I think that's where we miss the boat a lot is that um you know you you've got the conspiracy theorists that are waiting for you know Skynet to come out with Terminator next and and everything else, but but but you also have this fear that are the regulators going to be comfortable with it, you know, are are they you know are they gonna be okay with how you're doing you know, X, Y, and Z. And and I would say that, you know, my experience with with regulators has always been communicate, show them what you're doing, show them that AI is not making the decision. AI is helping you provide or providing you with more input to help you make a better decision, right? It's it's doing analysis from a consistency standpoint, um, because it will be consistent, right? Unlike humans. Um but but ultimately, again, you still have that human touch, you have that human eye uh that's sitting on there. Um will a lot of this stuff be done by by bots someday? Probably. I mean, if if if we're being realistic, you know, um you know, over time they'll get better, we'll train them more, uh, you know, uh machine learning, blah, blah, blah, blah, blah. Use all those buzz terms that you want to. Um, so eventually I think, I think it'll occur. Um, but I just don't think we're there yet. I don't think the AI is there yet. We we still you can still see too many biases, you can still see too many uh, let's say, hiccups, uh, so to speak, in the in the thought process with some of the analysis part. So have them do the heavy lift of the calculations and the data polls and the sorting of data and and part parceling and and have them spend the hours doing that or minutes for them versus you, while you do the actual thought process and analysis of what what's going on and determining whether or not something is suspicious.

SPEAKER_01 35:32

So for much younger people like myself who are cons contemplating entering compliance or the governance, risk and compliance industry in general, what part of your own experience would surprise them the most?

SPEAKER_00 35:48

I think how gray it is. You know, when when you're not in this space and you look at, say, laws, right? There's a speed limit, right, when you're driving. It's it's simple. Whether or not the cop pulls you over for doing 55 and a 45 is not relevant. The speed limit is 45. You can be pulled over at 55 at any point in time and get a ticket, right? It's it's a black and white this or that situation. Um, there are food quality standards. I'll use this another example, right? X amount of toxins, x amount of this, x amount of that. Period. End of story. When you start looking into, say, the FFIC manual, or you start looking into fraud monitoring and any of those other uh disciplines, you start to see all of a sudden that that there is no speed limit. The first question is, what do you think the speed limit should be? Why do you think the speed limit's there? And then now you can talk about what the speed limit is, but then ultimately you can have other people come in, challenge you, and say that you thought about this wrong. And and there's no there's no guide rail that says 45 is the limit. It's it's it's kind of all gray. You've got to be comfortable in the gray. And I think that's the biggest piece in compliance that that people I think would be shocked by is there's not there's not a single law that kind of points to how you have to do, say, an AML program. There are what I would call guide rails, but with everything starting off with on a risk-based approach, you know, again, I go back to what I said earlier. My idea of risk, your idea of risk, you know, like like it, it can vary based on on humans. So um, you know, that's that's where I think uh I think it would surprise most individuals talk thinking about getting into this space.

SPEAKER_01 37:40

And you've also talked about integrating AI into legacy systems by basically breaking processes into smaller steps and then testing in parallel. So, where should an institution start if it wants results without creating new control gaps?

SPEAKER_00 37:57

Yeah, I mean, I think you you start off with what the human would do that that can be easily replicated by a bot. So we'll we'll pick on transaction monitoring for a hot second, right? Your policy and procedure at that financial institution says that if you get, say, a velocity style alert, you have to at least look at 90 days of transactional history. You need to say, uh, understand the average transaction size. You need to say, uh, look at all the transactions with this counterparty that alerted. So there's these kind of ideas that the banks and financial institutions have that say, we're gonna start looking here. I mean, that's just time for a human to do. So you take that slice, you take that piece, and you work on automating that first, and then you test it and you run it in parallel. So while I'm still doing the same work I've always done, I'm gonna have the bot run it. Theoretically, the bot's gonna be done quicker, but I'm gonna justify and confirm that what the bot did sorting was was correct. Once you're comfortable that there's a uh a high enough uh we'll say consistency in that being done correctly, then you can go on to step two. What's the next step that would save your people the most time and space? Because again, remember, it's just doing some of the legwork for you at this point, right? It's not making decisions, it's not writing analysis, it's not writing reports, it's not doing any of those things. I think that's the next step. Um is then finding that next step where where the calculations that need to be done. Have it do the calculations, right? So now it can pull the data, it can pull the it can run the calculations, it can do those pieces, and now you've got two parts of the system put together. And you just keep adding on. And I think that's where a lot of financial institutions probably would get uh more comfortable quicker um by allowing those little things to go on versus say a wholesale task of transaction monitoring and being comfortable with it doing what it's doing, because it's something you can easily chunk off and test and get comfortable with, and then move on to the next component.

SPEAKER_01 40:11

So to kind of start landing the plane here, um, it's been a very insightful conversation. I feel like I could do another uh one hour with you easily. Um over the next 12 months, let's be conservative. What is the first uh practical move that a CEO, a COO, or a board member should make if they want a compliance program that is both automation-friendly and resilient under scrutiny?

SPEAKER_00 40:42

I think the first thing you have to do as a CEO um or a board member is sit in with those that actually do the legwork, not your management, not you know, not the guy that reports to you, the the individual that is sitting there doing that task on a regular basis, they're gonna they're gonna have the most ideas on how to make that process better because they're in the thick of it every day. And I think by again taking that slice and understanding those components, and again, not everything's gonna work, right? Like, you know, everything's not gonna be automatable instantaneously, but in some of those areas where you can find those time savings, I think it does a couple of things from a from a board and a CEO or management perspective. One, you know, it shows your team that you're willing to innovate to help them, you know, be more efficient. I think the other thing that it does kind of ancillary or secondary uh as a byproduct of of doing that is that you know your team feels heard and they feel open enough to talk about those things that they think could be made better with this. And I think that that boosts morale. I think that you know excites others around him to say, hey, Rob, you know, Rob was able to talk to the CEO or the board member and and get this done because he you know thought through this. Uh I wonder what I could, you know, figure out with my process. And and I think that's where you can spark innovation in your organization uh without much effort, if I'm being honest.

SPEAKER_01 42:20

Wow, wow. Is there anything else you would like to leave us with or anything we should have mentioned or discussed that we haven't?

SPEAKER_00 42:28

You know, I think I don't I don't care who you are, if you're the CEO, the chairman of the board, or or the you know, entry-level analyst that just got the job, just remember you always have the right to get smarter, right? You always have the right to get better. And if you try to get a little bit better every day with what you do and how you understand it, and uh, you know, micro learning is a big term right now, but you know, it's that's in essence what you know what I'm talking about, that uh overall you'll continue to grow and and you'll you'll you'll create the better mousetrap without really you know knowing it.

SPEAKER_01 43:02

Nice, nice. This has been really interesting, insightful, fun conversation. Thank you so much once again. Yeah, thank you for having me. Like I said, like I said before we started recording, hope I did a good job of convincing you to come back.

SPEAKER_00 43:16

I I would happily come back. I think uh, you know, we we definitely uh could hit on a bunch of different topics on you know the financial service industry, and you know, we could I'm sure we could have a whole episode on Too Big to Fail Alone, right? Like Right, right.

SPEAKER_01 43:31

And we didn't even touch on your work regarding anti-human trafficking initiatives and efforts. So there you go.

SPEAKER_00 43:39

So something, yeah, something near and dear to my heart. Um, just trying to, you know, help help anybody get out of that environment that they can. Um, I've done some work uh with not-for-profits. Uh my wife is uh a counselor for for sexually abused kids, and uh so it's a it's a topic we we keep uh close to heart here and and we try to do everything we can uh to helpfully uh you know break people out of that life.

SPEAKER_01 44:05

Nice, nice. It's definitely something to you know look forward to and you know connect with you for that down the line, maybe sometime before the end of the year and you know just talk about some of these topics. Yeah. Thank you.

SPEAKER_00 44:17

Sounds good, great being you.

SPEAKER_01 44:19

Thank you so much. Text to you later. Bye.