Exploring AI-Powered Financial Data Governance with Safebooks AI’s Ahikam Kaufman

Episode Overview

​Ahikam Kaufman is a seasoned entrepreneur and executive with over two decades of experience in the technology and financial sectors. He co-founded Safebooks AI in December 2022, where he currently serves as Chief Executive Officer, leading the development of AI-driven solutions for financial data governance. Prior to this, Ahikam co-founded Check Inc. (later acquired by Intuit and rebranded as Mint Bills) in 2007, where he played a pivotal role as Chief Operating Officer in creating a mobile application that provided personal finance management and bill payment services.

Ahikam’s educational background includes a graduate degree from Bar-Ilana University. His extensive experience, spanning from co-founding startups to leading financial operations in established tech companies, highlights his deep understanding of the intersection between technology and finance. At Safebooks AI, he continues to leverage this expertise to drive advancements in financial data accuracy and compliance, positioning the company at the forefront of AI-powered financial solutions.

Episode Transcript

  Ahikam Kaufman: I think a lot of change in terms of like the infrastructure today, you don’t have to build everything from scratch. So I think today if you come up with a good concept or idea, the ability to go to market can happen much faster because there’s a lot of infrastructure that we have to develop at the time.

Kevin Rosenquist: Hello and welcome to Pay Pod, where we bring you conversations with the trailblazers shaping the future of payments and fintech. My name is Kevin Rosenquist. Thanks for listening. Today I’m joined by Ahikam  Kaufman, co-founder and CEO of Safebooks AI, a company at the forefront of leveraging artificial intelligence to revolutionize financial data governance with a rich background in fintech and entrepreneurship. Ahikam  leads Safebooks AI in providing real time validation and substantiation of financial data for enterprises. We explore the challenges of financial data management. The role of AI in ensuring data accuracy as well as compliance and the adventure of being a founder. So please welcome Ahikam  Kaufman. What do you love about being a founder?

Ahikam Kaufman: I think there is kind of a unique experience. You’re like fully responsible for the everything which is going on. It doesn’t mean that you do all the work, but you wake up in the morning and you know that, you know, in terms of the strategy, in terms of the culture and everything falls on your lap. So the idea, it gives you a great responsibility, but also a great sense of ownership, which I think is essential because accountability also is something that is hard to delegate too much. So it has to stop in one place. So that’s one thing. The other thing I’d like to think is that typically when you like founder or entrepreneur, you’re trying to do something different than what was done before. And that exploration is something we feel every day in our work. Some of the things we are doing are we’d like to think they’re kind of new to the world, and it’s just like a great sense of exploration and adventure. It’s also very difficult, but, uh, it’s unique.

Kevin Rosenquist: Are there times where you miss just being an employee at a company, rather than manning the ship on your own?

Ahikam Kaufman: You know, I’ve been doing this for, I would say, a better part of the last 15 years. You definitely want to sometimes pause and get off the train for a bit. You get that sense. But I think it’s it’s sometimes it’s stronger than you. But I will tell you this. I don’t know everything which happens in the company. So sometimes I would come in and people just develop a new feature and, you know, before you got the agony of like not having this feature, all of a sudden you see something new. So, you know, again, it’s like you don’t do everything. If you have a good team around you, they probably do most of the work and you still have the sense of responsibility, but your team would probably carry a lot of the heavy lifting and the execution. And it’s always fun because the power of a team is like, irreplaceable. So you don’t need to do everything yourself. But yes, sometimes you want to get off the train for like, uh, yeah.

Kevin Rosenquist: At least for a little bit just to take a break. Right. Yeah.

Ahikam Kaufman: It’s it’s more. Yeah, it’s more mentally and physically. So it’s not like the times. The hours. It’s like the sense of responsibility, ownership. You know, sometimes it comes down to, you know, do you have a sufficient runway and liquidity and it’s all yeah, it’s a more like a mental heavy lifting as opposed to anything else.

Kevin Rosenquist: You’ve had an extensive career in fintech, including co-founding Check Inc., which is now Intuit Mint Bills, which is which is really cool. What’s been the biggest shift in fintech since you started checking in 2007?

Ahikam Kaufman: Obviously, that’s a big question. I would tell you this when we started Shaq and I always was fortunate and lucky to work with, uh, a great partners and team members who’ve done great things even since then. We were one of the first 100 applications on the iPhone. Back in check. So.

Kevin Rosenquist: Wow.

Ahikam Kaufman: So really felt yeah, I had a very strong co-founder and partner who was the CEO. And when we started Shaq, at some point we developed a web application that helps you manage all your financials. And at some point he said, I think we should move to the mobile because the mobile would be a much better platform for virality and for adoption and for creating value. People would spend more time on the phone. And this was the early days of the iPhone. And then immediately when they announced the App Store, we before we even had an iPhone, because I don’t know if you remember this that year in 2007. Actually, you had to get in line to get an iPhone and then I will pretty long and we tried a few times, but we got an access to the SDK so you could develop it virtually. And we actually got on a Steve Jobs slide as being one of the first application on the iPhone. I think a lot of change in terms of infrastructure today, you don’t have to build everything from scratch. For example, when we started check, eventually we had to create all the connections to the banks ourselves. And now you have companies like plaid, plaid and others who can do that for you. So I think today if you come up with a good concept or idea, the ability to go to market can happen much faster because there is a lot of infrastructure that we have had to develop at the time. For example, in order to move money, we had to partner with a bank and, you know, those kind of partnerships in its infancy. So you had to explain to the bank what you do and why do you want to move money? You know, so the infrastructure is much better today.

Kevin Rosenquist: Yeah. No doubt, no doubt. All right, well, let’s let’s dive into safe books. Can you start by giving us sort of the broad strokes of what financial data governance is and why it’s crucial for enterprises. Yeah.

Ahikam Kaufman: So financial data governance is actually I’d like to think it’s kind of a term we coined, which is cool because if you go on Google and search for financial data governance, I’d like to think we’re the first UNsponsored result. And actually that’s how the Google I defines the term. But I think it’s very important people do that, but they don’t maybe use that term. The idea is that when you’re like a CFO corporate controller, you have a responsibility for the integrity and accuracy of your financial data. And today, unlike before your financial data, your financial data infrastructure is comprised of many, many systems who participates in every business process. You have to make sure that all the data in all these systems is reconciled and is accurate. It’s captured in the right time, in the right currency, in the right amount. And, you know, without doing that, basically everything else you’re doing, corporate finance potentially could be wrong. The other thing is that we have to keep in mind that financial data is not just data. It’s about money. So if you have inaccuracies or mistakes or errors, it could lead to leaving money on the table or having financial leakages. So you have to do that. Actually when you are a public company, it’s a legal requirement. And basically we identified a huge gap between finance people who wants to make sure the financial data is correct.

Ahikam Kaufman: But in today’s world, you have really to be like a data expert to do that. And what we’re doing with bridge. We’re bridging between the data expertise and the financial expertise and created the platform which helps us in ordinary finance person. We don’t need to have like a technology degree or engineering degree to have full visibility into what we call the end to end financial transaction monitoring. So we help you make sure that all your data and all your transactions across the various systems, it’s all captured correctly. The data is accurate. And, you know, not only that, we also help you produce the to substantiate it and document it, because a lot of the work that finance people needs to do, once they look into data and validate it and reconcile it, is they have to also document it and then really using AI and other capabilities in order to actually replace also that role. So leaving you with way more time on your hands to investigate issues or do other things as opposed to do a lot of data crunching and fetching data from different sources and putting it on spreadsheets and doing all of that.

Kevin Rosenquist: What do you find are some of the most common challenges that enterprises face when it comes to managing that financial data?

Ahikam Kaufman: I think it depends at what level. It’s a great question. I think some of the challenges are that different people have different knowledge. So when you want to put together a single picture, you have to bring a lot of people and they all have to do manual work. I think some of the challenges are always around the fact when when you have a business which scales, then you need to put more bodies on the problems and they just need to struggle. If you think about a company who processes, we have like customers who processes like let’s say 2 or 3 million transactions a month. How do you reconcile that? How do you get your arms around that without any automation? So the way people do it today, they just download data into spreadsheets and try to reconcile it, or just make sure that the high level is correct. What happens if like an API gets, you know, screwed or whatever and all of a sudden, you know, a portion of the business is captured in the wrong timing, in the wrong currency or whatever. How can you even identify all of that? So I think a lot of the challenges are associated with the disparity of the systems that today you have to manage and control the data in these systems.

Ahikam Kaufman: The fact that growing businesses, you have a lot of scale and you need to manage that scale. And also, I think you don’t have good solutions today to do all of that before. So it’s like reconciling data across systems. It’s something that currently is not solved. And finance teams are always living under tight schedules because you can’t close the demands halfway through the month. So you have to wait till the end of the month. But once the end of the month comes, you have to release the numbers really fast, or end of quarter or end of year. And if you’re a public company of other schedules like the tax return schedule, all of that. So you’re always under a time structure. You pressure yourself between a rock and a hard place. And the question is, how do we make that work? Be super efficient? So by the time all the data is there, the data is accurate and validated. And that’s what we’re doing because we’re doing it in real time. That’s challenges they have.

Kevin Rosenquist: Yeah. That’s really that’s really cool. And you know, can you kind of elaborate on how you utilize artificial intelligence to ensure that data integrity and how your platform sort of monitors and validates? Yeah.

Ahikam Kaufman: Um, let me use some examples. So we are a technology company first and foremost, and we connect to your enterprise systems and we bring all the data we’re using, I think it’s kind of a unique new graph technology to align all the transactions and create a single audit trail for every transaction across all the systems. So we know how to identify starting even from a document. So let’s say you have a purchase order which is captured in your Salesforce in your CRM, which is then sent into a billing system, which is then maybe sent to a payment gateway, which is then sent to your ERP. And we know how to mesh all these transactions and create a single graph. And by checking the graph, each transaction on the graph across all the systems, we can know which transactions looks okay and which transactions do not look okay because something doesn’t fit. And we identify that and we document that. So this is one technology that we use. Another AI powered technology is the ability to actually understand why there are fluctuations between orders. For example, let’s say the numbers are accurate, but we see that the balance really fluctuates versus last month. Then we we understand whether that fluctuation is normal or abnormal. So we don’t only understand the integrity of the transaction, we also understand the reasonableness of the numbers and whether they fluctuate normally or not normally. And then we run across all of that data and again a lot of people allow the finance team to immediately identify things they should be looking at in real time, as opposed to, as we said before, wait until the close and have like maybe looking at the numbers and pointing at anomalies every identify every time. It’s almost like a cyber like approach to how you run the books and how you run the financial data. And I’d like to think that financial data is as sensitive, if not more than as as like cyber.

Kevin Rosenquist: Yeah. Okay. You know, I obviously is opening doors for a lot of people and allowing for all this real time stuff to happen, which is super, super cool. When, when did you sort of realize I was going to be kind of like this big, monumental shift in how we do things from a technological standpoint? Was there a moment when you were like, whoa, this is going to be big? Like, we need to get on this.

Ahikam Kaufman: I’ll tell you this, and I’ll be honest, I was fortunate enough to sell a company to Intuit ten years ago, and I spent, uh, 5 or 6 years at Intuit, and Intuit invested a lot of effort in exploring AI and really recruiting tens, if not hundreds of people in that domain. But I’d like to think that the epiphany moment for me was OpenAI, which was kind of exposed in a became accessible for the public, just like a month before we started the company end of 2022. And then all of us could witness. But that’s not what we were using in our work. But that definitely gave a different sense and scale of what you could do with AI. And I’d like to think that a lot of the AI capabilities are becoming more and more commoditized today. But the secret sauce and the idea is how to use that to solve a very specific problem in a specific area. And that’s what we’re doing. One of the things I would mention is today finance teams and CFOs, one of the challenges with AI, specifically in finance, you can’t as a public company, you can’t take, let’s say OpenAI has all the capabilities around analyzing data.

Ahikam Kaufman: You can’t just take your data and put it in a public domain and analyze it. So one of the things we’ve done is that all of our solutions around all of our technology is proprietary. So when we use AI powered technology, and I would admit it’s not just about AI, but when we use AI powered technology to analyze something or create something, it’s all proprietary. So we don’t take the data out. We are it’s interesting. It’s the questions that came from one of our customers. And they say, when you process our data, you actually process our customers data. Because one of the things we solve for is order to cash. Order to cash is how you manage the business data that comes from your customers, right? Our customers said they’re not allowing us to use AI when processing the documentation externally, but we’re not external when we’re integrated to your system. And we have like our own platform. All the AI we’re using is proprietary, which allows our customers to process data, their data using our technology because we’re not using any external resources.

Kevin Rosenquist: So there’s not yeah, you’re not capturing any data yourself. It’s all just it’s all you know. So basically is it like you.

Ahikam Kaufman: Integrate sending the data? I’m not sending the data outside of our like stack.

Kevin Rosenquist: Right.

Ahikam Kaufman: So all the AI we have on the AI engine, all the analysis, whatever we do, it’s all proprietary.

Kevin Rosenquist: Got it. Yeah. Well that’s good. That’s good for peace of mind and and and obviously security compliance. That’s another thing that’s such a big part of this especially in the financial world. You know, I’ve talked to people about this before on the show. Like how is it hard to balance that compliance and the security, especially with regulatory standards changing or even like not being there fully in the US and like there’s a lot of different moving parts. How do you balance that with innovation?

Ahikam Kaufman: I’ll tell you this. I think you’re touching a great point. I think for us, the number value, number one value we had from day one was security first before a product. If we have a set of things we need to do, the number one priority would always be to work on security before features, before innovation, before anything else. I’d like to think that we have a very high level of security. We have Swiss certifications. The thing is that I’d like to think that, you know, for the first customers, you try to find if your pain is bigger than your exposure, if your pain is so big, then you would be willing to take the extra mile and hopefully trust a company like us to help you, because you have to think, obviously, again, cyber risks and exposures should be top of mind. However, the actual compliance, you know, we’re not offering something which is nice to have. Financial compliance is not less important if not more. And what happens today, especially in companies that experience scale and all of that, you just can’t get your arms around all the data in order to generate that financial compliance, to generate that level of accuracy, to generate that level of real time remediation of issues and things and monitoring and all of that. And you have to be able to use resources like save books to do that. So what hopefully is working for us is the fact that while there was always a cyber and data exposure, the pain we’re trying to solve is so big that you can convince people to go the extra mile and use a service like us. You have to.

Kevin Rosenquist: You have to. Yeah, yeah.

Ahikam Kaufman: But most of our data is is on the cloud, right? Even for company, when they use an ERP, it’s a cloud based ERP. When they use CRM, all the data is on the cloud. It’s it’s you can go back but I think compliance pain points are so big that, uh, you know, hopefully convincing people to, to use a service like ours.

Kevin Rosenquist: Looking ahead, what do you see as the next sort of frontier for safe books? Is there something obviously, that you can talk about that you guys are kind of heading towards in the near future.

Ahikam Kaufman: I think for us it’s more like our solution is a combination of the platform we develop, plus being able to solve customer problems. We do see once you become a trusted advisor, even as a product company, you become a trusted advisor. We are capable of developing kind of unique solutions to our customers. So they would come to you with a lot of pain points where you can solve, you solve for them for. So for us, it’s all like we’re all focused on expanding, expanding our reach, our coverage of the problems we can solve in the customer. And our platform allows us to easily customize and accommodate our infrastructure to the companies, to the customer specific business or use cases. That’s kind of how we see the near future. It’s more like expanding our footprint within the customer, from the usual suspects to more things that he can monitor using all using our platform.

Kevin Rosenquist: Things obviously are moving fast? That’s not a hot take, everybody. Everybody knows that for anyone you know who might be listening, who’s who’s interested in becoming a founder, becoming an entrepreneur in the fintech space over the next year or so, what kind of advice would you give them and how to approach it?

Ahikam Kaufman: I’ll tell you this I’ve not only been an entrepreneur several times, I’ve also been an investor. I invested in probably close to 50 companies, and I would say there’s not enough you can do. On being able to validate and substantiate the problem you want to solve. I see, I see a lot of time. I run into cases where people are getting excited about technology they develop or a problem they think people have, but there could be other solutions. So focusing on what problem you want to solve and why, whatever you want to create can solve that problem in the best way possible. That’s something that you can’t over. You know, it’s always the number one thing for Unsinkable, foundered. So really being able to identify a use case and make sure that use case is repetitive or a problem or a pain, and that pain is repetitive enough and you have the best skills and the best kind of team to solve that pain. That’s the thing I think you should be really looking at when you’re like an early stage entrepreneur. The other thing is that you can’t underestimate the quality of the team. So being able to choose the right people for that when they cruise with you, whether it’s your partners or co-founders or team members, it’s like, you know, I can tell you that a lot of times you can find this great engineer, but he doesn’t have the right culture fit. It’s always also a great balance between talent and can you work with them really, really well? And can they really adjust into kind of like the culture you want to build?

Kevin Rosenquist: Yeah, I mean, it’s a good point because everyone talks about, oh, you need a good team, you need a good team. But it’s not just the knowledge, it’s not just the technical ability. There’s also that cultural fit. And I would imagine there’s probably a mindset you need that for a startup that may be different than you need for an established company. Is that fair from your employees, from your team members? They have to have a certain spirit about them. With a startup that may be different from a company that’s been around for ten years.

Ahikam Kaufman: Yeah, totally. I would say qualifications like resilience, being able to be independent. Right. You have access to a lot of resources now you have OpenAI. You don’t need to go to your boss with every problem having resilience, being able to cope with demanding customers, hardworking. It’s all about the time you dedicate. So I think personally what we got, the conclusion we got into is that we any day of the year, we would prefer people who really wants to work hard and are resilient, and maybe they have 20% less knowledge than people who are super knowledgeable, but they’re willing to work like limited number of hours. Their resiliency is kind of, uh, compromised and they, you know, sometimes things can break them. So it’s almost like I think now you have new titans, like founding team members or like things like that for your core team. We told our core team when we hired our core team, you know, all of our all of our including the founders, all of our emails are going to be first name at the company. So it’s not just like a privilege of the founders, all the core team members. And we try to preserve this unique sense of the core team because,that’s the team you want to have when you start a new venture.

Kevin Rosenquist: No doubt, no doubt. Well, well, Ahikam , thank you so much for being here. Really appreciate your time and all your insights.

Ahikam Kaufman: Thank you so much for having me.