The Capital Midwest Fraud Detection podcast featuring Tod McDonald and Chris McCall from Valid8

Stewart: Welcome to another edition of the podcast. I’m Stewart Foley. I’ll be your host. In the immortal words of Monty Python, “And now for something completely different.” Today, we’re going to talk about fraud and how you catch it using very advanced, high-tech software. We’re joined today by Tod McDonald and Chris McCall from Valid8, spelled with an eight. Gentlemen, thanks for being on. Thanks for taking the time.

Chris: Thanks, Stewart.

Tod: Great to be with you.

Stewart: It’s great to have you both here. We came together by way of a friendship, so I don’t know a whole lot about this topic. But I’m dying to know how you guys got into this business. What was the catalyst? What’s the backstory on Valid8?

Chris: Tod, why don’t you take it?

Tod: Perfect. Well, yeah, our background really came out of a fraud investigation. The idea for what we built Valid8 came out of a Ponzi scheme, in fact, one of the country’s largest Ponzi schemes. It was called the Meridian, Meridian Funds, out of Seattle, Washington, where I call home. In that case, I was working with the bankruptcy trustee. It was a Chapter 11 bankruptcy, which normally go through a restructuring evaluation, and often emerges successfully as a restructured company on the backend. We walked into a series of investment management funds with a real estate then that had filed for bankruptcy protection, expecting there to be some overhead to cut, some profitable versus unprofitable lines of business to evaluate. Normal bankruptcy trustee stuff.

That quickly changed a couple of days into the case when I was sitting, reviewing the detailed balance sheet with the owner and CEO of the funds, where he just outright admitted half of the assets on the $200 million balance sheet didn’t exist and never existed. In this case, it was virtually all mortgages receivable on the asset side and investor notes payable on the liability side.

Stewart: That’s astonishing. He just flat said actually, they don’t exist?

Tod: Yeah. I basically had a detailed listing of the assets and said, “Look, if there’s a compromised asset, let’s just talk about it. Maybe there was double pledging of collateral or something like that.” I was expecting there to be some stories and some assets that were substantially less than their book value. I wasn’t expecting him to say half of the assets didn’t exist and never existed.

Stewart: Wow. Okay. Then, what happens?

Tod: Well, that changes the nature of a trusteeship pretty dramatically. I immediately let our legal, finance, and fiduciary team know of the conversation. There was some disbelief initially. Shortly thereafter, FBI, DOJ were contacted from a prosecution standpoint and, well, it kicked off a whole series of events. A bankruptcy trustee, for those that aren’t intimately involved with that, their exclusive job is to, number one, follow the rules of the US bankruptcy Code, and number two, maximize recovery for the benefits of creditors. Get as much money back for whoever the creditors are. In this case, it was mom-and-pop investors and some commercial investors who were left holding the bag on a couple hundred million dollars.

For us, we needed to be able to craft a strategy for recovery. How are we going to get as much money back for our constituents, the creditors? In order to do that, we had to really understand what the fact pattern was. And the fact pattern, the best thing that we could identify was bank statement activity, the books and records. Normally, you’d go to run some P&Ls, some balance sheets, figure out where things went wrong, where the companies started losing money. In this case, it was a fraud from day one. The only thing we could rely on was independently-sourced bank statements through subpoena. We couldn’t rely on the internal books and records. Totally beyond repair. Malevolently manipulated.

We couldn’t rely on the audited financial statements. There was actually audits done that showed a profitable insolvent group of companies when it was anything but. We couldn’t rely on that to get our bearings. And so the only thing that we could do to recreate, to the best of our ability, what happened over the 12-year life of the funds was taking transactions directly from bank statements.

Stewart: That’s amazing. I’m just amazed at that. Okay. At the risk of just sounding just plain old stupid, continue.

Tod: Fair enough. Well, I had started my career in public accounting as an auditor with one of the big four firms. I moved over into technology firms in operational financial roles. Chris and I met 20 years ago at a streaming media startup. Chris was a product guy, I was a corporate controller. Then, evolved into, maybe devolved into bankruptcy, restructuring, out-of-court workouts, special operations scenarios. In that, with this huge amount of work that had to be done, we ended up with tens of thousands of pages of bank statements, 50 accounts, 20 different legal entities going back about 12 years in total. There’s this huge body of work to just get … Bank statements don’t mean anything. You have to extract information out of it. You have to make sure that data is correct, it’s accurate. There’s nothing missing, there’s nothing wrong, there’s nothing duplicate.

I really scoured the landscape from a technology standpoint, figuring there must be some tools for investigators out there in these follow-the-money situations, and really came up short in terms of what I was looking for. That led us to putting together a team, assembling a team in India, helping to manually transcribe those transactions into Excel workbooks. There was a bunch of pluses, there was a bunch of minuses associated with that, but there was an incredible amount of QA work that had to be done on the backend of that.

Stewart, there was also the FBI and DOJ doing the exact same thing in parallel and not sharing their information with us. It’s a one-way share when you’re working with federal agencies and investigators, you provide them with any relevant information that you have, they don’t really provide anything to you. Not only was there this huge administrative exercise, it was duplicated for different constituents, prosecution versus the trustee and bankruptcy process.

Stewart: Very cool. Chris, then, what’s the next step here? You and Chris get together and you begin to build these tools into what is now Valid8?

Chris: Yeah, it went like that. We’ve known each other for a while, so we started talking back and forth. Tod said, “Hey, I was just on this case. There should be software that does this.” I’m not an accountant. I come from the enterprise data center technology. Think network data storage and networking and those sorts of things. At first, I’m like, “Oh, I don’t know about this, Tod. How many Ponzi schemes are out there? It seems pretty focused and pretty nichey.” But we kept talking about it year-on-year and what we started to realize, what I started to realize is, coming from the professional space, I started realizing that the data requirements for a professional, like a CPA or an attorney, or even a government investigator that’s going into this, the data requirements are very different.

You have to be very precise about the data that you’re getting. Who are you getting it from, and how do you prove that it’s accurate? That’s when it got really interesting. Because if you think about it in that context, any situation, whether it’s a fraud investigation, whether it’s an audit, whether it’s a tax analysis or opinion, whether it’s merger or acquisition or a hardcore white collar crime investigation, high-net-worth divorce, all of those situations where there’s complex discovery, you need data that you can rely on in a court of law. When we recognized the scope, that it’s way beyond just Ponzi, it’s just anything where a professional is providing an opinion based on this financial discovery, you need these data algorithms and this prep automation cleanup. That’s when the light bulb went on.

That’s a huge market out there. If you think about the number of audits that go on, the number of M&A diligence, quality of earnings, the number of tax cases that are being prosecuted, the scope gets really big really fast. That’s where we said, okay, what’s really needed out there is a software platform that’s designed specifically for professionals that delivers verified financial intelligence. That’s essentially what we built and what Valid8 is. It’s a platform for these professionals to go collect and aggregate lots of different sources of financial evidence. And then we have software and algorithms that puts it all together in a transaction database, with visualizations and matching algorithms and all kinds of stuff, so that you can understand what’s happening and you can rely on the output in a court of law. That’s essentially what Valid8 is.

Stewart: When you say you can visualize it, you can literally see, follow the money, right? It’s visible?

Tod: Yeah. Let me give another example just out of that Ponzi case. Once you get all the bank statement transactions, there’s a whole bunch of additional work that you have to do, just general QA of the data. You’re also starting to label. Here’s investor money coming in. Here’s ‘bad guy did normal Ponzi things’. Bought two jets, two yachts, four homes. We were needing to trace where the funds came from to purchase each one of those assets. Of course, it was investor money coming in, getting laundered through a half dozen accounts, going to the bad guy’s account. And then the funds were getting wired out from there.

Using traditional methods without software, once you already had the data, once you’ve already QA’ed the data, just going through and running the individual tracing on those was taking two to three days to put together the complete package to effectively go file the motion that our investors, the estate’s investors, were entitled to the proceeds of the liquidation of each one of those assets. The idea that Chris and I had is, well, one, be able to pull in vast volumes of financial data, be able to QA it, and then be able to quickly analyze and interpret it. That was really a connection point, and that analysis is such a critical phase.

Just as an example, in the Ponzi case, we used that database to verify creditors’ claims. Lots of people said, “Hey, I’m owed money. Here’s backup showing my investment.” We had to vet all of those. If there’s a net winner, what’s called a net winner, in a Ponzi case, somebody who made an investment, got out with a profit, you can’t do that. The trustee came after and clawed back what the net winners, the net investment positive situations. We identified flows of funds, movement of money between 20 different related entities, which was critical.

We identified assets, like I just identified, and recipients of money with no legitimate business interest. Had to go chase after them. FBI, DOJ’s database, they were using the same thing, but for prosecution and ultimately a restitution calculation at sentencing or immediately after sentencing. Lots of different uses for how the bank data gets used and ultimately capitalized upon, but the tools that exist just weren’t there. Visualization, as you and Chris were talking about, is a big part of accelerating intelligence from a dataset from a particular case, ultimately leading towards strategy and execution on that.

Stewart: Who are your major clients?

Chris: Yeah. They fall into three main buckets. They’ll be directly the law firms, specifically the cases where complex financial discovery is required. High-net-worth divorce, corporate bankruptcy, financial litigation, fraud investigations and prosecutions, those sorts of things. White collar crime.

We also sell to accountants, specifically CPA firms, primarily to the forensic evaluation practice, but we also have solutions to help do full population testing and audit. That same technology can be used in M&As, so into the advisory practice. We also do several complex tax cases as well where the accountants are going through proving income and those sorts of things. Basically, any practice area in a CPA firm.

And then the third key customer is going to be government agencies; so federal, state, and local. We’ve got all flavors from major metro police departments up to state AG offices, to federal agencies. And it’s all about white collar crime, government prosecutions of fraud, essentially. In that case, it’s less CPAs, more just hardcore analysts and forensic accountants that are on staff at those agencies.

Stewart: That’s very interesting. Tod, right before we hopped on here, you’d mentioned that a very large recovery tied you back to the insurance industry. Is that the Ponzi scheme that you’re talking about now?

Tod: Yeah, that’s right. I mentioned that one of the things that we couldn’t rely on, as the trustee, to get our bearings in terms of what historically was happening, one of the things we couldn’t rely on was the audited financial statements. The fraudster, in this case, was able to get a number of clean audit opinions, audited financial statements, through a well-reputed, strong firm who just, frankly, screwed up multiple times. As we, again, with the trustees’ focus on recovery, we looked at, where was their opportunity for recovery? Not just physical assets, liquidation thereof, et cetera, but who else was culpable in this? There was litigation against banks, where this guy had all of this money, 50 accounts, money flowing directly through, lots of transfers, lots of insufficient funds that were going through. There obviously wasn’t robust know-your-customer diligence done.

There was also litigation against the auditors, and obviously when you’re suing banks and you’re suing auditors, you’re suing their professional liability insurance companies. We had a couple years of litigation, ultimately an out-of-court settlement for the audits that were failed, the beneficiaries obviously being the creditors in this case, but there was a lot of exposure for that firm. The initial litigation was well above insurance limits and ultimately the settlement that was in place was below those limits, but it was a very material amount of pain and payout from the insurance community. As Chris and I started thinking about other areas of applicability.

Auditors, where I started my career, auditors still use statistical sampling. When they’re looking at financial statements, they’re breaking those financial statements down to accounts. They’re sampling transactions out of those accounts and then projecting the results of those samples onto the whole population of the accounts and therefore, the financial statements. That’s been the state of the art since 1934. Right now, we’re at the 90-year anniversary of statistical sampling for auditing financial statements. We believe that bank evidence is a vastly underutilized part of audit, underwriting, ongoing monitoring. Bank statements don’t lie, and the vast majority of transactions that flow through an accounting system should be reflected in bank statement activity. When you send out an invoice, you should see a cash receipt. When you make payroll, you should see a cash disbursement. On and on and on.

Tens of thousands or millions of transactions over the course of a year, the vast majority of them being reflected in bank statement activity. When you took a look at what actually happened in the fraud case, in the Ponzi case, from a financial standpoint versus what happened in the bank statements, they didn’t match up. There were huge holes. We’re going to be addressing the audit market and modernizing the tools and techniques to take into account big data, full population testing, back to bank statements and other evidence.

Stewart: That’s really interesting. I guess it gets me to this question, what is the state of fraud right now, given the current economy? The genesis for the question really gets around. I hear, and I’m not alone here, there’s reporting of theft in major cities to the point where retailers are just walking away. For some reason or the other, I don’t know why, but post-pandemic, it seems like folks think that taking things that doesn’t belong to them is okay, and I’m wondering if that is also the case in more sophisticated kinds of fraud.

Chris: Yeah. For sure. I’m going to let Tod take this one. He’s the expert. But also, in addition to what’s happening at a lot of the major metros, think about all the stimulus and all the funds that have been pumped into the economy, there is a certain level percentage there that was taken advantage of and has not been found or prosecuted yet. There’s just a ton of stuff that’s out in the industry right now, and I think we’re on the cusp of a huge wave, tidal wave of investigations and clawbacks. It takes a while for all stuff to set in, but Tod’s got some great insight into this.

Tod: Yeah. Look, at the end of the day, fraud is always happening. But there are waves in terms of when there’s more or less investigations, more or less bankruptcies that are going on. Those things are not the same, but often related. Typically, the economic cycles go once every seven years. Typically, five years of a growing economy, two years of a contracting economy. I’m not an economist, but that’s in very rough terms. It’s been now 14, 15 years since the last economic recovery. Ignoring the initial blip that we had at the onset of the pandemic, there has not been significant amounts of bankruptcies. There have not been a significant amount of large-scale investigations and frauds exposed.

I’m talking about major headline cases like Madoff and the Meridian Ponzi scheme, the case that I’ve been talking about. Those things all came in waves and it’s often when there’s illiquidity in the market. When interest rates rise, when it’s more difficult to raise money from investors, that’s when the music stops and the investigations start. It’s been an extremely long period of time, by historical standards, since we’ve had our last corrections. So we’re starting to see cases in Q4 of last year, FTX, some crypto cases make headlines. There’s a bunch more that we expect will be forthcoming with the rising interest rates that we’ve seen in the last couple of quarters.

It’s definitely a much more challenging environment for anyone to be raising investment or debt funds regardless, and that’s usually when the frauds start getting exposed.

Stewart: When we talked about this call earlier, that’s what struck me was you said you need a dislocation and that will precipitate. I think the term you used was the tide going out. It’s a term that I’ve heard Buffett use, too. You can’t tell who’s swimming naked until the tide goes out. And you’re right. You haven’t seen a big Madoff. Obviously, you mentioned FTX. That’s massive and there’s, I think, more to come.

What are the challenges to identifying and prosecuting fraud? What I’m hearing in this explanation is that there are a zillion transactions and that you need to be able to look at all of them, which is currently, you have the technology to do that, but not everybody does. But as tools get better to investigate fraud, it stands to reason that we’re going to discover more fraud, right?

Tod: Yeah, I just say we’ve all been hearing a lot about big data over the last 10 years. Big data just means you’ve formally had access to very limited amounts or the ability to … Even if you had access to vast amounts of data, that you didn’t have the ability to analyze and ingest that. Things are changing considerably, whether we’re talking about artificial intelligence, new tools, machine learning, software like Valid8, even going really far out there into quantum computing and so on. The ability to ingest large volumes of data, we’re absolutely still in the early days of being able to do just that.

What we’ve built specifically is focused on follow-the-money investigations, where there’s a need to understand where did money come, where did it go, how did it get there? And to be able to do that in a matter of hours or days rather than months, quarters or years for some of the bigger investigations. I think it’s just going to be a breathtakingly fascinating era that we’re still on the early days of, is AI. Chris and I have been paying attention to for quite a while on the periphery. I’m not a computer scientist, but certainly of great interest.

That’s been out there, being discussed. Lots of publications, lots of books, lots of academic research, an amazing amount of investment, but not a lot of public awareness and PR until just first quarter this year with ChatGPT. It’s going to be an absolutely fascinating era.

Stewart: Our audience is overwhelmingly insurance, and one of the things I was going to ask Chris is, how does this technology help daylight insurance fraud more quickly in particular?

Chris: Yeah, it just goes to the nature of fraud itself. A lot of people think of these complex schemes and really smart people doing algorithms and all this stuff. If you get in a lot of these cases, you realize that what it really is, is somebody has access to a bank account and does something wrong, moves it where they shouldn’t be moving it. It’s literally that simple. What it really comes down to, back to your prior question, just before I get into this one, just the challenge is just transparency. There is no transparency because the data is hard to access and put in a format where you can look and understand and see what’s happened.

Because it’s difficult to get and to see, there’s opaqueness and people take advantage of that, and that’s the key thing for insurance fraud. Instead of just assuming a risk and then there will be a certain amount that’s going to happen in being right or wrong, I see a world where insurance is going to want to monitor some of these assets that have a lot of cash flow going in and out, and actually be looking at exactly what’s happening. Today, that’s just not possible. It’s like sampling. You don’t have any tools. There’s no way you can look at anything, so you sample.

Well, what if you could look at everything and see everything and monitor everything? What does that do to the risk equation? That reduces it tremendously. And then in terms of just prosecuting the ongoing fraud, again, in complex situations where there’s lots of cash changing hands, and these are very specific situations, this doesn’t apply to all insurance fraud, but for those cases where it’s cash-intensive, lots of entities, lots of accounts, if there’s suspicion, we can come in and really help daylight exactly what’s happening very quickly without spending the millions of dollars of professional fees to look through everything. That’s where we play and tie into.

We do have several very large insurance fraud cases that we’re currently working on, and that’s what it’s about. It’s very specific cases where there’s lots of entities, lots of accounts, lots of money exchanging hands, and we can provide transparency into that and help get the bottom of what’s happening.

Stewart: What comes to mind for me is, is there a healthcare example that you’ve got that you can share with our listeners before we wrap?

Chris: Yeah, there’s a healthcare situation. There’s auto insurance. It varies specifically, and a lot of the cases are confidential and we can’t talk about specifics. But again, I’ll go back to the nature of the cases. There’s a network of entities, and there’s kickbacks involved and it gets pretty complex pretty fast, and it covers several states. But the key thing is, there’s no way that a legal body or a forensic accountant could assess everything and see everything without the help of a VFI platform like we provide. The ability to quickly ingest, to tie everything together to see the flow of funds in those situations where there’s hundreds and even thousands of different entities, that’s where we’re being used in the insurance fraud space.

Tod: At the end of the day, Stewart, fraudsters thrive in opacity. Daylight, insight and transparency are the enemy from their standpoint, and they’re the friend of insurers or anybody that wants to really get at what’s happening. Thankfully, the tools, including what we’ve built, for increasing that transparency, insight, timeliness at a reduced cost, we’re entering an exciting new era.

Stewart: That’s fantastic. I’ve got a quick question on the way out the door. I got two questions. One guy can take one, one can take the other one. I’ll start with you, Tod. The questions are, who would you most like to have lunch with, alive or dead, or best piece of advice you ever got?

Tod: The most interesting person that I’d like to have lunch with? I’d modify that into the most interesting two people. I just cannot stop watching whenever I see Warren Buffet and Charlie Munger. Just the wisdom and the knowledge that those two guys have, and their long-term friendship and incredible performance, and collective insight and reliance on one another, I just find their friendship and their insight absolutely fascinating. I think society’s been lucky to have those two around for as long as we have.

Stewart: That’s fantastic. Chris, you can have either question. Best piece of advice you ever got, or who’d you most like to have lunch with, alive or dead?

Chris: Yeah. I’m going to do the best piece of advice. That goes back to my roots. I grew up in North Dakota. My grandfather used to tell me all the time, “You can lead a horse to water, but you can’t make them drink.” It’s very similar to what we’re doing at Valid8. We show you exactly what’s going on, but our professionals are actually deciding, what to use, the data. It’s just a good, humble understanding of you can only do so much. You can only get it to a certain state, and then it’s out of your control. And you’ve got to recognize that.

Stewart: That’s fantastic. Great way to wrap. Thanks for being on. We’ve been joined by Tod McDonald and Chris McCall of Valid8. Guys, thanks for being on with me.

Chris: Thanks, Stewart.

Tod: Thanks, Stewart.

Stewart: Thanks for listening. If you have ideas for podcasts, please shoot me a note at Please rate us, like us, and review us on Apple Podcast or wherever you get your podcast. My name’s Stewart Foley and this is the podcast.

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