EP17 – Using Voice Technology to Flag Risk. A Conversation with Alexander Martin, CEO of Clearspeed

Voice technologies have made major strides in just the past few years. In this episode of The Coverager Podcast, Nick spoke with Alexander Martin, CEO of Clearspeed and former Captain in the Marine Corp. Alex and I discussed how Clearspeed is using voice technology to flag risk. Using simple yes/no questionnaires, Clearspeed can quickly flag suspicious answers for further human adjudication. The same scalable technology the military has used for quite some time to quickly flag potential bad actors. Clearspeed is using their technology in hiring situations, security and in insurance, claims fraud and underwriting.

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Transcript

Nick
So we're live. Take two...because I'm such a goofball. Alexander Martin, Alex from AC Global Risk has agreed to come back even though completely botched the first recording. And so...tech savvy...I have never claimed to be Alex.

Alex M
That's all right. Absolutely.

Nick
So I'll start over again with AC global rescue you and I met at ITC last year and I was extremely interested in the technology. Justin Fowler her made the introduction to us. And so why don't we give the audience a flavor AC Global Risk, elevator pitch in your own words....

Alex M
Yeah, great. Well, thanks for having me on. It's good to be good to be back. For my for my second time,

Nick
no, it's just weekly.

Alex M
Yeah, why not? No, I'd love it. No, it's great. But But what we're what we're doing here is we're using voice analytics technology to help to help do some blind spot coverage for companies that are you know, missing missing potential risk, or in the case of the insurance market, fraud And we're coming at it from a completely different, completely different angle. And so instead of coming at it from a position of, you know, treating every potential caller as as high risk, actually, we're coming at it from a position of clearance and kind of the ability to clear a lot of people better faster, leveraging our voice analytics platform, but also in the process we're alerting to, to risk that that is often missed. And so that the highest level, you know, soundbite for for AC Global Risk is, you know, a, an ecosystem enhancer that identifies fraud that that otherwise goes undetected.

Nick
Yeah. And so maybe you can spend a couple minutes and actually talk about the technology because it's so interesting, right? And it's got a long history. So in a nutshell, you're using things dealing with voice like the way that I am talking now. And right can actually pick apart various aspects of it, to deduce what my intentions are, in that. So talk, talk a little bit about the history and the significant amount of research that has been done over the past few decades to get to this point where it's actually can be used in a lot of different cases. And you've picked, you know, you've kind of really honed in on the fraud element of insurance.

Alex M
Right? Sure. So, the voice is a really exciting frontier...frontier with respect to opening up a lot of new opportunities for a host of industries. And, you know, we're kind of focused on hiring, insurance and then security, so insider threat or, you know, in the government and military kind of worlds as well for force protection. But it all ends up being the same thing. And so what that is in terms of how it's delivered and what we're what we're looking for, and what that is, is we're automating questionnaires, so yes/no response based questionnaires and if we kind of press pause on that and go back in a little bit into, into the voice itself. Voice is very rich with information and think about how we're now using voice to interact in our daily lives in ways we thought, you know, was just science fiction this a few years ago, right. So between assistance and voice recognition, there's some stuff going on. That's interesting on the lie detection, you know, markets. But what's fascinating about the voice is that, and now there's a corpus of research and validated kind of science behind what's going on. And what can be detected and measured in the voice is that it's highly scalable, and its ability to kind of touch, you know, vast amounts of people in a repeatable way. And then the richness that's in there and the analytics behind that allow for a very great enhanced, you know, customer experience, as well as adding a lot of benefit to the end user. And so what we're doing in particular, is we're taking the yes/no structured interview and so from our backgrounds in counterintelligence in the military in the intelligence world, you know, everything that went on was all about, you know, yes, no interviews, right. And so the ability to collect information and just talk to people about these client defined questions as they related to risk. The problem with that is it doesn't scale, right? You can't scale that human expert who needs to sit down across the table from someone to make a decision, using their judgment, their experience, you know, the rule of law, empathy, all these things. So on the front end of that we wanted to do is, is create a sensor that was, that provides these very productive alerts so that that human expert is able to then do their job better and faster, so highly, you know, resource allocation, but also right, picking up risk that happened that is missed otherwise. And so what we're doing is we're kind of bundling three things together. The first is the method of these customized questionnaires. That's taking all these yes/no responses that you're working about, you know, think about underwriting thing but all the dearth of information that these, you know, very sophisticated underwriters are having to do but they they have imperfect information at times and so we're automating that that questionnaire Are you are you a smoker? You know, are you currently at risk for ABCD conditions? The second thing that we're doing is then we're actually providing some real analytics behind this, we call it the convoy threat risk recognition and analytics, we're recognizing risk, and that is how that questionnaire impacts the speech of those responding. And the point is, it shouldn't impact the speech. Right? If you were asked a questionnaire did you kill john F. Kennedy, your response would be no, that would not your the neurocognitive reaction that we're detecting and measuring in that speech would actually result in a normal no form and our system would say you're low risk, but if in fact, you were a smoker, and you're submitting your life insurance claim, and you're in fact withholding that information it would impact your response we would detect that, measure that. And we would be able to report in this kind of third aspect, which is the, you know, the ability for us to conduct recurring audits or, you know, individualized questionnaires in a way that that gleans information that would otherwise be missed. And that's kind of how the science of how a real world environment impacts speech, how that speech can be detected and measured, modeled, and then produced into a productive alert on a recurring basis and are using this platform.

Nick
So it's essentially a verbal polygraph.

Alex M
Well, you know, that's very interesting, because we're, we're trying to make a big distinction between polygraph does what we do, right? So if you think about think about in the taxonomy of risk and fraud detection, and you think about what problem a polygraph is trying to solve, and that problem is we're trying to do lie detection and then gain admission or confession to make a decision, right, and that's what that machine does. It helps detect changes in a human's physiological reactions, right. And it measures certain things that instrument is saying, hey, there's elevated, you know, elevated concern here for lying. And then that human is using that to, to dig on you and to then use that as a tool to elicit a confession. So that's what polygraph is doing right? But on the other end of the spectrum on this in this taxonomy of kind of, you know, deception and detection, there's alerts, right? And those are things that are untethered from the human, making the decision, and they're actually just providing beeps. So everything from a credit check, social media check, you know, any kind of background check, write anything that provides an alert, and they're not necessarily saying you're bad, don't process. They're just saying, hey, there's low, middle, medium or high risk here. What's your credit score? I'm sure yours is great. Maybe mine's lower. Does that mean that I'm not going to get a loan? No, it just means that's an indication that I'm risking. I could very well explain that. Right. And so we're playing very much in that size. And the reason why that matters, is we say, Hey, are you guys voice polygraph? No, because polygraph doesn't do screening and vetting, right? Polygraph does determination and adjudication, right? We're just providing sophisticated alerts, much like the metal detector in the airport, if you think about that, the purpose of the metal detector airport is to get people through, to get onto their flights and to get on with the business of their life. If you metal detector alerts, it's not saying that person is bad, it's just saying is this a pen or a pistol? And then the agent can then do the work of mitigation and escalation. And so in that way, where we're actually you know, from the the algorithm to what we're measuring, detecting. We're so far away from from the polygraph, we're really doing completely, completely new mission, an automating in a way that, you know, is meant to enhance that funnel not to be that endpoint, if that makes sense.

Nick
Yeah, completely and and, you know, let's, let's explore on that and kind of tie it back to the customer service aspect that you deserve. One of the classical elements of the insurance business model is that it's a leveraged product, you pay a little bit of premium. And there's the opportunity to collect a lot on the inside, which means there are folks that desperate folks that would be willing to do bad things in order to get access to the contract, so they can get a lot of money. That's the fraud element of it. And you know, fraud is kind of endemic and insurance but in fact, like your metal detector case, most most people would never consider doing fraud isn't like frauds. A very it's actually a very small percentage, but it's meaningful percentage. So you want to catch it, you want to root it out. But in our prior conversation before I screwed up the technical components of the interview, you had described how You know, from a customer service standpoint, why would you grill a potential prospect or customer? When the likely very, there's a very high likelihood that they're not committing fraud? Right? So can you talk about that element of this particular technology and, you know, basically treating customers like like customers and you want to treat you want them to be valued and just trying to root out the rest?

Alex M
Yeah, that's absolutely so kind of the golden rule like treat customers as you'd want to be treated. And, and I think underlying in even how the technology works to its application is actually a element of kind of opt in to fast track and and kind of like a no harm kind of lane and what I mean by that, if I'm, if I'm a customer and I want my life insurance, and that process is going to take weeks, with in person visits and people coming into my home to do very invasive things like draw blood and, you know, weigh me and you know, have an in person discussion about my health. And then all that information very slowly goes to someone who's going to, you know, adjudicate and make a decision of what my premium is. If I had a choice to take a telephonic questionnaire where I know the questions in advance, you know, are you a smoker, is your application accurate, blah, blah, blah, and I had a chance to click one button that allows me to then get a text to my phone, take a quick voice questionnaire and get through that in a matter of then have my case adjudicated in a day as opposed to dozens or more. You know, that's where I think the customer experience gets greatly enhanced. If I don't want to take that questionnaire, I don't have to I can go through the whole process and the blood person and get the blood work done and kind of do that and that becomes, you know, a process that is very much. You know, high touch, labor intensive. It costs the insurance company a lot of money. It costs me as the end user a lot of time and so you The idea of using technology to get ahead because again, I'm not committing fraud, I'm not worried about I'm not worried about this, I'd actually like this process to move faster and not have my blood drawn, etc. I think it's a good a good, you know, way to think about this from a customer use case enhancing experience.

Nick
Yeah, it's like self checkout. Right? You know, it's, for some people, it's no, I, you know, for whatever reason, I want someone to, you know, scan my stuff in, but often for me, you know, it's and I think a lot of younger professionals as well, is they just want to get through the line, like the line in the the time consuming nature of that is the, drawback.

Alex M
Mm hmm.

Nick
Do it. And so to me, it's like, I just want to get the hell out of the store. So I would gladly do that. And as you're describing it, yeah, I would gladly give up having to go get a physical or blood drawn On, or, you know, extended out months and months and months when it's like, I want resolution as quickly as possible. Right? Yeah, I'll I will go through this. And the advantage is it's not invasive.

Alex M
That's right. And and, you know, often cases, we see people launch with the, with allowing the customer to have the results in their hand. So, hey, yes, I want this faster, I want to move to the front line, I'm going to then take this automated question, or maybe you get to get through results are going to come back to me and I can determine whether or not to share them with the end user or not with with with the provider. And in that way, jumps me to the front of line on my own terms. Oh, I got a hit on question three, I'm at high risk there. Why? Well, that was around smoking in the past 12 months? Well, you know, actually, I've had a few and so on, I'm just going to go through the normal process and you know, kind of kind of, you know, move accordingly. But, you know, in that way, it's it's all about empowerment and allowing people to make the choice for themselves to move forward on their own on their own terms and With full, you know, consent and disclosure in the court, we all know what the questions are going to be. I mean, it ends up being an absolute net positive for for the end user to move quickly, through questions they're not worried about.

Nick
Yeah, do do. Are you in different lines of business now? Or is this easily transferable to auto homeowners like it? Is there any limitations to it in the insurance realm?

Alex M
Yeah, I mean, with anything, there's limitations to our tech and there's limitations in the market. I think we're seeing a lot of stuff in kind of the higher volume, lower, you know, lower amounts, we're seeing a lot moved away from voice and calls and, you know, people just using leveraging couple pictures and, you know, their their devices to process claims. And that's great, right, because that's about fast tracking and getting people through processes and moving them quickly. It's where we see the opportunity across different lines is in places where there is a lot of high touch or there is A lot of risk at the other end, there's hype, you know, there's there's heavy payouts there there's big if there is an instance of fraud, these can cost hundreds of thousands of dollars, if not more. And these are ones where they're leveraging, you know, everything from human surveillance teams to any matter of interviews done over a phone with a live agent. And these are the areas where we can come in, enhance, and really help the customer experience but also help the human teams do their job better, faster. But yeah, but I think you're seeing I think, across the board, you're seeing a bigger push towards, you know, the use of kind of AI ml driven technologies and getting people out and over this kind of hurdle. And I think the markets, you know, really wide open for that, but specifically for us, we're seeing, you know, great traction opportunity in in underwriting as well as when we talk about workman's comp. And there's other aspects of, you know, dealing with diligence and kind of follow up investigations that have been, you know, very exciting to see how we can help make Those things, lubricate those processes more.

Nick
So word of warning to any of my broker friends that are listening, you may want to close your ears. Alex, is there a way we can do this kind of questionnaire for brokers submitted applications?

Alex M
Absolutely. I mean, the use cases, you know, are that again and again, assuming that the brokers want to get more, more through a pipe better and faster, right. This could be a tool to help accelerate that, you know, and there's also there's also advantages to kind of the under the underbanked. The under insured markets. You know, we're seeing some interesting plays in a geographic context when you think about people need to expand in the markets overseas. Now think about COVID how are you going to be doing this with you know, even more need and necessity to leverage remote right capability and then the underlying technology is called remote risk assessment. It was designed to telephonically and remotely deliver risk assessment Because humans can't move to these places, so there's an opportunity to get more market share, but also even here in the US, or in these markets that are expanding to immigrant populations, people that are, you know, now becoming business owners, and, you know, need to be served, and are, but don't have a FICO score or you know, don't have the credit history or don't have the past performance to be able to need to be able to link up with brokers to get deals done as their businesses expand. And so I think in that way, I think there's, there's a, there's a big opportunity, and if we're worried about fraud in the brokerage aspect, and I think, you know, the best case is always when it's driven by the community, right, and it's a lot of it's about education, and the education of a fraud as a as a as a wave that impacts negatively everyone. And I think sometimes, you know, even the end user from that person that thinks, you know, I'm a good person, and these are my values, but I've been paying thousands of dollars to this, you know, this insurance company that I've never seen before, and they owe me Right, and you're able to rationalize in that one context, why this case should happen. And I think, you know, those incidents of fraud are probably, you know, more hurtful to everyone than even the professional fraudster who goes out and kind of tries to weaponize fraud across, you know, very deliberate base. And so it ends up being a discussion that again, going back to the broker discussion, education and understanding of, Hey, this is where the fraud is happening. This is how it hurts the industry and us and the and the people in a way that is really negative and needs change. And that change needs to be driven by us. And therefore these kind of tools help that.

Nick
Yep. And you brought up immigrants. So language can be configured pretty pretty easily as well.

Alex M
Yeah, it's all Yes, no responses. And so think of think of, you know, see no, Don yet nom Lom any of these of these responses, all Yes, no. And our software is just grabbing those those single utterances. And that's what we're That's what we're running the analytics on. And so it is it is language agnostic, they're able to hear they don't need to read, you know, they just simply pick phone hear the interview, they're engaged with that questionnaire, and we're just we're just scoring those responses that easily

Nick
it just the casual curious questions and you know, a lot of languages a lot of cultures, yes and no, as I say, I mean, hello and goodbye are the same word. Or any cultures where yes and no could produce the same emotional reactions like that just something within the culture. It's just their, their, their the ambiguous culture.

Alex M
Yeah, we haven't seen that yet. But your point on culture is really important because how we ask the questions how the really the machine asked the questions, is vitally important that they understand what the question is and why. Right and so you're spot on in that if you ask the wrong Question or in the wrong way, you might, you know, elicit a false positive, right or or, you know, a false negative. Right. And so in the case of of how we do that the tuning of the sensor is really putting in the hands of people that know the language and culture as experts, and then they help make sure the questions are very, very concrete. But in terms of ultimately, yes, no, as long as you ask the question the appropriate way to that person who's hearing it, and they understand it, then you have no problem. Yeah.

Nick
I'm glad I asked that question. Because now like, I'm thinking, I this your whole technology, to me sounds like episodes of homeland. You know, because now, you know, it could also matter if so the voice that's asking it could also matter if it's male or female, right? Like there's a that that gets to you go down a rabbit hole of a whole bunch of stuff of could be, you know, religious connotations. You know, I, I need to respond this way because a male asked me or a female asked me or that must be, is it Have you sort of come to grips with that like, kind of got it manageable? Or are you kind of always keeping open of like, Hey, we need for this culture, this language, you need to be very aware of the specific instances because you could get a false positive or false negative.

Alex M
Yeah, absolutely. And we do, we have experts on our team on kind of our engineering and the science side, but also, you know, partners who help us in the region who really know those things and help a tune for that. Even even kind of, you know, things as simple as like words that translate maybe at a academic level, but don't translate at a real user level. And so, you know, we were doing some really interesting work in the Philippines for basically protecting pipe pipelines and supply chains, and there's a great Deal theft going on across thousands of miles of supply chain pipeline, and also, a lot of different people involved very hard to determine where that risk is. But the point there was 99.9% of the people there, were not involved in this multi year theft ring. And so it wasn't a polygraph problem, let's put thousands of people on a polygraph because you're lying. To me, it was a screening problem, meaning we needed to clear 99.9% of the good so that a handful of people at risk could then just have a conversation with an investigator to determine whether or not they were involved or not. And that was our mission. Right. And that became an enduring mission. And in that way, we're able to engage with the folks there in a very, you know, user friendly way, clear them in minutes, alert to risk that they've missed and couldn't get to without us, and then allow those people to have a follow up conversation. But why that matter to this point, is in the early instance, we were using words for fuel that in the more local context, that Nothing to do with crude oil, and was more like fuel like wood for a fire or a fuel you would use to heat you know, a stove. And and so that first word makes sense when you're, I got a master's degree and you're in Manila, and you're using those words, but at the village level in places we were conducting our interviews, this was not translating. And so people were like, No, you know, this is the and this was the wrong word. And so just as an example, really understanding your partner and her using using the right words, words have meaning in the insurance context, right words have meaning that they do differently in other financial services, sectors, and so on. And so it's really important we know our customer, our customer knows us knows that the sensors tuned by these questions, and how to ask the right questions. the right context matters a great deal.

Nick
Yeah, I mean, given the environment that we in with this pandemic, a lot of it sounds like you know, the typical epidemiologist epidemiology testing like testing screening, right? You know, let this is, this is how we find this thing. But let's, you know, let's not assume everybody has it and if they pass the test, they go through the, they can pass through and then we'll, we'll worry about the others. Amazing how much overlap there is with that. What does what does a typical engagement look like? So for a carrier or someone that's trying to, you know, deliver this sort of framework to their underwriting to their claims, fraud detection, how would they play ball with AC global?

Alex M
Yes, which usually identification where's the where's the toughest spot we've found great success in starting with with a short pilot because it allows me have a very have no no kind of it. Connectivity needed flow at low it lift. And so the put the pilot allows us to do is both get the questions kind of wired for the pilot And also in a spot where they're traditionally having a great deal of pain or expense, insert ourselves and be able to, in very short order produce kind of meaningful, productive data that can be seen Wow, here's the business case that we were that we were told. And in that way it kind of reveals itself in real time as to being you know, a cost saver and a time saver. And then from that pilot, what usually happens is a change or two of questions. So kind of I call it like a tuning of the sensor a want this question out, put this question in, and then being able to plug it into a into the workflow accordingly. So it's really that three step process identification of pain, pilot produce results, benefit them show demonstrated enroll into kind of production. And that's really the the three step processes work. You know, very well for us so far.

Nick
Yeah. And no necessary. There's not necessarily any issues with legacy technology either. Right? Right. Yeah. But even carriers that, you know, have decades old systems, your your technology and your ability to engage with them is not necessarily dependent on pulling information from those systems or interacting with them where that could be a stranglehold on on on efficiency.

Alex M
That's right. And and it's also an investment in legacy systems. If you're using like a, you know, a pin drop platform, very elegant, beautiful, you know, suite of technologies. You know, this is a way to kind of integrate into that into that larger platform and get even more value out of that investment. Yeah.

Nick
So your background is in the military.

Unknown Speaker
Yeah. Got insurance.

Nick
Yes. So can you talk about, like that moment where you were not all military. I think military people have the necessary training to become entrepreneurs. Most of them do not but you know, they They're very regimented and focused on process. When did you know that the military might not necessarily be enough that you would want to serve society in a different way with different solutions?

Alex M
Yeah, you know, I think there's a lot of great parallels to kind of, you know, the military community and entrepreneurs. You know, one of the one of the things that I always think about is, you know, entrepreneurs, someone that is absolutely fanatical about new creating something new to solve a really big problem, and they're more than likely going to do it in a small team, you know, of highly capable, wildly talented people who are iterating on that, to solve that with that fanaticism tied to like a higher purpose. And so the higher purpose, you know, isn't, you know, making money the higher purpose is change. Right now, you create the business so that you know, it's profitable, and that profitability allows you to raise more capital and make money. broad sweeping change. But I think you talked to most entrepreneurs, the fanaticism isn't driven by some hope for an exit with monetary gain. I think that's a byproduct that's unrealized. And it's, it would be fantastic for those that that are lucky. But the entrepreneur, spirit is a, we're solving this problem, it's going to be really hard. There's going to be a lot of, you know, a lot of casualties along the way, we're going to have to sacrifice a lot, including ourselves, our personal lives and everything tremendously for that higher calling. And I think, in that way, very nicely kind of ties into, you know, the veteran mindset of, hey, we're going to be a small group of people and do this thing that is going to be really hard and might be really unpopular, but we're not tied to this kind of political winds, we believe in a higher calling, which is service to our to our country. And so in that way, I think that just tie in of, you know, being in part of a small team being you know, highly creative and really, you know, tough and working through challenges over time, I think is what drew me to You know, the transition out, and being able to use the same kind of value driven approach to problem solving where I didn't come up with this technology. It was a team of brilliant people that I was connected to, because I in my first startup was trying to solve the same problem of how do I get great people hired in places where there's no background checks, right. And that was, that was my thing of like, we need to hire great people, but there's no way to, to make sure that they can be trusted, and they can trust me or trust is a two way street. And so this pulled the thread to bring us to what we're doing today. And the hope here and we're building is yes, that we create a technology that can help you know, in insurance companies, you know, identify fraud and grow their market share, but in a much broader context. Those insurance experts lineup next to our government security experts lineup next door HR experts, and everyone there is trying to do the same thing which is you know, advance their business to achieve their vision, their greater purpose and if we can be a part of that in a way where kind of turned lie detection on its head and make it about clearance, and about fraud detection in a much more kind of elegant, user friendly way, then we'll be successful because that'll help. That'll help immigration in this country and beyond people move better, faster, it'll help trash could establish better faster on people's own terms of how people get hired and places they couldn't get hired to without us. And I think in that way that ties into the vision that we're trying to do here, which is effect positive change by allowing people to trust better faster.

Nick
Yeah. Do you do you think it's just an inclination on my part that, you know, the military war has changed so dramatically over the last couple centuries, where, you know, the whole idea of sacking a city and just like taking it like, that's not, that's not realistic anymore, that's been proven. Now, you know, we're the strongest country in the world, and time and time again, where it gets shown proven like, if the if the local people don't buy in, you're eventually going to lose, they will wear you down if they don't buy it. And so I see, you know, the military making this really strong effort, you know, winning the winning the hearts and minds, and using a lot of technology to do that. So as you're describing that, I'm thinking there's going to be a lot more opportunities because they are in real time testing out really complex technologies, systems techniques, in order to communicate that, hey, we're not the enemy that you think we are. We are we are on your side, and we're here to help. You know, sometimes it doesn't work. Sometimes it works. But it seems to me there's a lot to tap into there. There's a lot going on on the military side that we've learned in the last couple decades. That could turn into commercial related stuff because it's, you know, the commercial This is essentially a quasi war as well, just different kinds of casualties.

Alex M
Yeah, I think well, well said, I think the thing gleaned out of there is whether it's in, you know, in the military if you're a counterintelligence team, or whether you're, you know, in an insurance risk fraud identification team, those that expertise doesn't scale and when you're in, in, in combat or in the daily, you know, daily business of combat, you're just overwhelmed with, with, with information and in some cases, that information is often incomplete. Some of the other alerts you're getting are non productive. And so there's so much noise that it's very hard for you to do your job and we can't scale you can't scale as a business because of you know, the cost implications on the balance sheet, but you can't scale also because you're a human person with your own expertise and machines as good as they are. In often cases when we're talking about you know, counterintelligence or making a final decision for very high you know, high stakes insurance. claim requires some human in the loop for good reason. And to the extent that we can, you know, leverage these technologies into a productive ecosystem that are more harmoniously feeding that humans ability to interact, and guess what, you're going to get better interaction with a local population in a place that you're, you know, in a ground war with, and you're gonna have a better interaction with your customers, as as the customers are lost in the noise of fraudsters, and the better, the better connection is always made based on trust. And if we can accelerate trust, and we can outpace the fraudsters ability to slow down the trust building we're doing with the 99.9% of our customers are in the military perspective stakeholders, who are good people and just want to return to normalcy and get their kids in school and get their shops open again and get back to the business of being a human being in this troubling world. The extent to which we can use technology to outpace the bad guys, is the way we have to go and that's that that cycling and shortening of the Trust. You know, the trust equation, I think is vital of how technology can help us fight and win in both of those scenarios. Yeah,

Nick
just, it's amazing how much of our just our day to day interaction or day to day business interactions all boil down to trust. It's it's a

Alex M
Yeah

Nick
such a phenomenal concept, I think, very much misunderstood it, but it's straightforward. You have trust...things happen. Yep. So, thank you for your service. Thank you for coming on and explaining AC Global Risks. I will have your contact information, your company's contact information, transcript will all be in the show notes. So reach out there. Don't forget to subscribe and to Alexander Martin, of AC Global Risk. Thank you so much again, thanks for being patient with me.

Alex M
Absolutely. Thanks for having me on. I appreciate it.