In this episode of The Future Of, Dr. Michael Housman, CEO and Founder of AI-ccelerator, and Fernando Luege, Chief Technology Officer at Grupo Financiero Base, join host Jeff Dance to discuss the future of AI in FinTech. They explore the FinTech evolution in the new AI-driven era, how generative AI unlocks new horizons in FinTech innovation, and how FinTech’s development enhances human potential.

Fernando Luege: GenAI is available to a broader and larger set of users in more verticals inside of the same institution. So it can help to increase productivity from a coding perspective while you’re generating new technology, but also for generating better interfaces and products and accelerating almost every single operational aspect of, in this case, a financial institution.

Michael Housman: I think no one’s talking about synthetic data, and it’s going to be a real thing in the next three to five years. And it’s going to totally loosen up our stranglehold on data. And that’s going to enable all sorts of experimentation.

Jeff Dance: Welcome to The Future Of, a podcast by Fresh Consulting, where we discuss and learn about The Future Of different industries, markets, and technology verticals. Together, we’ll chat with leaders and experts in the field and discuss how we can shape the future human experience. I’m your host, Jeff Dance. In this episode of The Future Of, we’re talking about The Future Of AI and The Future Of fintech, and how those two come together in the future. Today, we’re joined by Dr. Michael Housman, a technologist, data scientist, and AI expert with a specialization in fintech, and Fernando Luege, an innovative CTO whose career has been focused on building fintech software and working with banks and fintech companies. Just to go a little deeper, Michael spent the last 15 years leading technology teams. His research has been published in peer-reviewed journals. He’s presented at conferences and profiled in media outlets such as The New York Times, Wall Street Journal, and The Economist, to name a few. He’s also a faculty member of Ernst & Young Tech University and Singularity University, and the founder of AI Accelerator, which specializes in AI education, consulting, and adoption. Grateful to have you here with us, Mike.

Michael Housman: Thanks, Jeff. Glad to be here.

Jeff Dance: And Fernando. Fernando has built an extensive career as both a founder and a CTO in the technology space, pioneering Atomic Labs, who works with over 50% of Mexican banks, in addition to his work as CTO at Grupo Financiero Banorte, or Banco Base, and also as the CTO of Banco. And he was also the CEO and CTO of a data analysis company, Andore. So he has a lot of experience in the financial space, also with fintech. Fernando, grateful to have you here with us.

Fernando Luege: Thanks, Jeff. I’m happy to be here.

Jeff Dance: If you guys want to share any more insights, what was your experience? Your journey kind of getting into fintech? How did you guys land here? Mike, if I can start with you.

Michael Housman: It’s been an unusual journey. I started as a data scientist for a company called Evolve that did HR technology. Bear with me. There was evolution. We were doing hiring. It’s a similar challenge, which is making good decisions using algorithms, in our case, to hire people. And there’s sensitivity vis-a-vis the EEOC about making sure that you’re not behaving in an unethical way. And so from there, it was actually just a hop, skip, and a jump to a company called Doma, where I helped build out their data science team. And we were focused on title insurance. I moved on to a company called Point Predictive, and we were doing fraud detection. I’ve been doing work in consumer and small business loans, advising companies as they do payday loans. So it’s funny how I never really anticipated fintech was where I would land, or at least where I’d spend a lot of time, but it just kind of evolved that way. And it’s a really fascinating space with, frankly, a lot of technology and AI.

Jeff Dance: Thanks, Mike. Fernando?

Fernando Luege: In similar ways I start my career on data building graph-based algorithms to correlate data to correlate information. To profile and enrich user date, to create better product after that. I participate a bit on the marketing side, trying to understand and measure the impact of marketing campaigns and product launching for the financial space in social media. And then, you know, everything left to the next step, where we fundamentally work with Bank of all creating one of the first fully digital branch list, Bank offerings in Mexico. So it was similar fashion anf then from there we build career fundamentally working on the back end. And kind of in the critical or mission-critical systems space on the financial environment.

Jeff Dance: It dawned on me as we were kind of contemplating this whole session, why is AI such a big deal for the future of the financial space and fintech? And it was like, well, there’s so much data. There’s so much data there to analyze or to build algorithms around or put artificial intelligence on top of. It’s such a ripe space for having so much transformation in the future. And I know you guys have been pioneers sort of already in this space, and so really excited to get your insights as we think about the future. One more question about you two. What do you do for fun?

Michael Housman: Travel a lot for work because I’m speaking all over the world around AI. Also for fun, I was just in Dubai a couple of days ago. I’m headed to London tomorrow. And then I’m a big CrossFitter and kind of a workout junkie. So I’m not on my laptop. I’m usually throwing some barbells around.

Fernando Luege: On my side, I would say that I’m a professional fixer. So I have four kids. So the rate of destruction overpasses by far. My capacity of fixing things. I’ve been focused on leading those four kids on their lives. So that is what I do for fun.

Jeff Dance: You also mentioned something about a car. Aren’t you working on a car as well?

Fernando Luege: That is right. So I try to be as close as possible to technology of all sorts. So I’m just finishing a car from the ground up. So every single screw from the engine to every single wire, all done by my family and myself. So yeah, I’m fairly deep into mechanics and some of those things, you know.

Jeff Dance: That’s amazing. Good to have you guys here. To get started, fintech can be a broad word. It’s like the word innovation or love. They can mean lots of different things. But give us the high level for those users that aren’t deep into the space yet. What is fintech? And where are we today as we think about AI and fintech? Mike, if we can start with you, then I’ll go to Fernando.

Michael Housman: It’s a broad term. So broadly, it could be any element of technology that’s touching banks, insurance companies, like any financial services institutions. I think of a couple different buckets as being the broad categories, right? You have these payment processors, kind of Plaid, Stripe, Venmo, Zelle-type companies. You have companies that are doing lending, consumer, small business, using a lot of sophisticated data in a kind of more modern way. InsurTech companies, I still roll that into FinTech, making better decisions about how to risk adjust and price insurance products. And then, you know, I mentioned earlier, you could even roll some like crypto banks in that, but I tend to exclude them because I’m not a crypto guy and it feels like a different animal. There are obviously a lot of little niches in between those, but to me, those are kind of the big categories. And yeah, I think where we are is the high level is like, it was a white hot space about three, four years ago where anything that was called a FinTech was getting funded. And I think it’s cooled a little bit since then. Some companies have had a little bit of a reckoning. And I think all startups that SPACed got kicked in the teeth for a variety of reasons. So it’s cooled a little bit, but I think AI is putting it in a position to really heat up again, right? Anything that touches data, Jeff, to your point, I think is going to have a kind of reawakening as we see how these algorithms work their way through organizations.

Jeff Dance: Thank you. Fernando?

Michael Housman: Absolutely, yeah. And then there’s this other aspect, and following the idea of the cool-down that we’re seeing on the market, I think we saw the first round of low-hanging fruit and early players in different verticals. So you have players in payment gateways or payment channels. Then you have another few sets on fraud prevention, lending, and all the different verticals. That it was fundamentally like the digitalization of existing products or existing offerings. And nowadays, we’re entering to a more mature adoption or phase where you will start to see some mergers, where these technologies start to combine and also start to be implemented by more, let’s say, conventional players. So this will open up, from my perspective, a fundamentally new age on finances, where we will start seeing truly new and more innovative offerings.

Jeff Dance: In addition to the conversation we had with our guests on today’s episode, we asked another expert to provide their insights on the future.

Daniele Grassi: Daniele Grassi, CEO and co-founder of Axyon AI. We aim to transform investment management throughout AI. For as long as I can remember, technology and finance have been huge interests of mine. I studied software engineering and I set up a software company while at university. And in 2014, I recognized something, sort of a pivotal moment for AI and finance, and shifted focus and brought my two passions together, co-founding Axion AI. Axion AI empowers investment managers with AI-powered asset rankings, model strategies, and active indexes. And we harness cutting-edge AI techniques to provide predictive insights for asset management, analyzing alpha generation and operational efficiencies. AI technology in the investment sector is surely making substantial progress, but can still be considered in its early stages. We are seeing an increased adoption of AI for predictive analytics, risk management and operational automation. Yet, the full potential of AI in reshaping investment strategies and decision-making processes is just beginning to be tapped. Challenges such as data quality, interpretability and regulatory compliance still remain, but advancements in AI techniques and increased industry uptake really signal a promising trajectory.

Jeff Dance: One of the things I was thinking about if data is sort of the ground in the financial space, there’s so much data and there’s so many different offerings that can come together through. I read what 25,000 different fintech startups that are in play today. And maybe, Mike, to your point, we’ll see some softening given the fact that startups have been all kind of kicked in the teeth a little bit with the rising interest rates and the lending situation from investors. But I think about the DIKW, General Framework of Data Information, Knowledge, and Wisdom. And it seems like we’ve been in the data information and maybe doing little pieces of knowledge here and there, but we haven’t got to the sophistication of non-humans actually delivering a lot of that knowledge and wisdom forward. And I’m excited to see where the space goes. As we think about the biggest players, there’s a lot of startups and then also bigger financial institutions just taking a much more serious focus in this area. Who are some of the bigger players that come to mind? As we think about AI and fintech, independent of just financial institutions. And I guess some financial institutions could be big players in themselves, could be leaders in themselves. But do any companies come to mind? Mike, start with you.

Michael Housman: On the payment side, it’s the, you know, Stripe, I think is kind of the biggest name there. You have the Flads, Venmo, you know, which is part of PayPal now, Cash App. So there’s them. For me, I’m really excited. I think that on the lending side, consumer and business, you have Brex, SoFi, Kabbage, like a lot of companies that have been really innovative about who to lend to, how much, right, and how to underwrite those things. And then I think I mentioned there’s some outliers there like Carta, right, which I would call a fintech just because they’re dabbling in that secondary option market. I think it’s a really interesting story behind them. So I think those are the biggest ones. And like I said, they’ve kind of had their meteoric rise. They’ve come back to earth. I don’t think they’re going anywhere anytime soon, but it’s fascinating. I’ll share a little bit later, like the stories of how they got started is really interesting.

Jeff Dance: Fernando, anything else to add there?

Fernando Luege: Absolutely. I think aside of these big names, there are also interesting players coming in as more enablers and backend players. You have Lendio, for example, where they’re trying to provide an operating system for lending and increasing availability of more technology and more sophisticated solutions to any existing player. You have new age core banking systems where you have a better architecture and a more service offering from a marketplace perspective. And then you have big technology players like OpenAI or Google integrating their solutions to the financial space and providing very well-trained models and making them accessible for fundamentally everyone. So you will start to see as well more raw models or technology being integrated directly to the pipeline and to the technology framework of the financial institutions and not only services being provided by…

Jeff Dance: Would you guys put Robinhood in the mix as like FinTech player?

Michael Housman: Yeah, I would say, again, they’re kind of in their own little category and you have a number of, you know, I didn’t even mention the robo-advisor investor technologies. Robin’s a little different in that it’s more like do-it-yourself premium platform. But yeah, I would definitely throw them in there and obviously they’re massive.

Jeff Dance: Interesting to watch how they’re innovating on the consumer side for sure. Fernando, question for you. Citi came out with a report on unleashing AI and the AI arms race and, you know, talked specifically about the financial industry. And one of the things they said was that they thought generative AI would have the most impact on, out of all the industries outside of tech, that generative AI would have the most impact on the financial and FinTech industry. And I’m curious if you have any insights to why that is. Why would generative AI have the most impact on this particular industry?

Fernando Luege: I think generative AI, differently from the analytical side of AI, generative AI is available to a broader and larger set of users in more verticals inside of the same institution. So it can help to increase productivity from a coding perspective while you’re generating new technology, but also for generating better interfaces and products and accelerating almost every single operational aspect of, in this case, a financial institution. So that’s a fundamental difference among more heavy technological solutions where data and the crunching of numbers and data becomes more important. In these other verticals, as you have a larger user set, also you have a much larger market and a much larger impact, a more broader set of goals that you can impact with this type of technologies. And also there’s the accelerated adoption rate that we’re seeing. I mean, the release of better trained, and more precise and particularly oriented models is just astonishing. I mean, it’s very close to a few of the other very big leaps in technology that we’ve seen in the past.

Jeff Dance: Industry-oriented, data-oriented models, you know, specific to the financial industry that companies and or startups could leverage really quick for new consumer value.

Fernando Luege: Exactly. Let’s analyze or let’s mention just as an example, the speed of launching or releasing new models for the NLP approaches, OpenAI has in these last six months. So they jumped from, you know, simple AI-constructed images to video-generated marketing campaigns within, I don’t know, six months. That is just incredible.

Jeff Dance: And so if you couple that with the vast amount of data that you can embody or specific body of knowledge and data, you know, that seems to be a space that’s ripe for all the generative experiences you can put on top of that.

Fernando Luege: Exactly. Following that line, just to finish up, we’ve been close to personalized advertising for a while, but it was a set of predefined ads delivered to predefined user groups. And nowadays, we will start seeing personalized advertising for each individual. And then you will start to see personalized product offerings for each individual. And that is in a different scale.

Jeff Dance: You can generate it on the fly. You don’t need all of Google’s data anymore because you can collectively analyze it and then generate it on the fly. Exactly. Interesting. Mike, you have some thoughts.

Michael Housman: So I’ll give you two examples of how I think generative AI and especially LLMs are going to totally change the game. Number one is no one thinks about this, but synthetic data, which I’m calling right now, I think it’s a huge opportunity. I did fraud detection for a number of years. And what that means is you go to banks, you say, listen, I need highly sensitive social security numbers, consumer data, fraud data. You need to share that with me. And they immediately clam up. And then you come up with all these crazy ways to encrypt the data and to get them comfortable with the notion of sharing it because we pull it across multiple banks. Like, what if I can make a copy of your data set and the copy I get has no personal identifiers, but it looks like real data and it acts like real data and smells like real data. So for me, I think no one’s talking about synthetic data and it’s going to be a real thing in the next three to five years. And it’s going to totally kind of loosen up our stranglehold on data. And that’s going to enable all sorts of experimentation. So that’s one. And that’s a real clear implication of Gen AI. And number two is this is more around large language models, but the ability to parse all this data to then get to like nuggets of information is really valuable. And what I mean by that is I’ll tell the story. The founding of Brex is really interesting. So I love to share this story, which is the founders were starting an entirely different startup. They applied for a credit card. They got denied. I think it was by American Express. And it’s because startups don’t look good, very credit worthy because they have no revenues. And they have no, absolutely. You know what I mean? There’s no credit history. And so they got denied and they thought this is insane. We’re going to start our own company. And it’s obviously done well. And my point is old institutions don’t know how to risk adjust properly and to use all the information that’s available. And with LLMs, there’s the ability. I do demos when I go on stage and I feed an LLM the King James Bible. It eats it up in a second. And then I can ask questions about it. And it’s able to extract information that no human being could do. They’d have to read through it. So my point is like all this unstructured data that’s totally untapped by FinTechs. They just not using it all. They’re going to be able to use it. And a friend in reinsurance, he does reinsurance work. And he says 80 to 90% of the applications are unstructured. Almost all unstructured data. 80 to 90% is not even touched. It’s not even read. So what if you could build models that can risk adjust and premium adjust based on all this information that wasn’t being used? Like, I think it’s going to be a game changer for the ability of banks and lenders to kind of make good credit and lending decisions.

Jeff Dance: I want to build up that just for a second. I read that banks like HSBC are already incorporating AI heavily and they have nearly a thousand applications of AI. This is just HSBC. So that seems like they’re far along. As we think about the industry, you mentioned all the synthetic data, you know, customized LLMs, like all these different applications where we can both analyze these data sets and be much quicker in our personalization or our capabilities. Like, are we far along? I know AI has gone through waves and we’re in this recent sort of generative AI wave, but like, how far along are we? Are we just starting or are we like halfway there? What’s your perspective, Mike, on the penetration of AI technology in fintech today?

Michael Housman: I think it’s actually early in the journey. My experience is, especially with GenAI, what everyone’s doing right now is they’re looking across the organization. They’re saying, where are all our knowledge workers, right? Because at their core, these technologies scale intelligence, right? They enhance and sometimes replace knowledge workers. So they’re saying, who’s in our organization? What do they spend their time doing? And can we supplement them with Gen AI technology so that they get their time back so they can be doing more value add stuff? And I think that’s going to impact FinTech the same way it does any other type of technology. What I don’t see them doing, and I think Fernando kind of addressed this really nicely, is they’re not thinking about how is this going to upend the model of what I do? Like imagine a credit or a lending product that’s personalized, like hyper personalized. It’s a single person product, right? Based on your unique needs and your footprint digitally, that I think is going to completely upend the industry. I don’t think banks are going to understand how to deal with that, right? That’s just they’re not equipped to do that. So for me, I think we’re somewhere along the journey because they’re looking at these technologies like chatbots and they’re looking how to automate their CRM. They’re trying to be, they’re implementing all those kind of value add SaaS tools to be smarter. But what I don’t see people doing and where I think we’re going to see a lot of change in the coming years is like, how is banking or insurance or any of these industries going to be disrupted? And like, how are these offers going to fundamentally change the relationship we have with our financial institutions? It’s exciting. But if you talk to banks, which I do on a pretty regular. Basis, I mean, scares the bejesus out of them, right? The notion of the bank might kind of go away. You might just have an individual AI lender.

Jeff Dance: Fascinating. Fernando, what are your thoughts on that maturity, but also this perspective he has on banks?

Fernando Luege: Yeah, so totally agree on that. We are in the very, very initial phases of AI being adopted in any vertical, but in particular in finances and banking. Differently from other waves of AI, I think right now we’re in a very, very different position where this time will be permanent. So the solutions that we are seeing being created are going to be the fundamental base for a lot of the innovation in the upcoming years. And then taking a few of the ideas that Mike was mentioning a second ago, we’re in the start of a cultural change from every single perspective. Not only inside of the different organizations, but also from a user perspective. And I think as the time goes by and these solutions are more profoundly integrated in every single thing we do, the products offered by us, by these different institutions incorporating AI, will start to accelerating and maturing at the same required rate. Because right now we’re seeing adoption of solutions being presented by the tech companies to… The banks in order to solve particular problems. But we will start seeing a different approach in the near future where the solution itself is being changed by AI and in constant basis. And I think that will fundamentally disrupt the entire industry.

Jeff Dance: I think that kind of speaks to what you were saying, Mike, that like there’s a disruption that could happen.

Michael Housman: Yeah. Just to cap it off, it’s like, you know, we saw the Internet Revolution in 93. We saw social media in 2003. This is the third digital disruption in the same way that mobile and internet, like you never would have thought cabs would be upended, right? That’s an industry that’s just completely been kind of changed. I think we’re just starting to see now like, okay, what are the industries that are going to be turned upside down? And it’s like, it’s exciting for new people, for entrants. It’s scary for incumbents. We’re still very early in that process. We haven’t even really started.

Jeff Dance: That brings us neatly to the future. Let’s talk a little bit more about the future. So if we jump ahead 10 years, 20 years, what do you think things will look like? What kind of things will change? And I know that’s a broad question, but I’m interested in some of your predictions. Mike, start with you and then let’s go to Fernando.

Michael Housman: Yeah, I mean, I think we’re going to see a lot of different data streams being used. Like I think credit and lending decisions right now are still dominated by kind of structured data. And I think, like I said earlier, it’s going to be opened up to a lot of unstructured data. And that’s scary because it’s like that data might come from the web and it might come from social media and it come from that footprint that we leave behind. But I think that’s the first thing is like there’s going to be so much more data available to be making these decisions. I spent years in fraud detection. It’s going to get scary. We all heard a couple of weeks ago, someone perpetrated a $35 million fraud by deep faking a Zoom conference call in which the CFO said, hey, we need to wire this money to this account. And folks were just doing their jobs like that’s just the beginning. These deep fake technologies are going to get very widespread, very accessible, very easy for kind of anyone to adopt. And the story of fraud is always cat and mouse, cops and robbers. It’s always fraudsters come up with some really clever way to do it. And then folks from my team doing these sort of forensic work, like quickly find it and then plug the hole and it just iterates ad nauseum forever. So that scares me a little bit. Friend of mine got a call from her son saying, hey, mom, I’m in jail. Wired me some money. Turns out it’s easy to spoof your voice. Jeff, I could take your voice and come up with a very convincing call that would convince your mother that it was you.

Jeff Dance: So. How do you know it’s even me? How do you know that I’m not just an AI that I did an autopilot thing this morning to take this whole podcast on?

Michael Housman: Totally. No one knows. It’s possible I’m interacting with an AI Jeff.

Jeff Dance: Yes, it’s possible. Actually, this very recording is going to be part of our own future AI. We’re putting something out there. I’m sorry, but it’s going to be part of your own personal LLM that represents you in the future.

Michael Housman: Oh man, it’s scary. You can use it for whatever you want. I’m fine. But yeah, I have a friend who created a podcast. You listen to this podcast and then he revealed to everyone, oh, that was completely generated by ChatGPT and some tools that can then synthesize voice. So I always scare people with these things, but I think it’s good. We’re aware of like the implications for fraud is pretty significant. On the other hand, on the more upbeat side, I think it’s a good opportunity for us to be smarter about how we extend credit and lending, right? In the same way, I love these stories. Like the Brex founders, they were denied a credit card. So they started a company and ate American express lunch for them. Same with like, SoFi, they were smart enough to realize that like, Hey, if you went to a good school, you know, you went to an Ivy League and you graduated with a good GPA, you’re probably pretty credit worthy. And so they started lending to those folks and a lot of large banks ignored them because they’re students and they didn’t think, Hey, there’s a risk. So those folks deserved credit, right? They deserved to be able to be loaned to. So for me, it’s exciting because like, there are lots of pockets of people that are underbanked underserved populations, and they deserve to be given access to this system. And I think there’s a lot of AI that’s going to help that happen.

Jeff Dance: Fernando, what are your thoughts on the future?

Fernando Luege: Yeah, I mean, differently from other industries where being the leader, implementing AI in something particular can develop these winner takes all. In finances, I think it changes a little bit the approach where what you want to achieve is to serve as many people possible to achieve their goals. Because financial institutions are there to fulfill another goal, a payment gateway doesn’t exist just because it’s interesting to send money across. Or a lending institution doesn’t exist just because people want to have a little bit more money. Everything is related to a milestone. So the concept of embedded finances, I think it’s the it’s going to be key in the midterm future where you will start having solutions that enable you to perform something and to get something, some objective done without noticing them fundamentally. And I think AI, it’s critical to be able to have and provide that seamless experience. So that will allow potentially people to achieve their goals without getting distracted by very technical financial conversations that perhaps, or in the majority of them, won’t be in their best interest or in their core capacity. I’m pretty excited. I think that we will be able to see financial institutions being able to maximize their customers’ value instead of just providing them some sort of services to be consumed.

Jeff Dance: Thanks for that perspective on the consumer.

Daniele Grassi: The world of fintech will likely undergo really big changes due to AI and machine learning advancements. And I believe you can expect one, operational efficiency, because we will see drastically reduced manual processes in favor of automated AI-driven solutions. Two, we will see automation and personalization with really enhanced customer experience, with personalized financial advice and personalized services.

Jeff Dance: Fernando, you’re in an interesting position given that you’ve been a CTO at multiple banks. What do you tell banks as far as preparing for the future? Because given that there can be disruption, given that this will change the landscape, what would you tell banks to prepare?

Fernando Luege: This is a very, very interesting point in time because you have enough accessibility to technology to disrupt the industry, but also you have large enough institutions to try to compete. So what I would say to any bank is, one, they need to put a data strategy in order. They need to be able to convert themselves into data-driven organizations and deal with it not only from the technological part or perspective, but also from a cultural perspective where you will have every single decision being driven by data. And how you process that data and how you integrate that data into your decision-making process, that’s where AI will play a significant role. Secondly, you will need to modify entirely how you see customers. They will end being like these set of entities where you can offer something and be consumed. You will need to start thinking on them as individuals that will require personalized products and solutions. And taking a few of the comments that we did earlier, I think that’s what will drive as well some of these divisions between entities that will survive and other entities that will be simply, remove and distrupt.

Jeff Dance: Mike, switching gears just a little bit, as we think about the future, you had mentioned disruption of knowledge workers, thinking how knowledge workers will change. And there’s obviously a lot of knowledge workers in the financial space. As we think about the future and this trend of AI and automation, the augmentation, the decision-making, the knowledge that can be produced, what future does this leave for humans within the fintech industry? How does this change the workforce? How do people in the space think about how to adapt?

Michael Housman: Closely related to what Fernando was just talking about, which is, I think you’re going to end up with banks and financial institutions, insurance companies saying like, what are our people best equipped to do? Right? Like what is our value prop? Because there are small companies that are going to be able to kind of move faster. And, you know, we’re all using a lot of the same payment gateways. Like I’ll give you a specific example from my career. I helped build out the data science team for a company called Doma that kind of reinvented the way title insurance is done, which was very antiquated and slow going to County courthouse records, property being bought super small risk of any title issues, but manual searches and County courthouse records to pull this data. Doma said, listen, we’re going to automate every step of that process underwriting, but also we’re going to have our people leverage technology because they’re spending all their time sending out emails and digging through documents. And both of those can be automated. And so they basically set teams out to automate those processes. And frankly, a lot of the title examiners kind of freaked out and they were like, well, what is it that I’m going to do? And the answer was really easy, which is like, you’re going to build relationships. Like you’re going to go communicate with the customer, hold their hand. This is a complicated process. We want you on the front lines, really working closely with them. So they understand what’s happening. And when there is an issue, which does happen, you’re going to be the first on the phone. They just want communication. So I think that’s a good kind of analogy for where FinTechs are going to land, which is they’re going to realize that a lot of the time, the very automatable processing is going to be automated and they’re going to have to figure out what’s the value we provide. And in many cases, I think where they’re going to land is, oh, we have trust. We have relationships. We’re good at communicating. We’re going to double down on that stuff. And we’re not going to have our people parsing through spreadsheets or doing a lot of very, very kind of simple tasks or whatever. Let the humans do the things that humans do best.

Jeff Dance: Fernando, what are your thoughts on the topic?

Fernando Luege: Totally agree. And then there’s this other more operational aspect of the financial world where you have a lot of people analyzing and participating on the workflow of anything, like manually doing something. So the automation of that process is not very different of all the other transformation, industrial transformations that we’ve done and that we’ve seen in the past as humans. And in this case, you will end up, as Mike was mentioning, doing the stuff that humans do best. Also, from an operational perspective, instead of managing and governing the workflow, you will be supervising and training the workflow and providing valuable feedback all the time. So I think it’s very important that people don’t forget that at the end, we are a fundamental piece of all this process. And we’re not going to be just removed, but we will be enhanced. And I think that’s the fundamental on that line.

Daniele Grassi: Three, on the risk management perspective, we will see improved predictive models for assessing credit risk and detecting fraudulent activities, but also to assess market risks. And I believe that this will actually be a battleground between data privacy and accuracy. And four, quantum computing in finance is still a big if, but the potential integration of quantum computing could solve or help solving better complex financial models much faster than current technologies allow.

Jeff Dance: I think going back to the advent of the computer, I think everyone thought that humans were going to go away. The reality was work dramatically changed, right? Most of us became knowledge workers versus manual workers. As we think about this new frontier, I think work will dramatically change, right? Anything that can be automated will be automated. I think my hope is that the work that can be automated isn’t high-purpose work, right? And so if we can get into the trust, the communication, the relationships, the issue management, the higher order of human work, essentially what we do best, that would be better for those disrupted in the industry, much like we’ve had waves of disruption in the past. But I can’t help but think that there is just going to be a lot of automation in this space and that this will change a lot of jobs. And I almost, unlike other industries where it’s like, I think you can see AI more like a co-pilot and an assist. It seems like AI may take more of a central role in fintech. And that humans will be more of the assist, essentially, to make sure, like, you got to make sure you get this right. We’re going to be almost like training the AI. And I’m wondering if it’s going to go in reverse for some of the core stuff because fintech is so AI and data heavy. You know, because there is so much information at hand that, you know, maybe that will be a little bit more of an assist to make sure we get all that stuff right.

Fernando Luege: Let me add just a couple comments there. So, I mean, I see that every day. So sometimes the agent managing the relationship between a financial institution and the customer, those are business savvy people. I mean, they have a lot of experience. They’ve seen a very broad number of businesses of a very similar nature. But all the time is being used on collecting data to assess the risk and minimize the exposure of an institution. But if you have the capacity to automate that portion of the task, then you free up that agent to maximize customer value. So they can engage the customer with the same purpose, but now providing more value to the success of the business and not only to the minimization of the risk. And again, not forgetting that human beings are, we are extremely creative and also extremely adaptable. And those two principles will lead the future. In this case, as it’s been in the past.

Michael Housman: One more example of how consumers win, which I love, is payday loans. So think about it. Fernando is talking about how we’re going to result in less friction in this process. Well, there’s no more friction than waiting every two weeks to get paid, right? Why do I have to do that? It’s just the way we’ve done things. Well, you have all these tech companies that are issuing, they’ve gotten into payday loans, which is just a scummy business, right? With usurious rates. They basically use a kind of like pay what you think we deserve approach. That’s how they get around these, like the laws. And now the only question you have to answer is how do I know you work the hours that you work? Well, this device that I have, it follows me around and it tells you if I was at work, right? And it’s likely telling you if I was doing the job. And so the point is like those companies came in, use really clever data streams to then pay people instantaneously. It gives access to cash to people, frankly, that need it. And I think it’s also destroyed an industry that kind of needed to be disruptive. So I think it’s a great example of like, in the end, I think consumers are going to win. They’re going to get kind of more. Handholding faster transactions. They’re going to get better pricing for their, you know, their loans, their debt. So yeah, I’m just, I’m super excited. I think the consumers are going to win. I think FinTech is going to need to adapt, right? They’re going to have to kind of suffer the fate of the dinosaurs.

Jeff Dance: Such is the case, right, with the pace of change in companies that don’t quite keep up. Closing out with just a few more questions. What advancements in FinTech technology are you guys personally most excited for? You’re both kind of industry leaders. You guys have started a lot of initiatives around this. You’ve built teams. You’ve advised a lot of companies. What are some of the things you’re personally most excited for? Fernando, if we can start with you.

Fernando Luege: So KYC and all the, let’s say, your digital profile is extremely exciting because the impact it has is not only related to fintech, but as well in any other applicable authentication process. I’m really excited on the merge of biometrics with your digital footprint that is close to what Mike was talking about with the cell phone tracking and data streams, but as well with all your interest and consumption patterns, et cetera. So that junction of all your data streams to create your digital profile, I think it’s going to be extremely valuable to reduce fraud, but also to maximize value. The value you receive. And then payment gateways as well, I think, are on the verge of being transformed profoundly. We’re still working with extremely old infrastructure and following those legacy concepts and principles where we have the technology capacity to do instantaneous global transactions. I mean, we do have the technology. So I think the incorporation of AI on those processes and implementing them in solutions are going to be super exciting.

Michael Housman: Mike? I think the latter. I still wonder why I want to send a wire. Like, why do I have to wait days, plural? Why am I spending $15? Like, we have a digital age. Like, why is this stuff not instantaneous? With the caveat of, like, notwithstanding fraud risk and needing to make sure that there are risks involved. I still wonder to this day why it takes time for this money to be transmitted. I think that’s going to, as companies compete for that space, and it’s very competitive, I think that’s going to go away. I think the price is, it’s going to be very cheap, and it’s going to be painless, and it’s going to be instantaneous to send money. And I’m very excited about that, because we’ve all been spending, all of us have been paying fees for something that should be effectively costless in the digital age.

Fernando Luege: The other thing just to add, we haven’t talked about, but is how transformative is this on the regulatory side? Because right now we’re seeing financial solutions and institutions being bound where the boundaries are fundamentally created by legislation. But we are in the point where we will start seeing more global-oriented banks and global-oriented solutions where the regulatory framework will be required to evolve because of those potential solutions. So I’m pretty excited as well in that aspect in particular, because I think we’re in the point where, as Mike was saying, there is no justification to keep doing things as we’re doing it now.

Daniele Grassi: The most rewarding part of my job as CEO of Axyon AI is surely leading a team of talented individuals which are very passionate about leveraging AI to revolutionize the investment management sector and also seeing the tangible impact of our AI solutions on our client success. I’m very proud of the team’s ongoing dedication to making Accion AI a leader in the investment management space with really solid principles and trust. And it’s been this way since we founded the business in 2016 and it is just as strong today. I also believe that our job and the way we tackle the challenges of applying AI to investment management can be seen as a school of life. And as in life, you always have to be conscious that there are things that you control, which in our case is the scientific and technical process we employ to go from raw data to trained AI models. And things you do not control. Such as the market’s behavior. My belief is that establishing a solid process is the way to tilt odds in your favor. And as in life, being virtuous in this is what will lead you to success.

Jeff Dance: Another question I wanted to ask as we’re wrapping up here, the history of technology is it kind of has a life of its own. It evolves sometimes at a super fast pace, sometimes it’s slow, but sometimes country to country, we can’t control it essentially. And it’s wake over the last 20 years has been this massive uplift for humanity, but there’s also been the byproduct where it’s like people have been harmed or you have the bias or you have the judgment or you have the fact that we’re all glued to these little things in our pocket and it’s changed how we interact as human beings. Any thoughts about from an ethical perspective, how we try to get this right for the FinTech industry? Anything come to mind from a principle perspective? If we’re the innovators and the creators of the future, what are some principles? What are some things we need to think about so that we do the most good and the least harm?

Michael Housman: The first thing that comes to mind is really I spent years kind of working with like fair lending laws, right? So like you have, when you’re designing these algorithms, you have these kind of two conflicting objectives. One is I want to use data to kind of risk adjust the kind of pricing and to make sure that we’ve properly scored your credit worthiness, right? On the other hand, though, redlining is an issue, right? And you shouldn’t be unfairly biased against individuals in specific categories that don’t have access to credit, right? So that for me was always the challenge is to kind of use data to be at the sharp end of the spear, but at the same time, making sure that we weren’t discriminating against folks that, you know, frankly, those laws exist for a reason. And there’s no easy answer, right? It felt like, and I will say on top of which those laws, they exist for a reason, but they’re very vague and it’s really unclear what the line is. And I think that’s probably by design because they don’t want people to kind of skirt on the edge. It’s a challenge. It makes it challenging to like innovate and be on the kind of bleeding edge. But I think that’s where on one hand, I think folks will benefit and underbanked and underserved populations are going to benefit. On the other hand, I do worry that there’s a kind of cream skimming that’s going to occur where lenders and banks are going to try to subtly get better populations and, you know, folks that are more likely to pay loans and keep balances on their credit cards. And so that’s always the challenge. And that was when I was doing fraud detection. When I was doing consumer loans, small business loans, like you always have to be cognizant of that.

Jeff Dance: You definitely seen both sides, right? So it’s fun to get your thoughts as you think about the experience you’ve had.

Fernando Luege: Fernando? Now, on my side, one particular thing that I think we need to take into consideration is as industries incorporate financial solutions, you know, non-financial companies include finances or financial solutions in their products. We need to be able to keep competition head and available for everybody. It’s going to be fairly dangerous if we allow to your majority or majority players in certain industries to control those entire markets or those entire populations through financial instruments. Because in that way, then it happens what Mike was concerned with. That is, you won’t be able to provide fair access to financial solutions to everyone. So I think that’s going to be something important to take into consideration in the near future. And then the other thing is to be able to outweigh the access of AI from players that are trying to commit fraud, to outweigh the ability of the market to provide better solutions for the people that is well intended and that is truly trying to access that solution to create value and to create good. So we will need to get some balance on that point in order to be successful and integrating these solutions as a driving engine and not as a control tool.

Jeff Dance: Any last thoughts, guys? I’ve really appreciated your insights so far. Any last thoughts on the future before we wrap up?

Michael Housman: I always wonder when I’ve given talks, I come on stage and everyone thinks, oh, my God, the robots are going to take our jobs and they’re going to take our lives. Like I try not to leave on a kind of doom and gloom. I think at the end of the day, really, consumers are going to benefit unequivocally. I think there are things that we need to be concerned with in terms of inequality. That’s why those laws I mentioned exist. And yeah, I think hopefully, I hope and I really do believe that folks will get to do the parts of their job that are more fun. That like no one likes digging into an Excel spreadsheet. I’d rather engage with. Well, some people do. But like the point is, like, I’d rather focus on the parts of my job that require more critical thinking and the pieces that are less automatable and rote. And Fernando said this, and I think you agree, Jeff. It’s like there’s going to be a shakeup and that can be scary for large financial institutions. But I think it can also be healthy. Competition is, I think, is a good thing. And it’s going to force some players to really up their game and to realize that we can’t rest on our laurels. Just because our name. Is city or American Express or whatever it is, it doesn’t mean we can just sit back. Like we need to kind of innovate. We need to be on the bleeding edge. And I think that’s exciting.

Fernando Luege: And from my perspective, I totally second that comment. I think we are starting to see a brighter and better future where you will have better and more comprehensive products, but also funnier and more challenging jobs from an intellectual perspective in any financial institution. So it looks promising and excited to be part of it.

Jeff Dance: Thanks, Fernando. It’s my pleasure to have both of you guys on the show today. Really grateful for your knowledge, your perspectives, but also your heart. I feel that you guys are folks that care about doing good and using all your skills with tech and with people for making it happen. So grateful.

Fernando Luege: Likewise. Thanks, Jeff.

Michael Housman: Thank you.

Jeff Dance: The Future Of Podcasts is brought to you by Fresh Consulting Consulting. To find out more about how we pair design and technology together to shape the future, visit us at freshconsulting.com. Make sure to search for The Future Of in Apple Podcasts, Spotify, Google Podcasts, or anywhere else podcasts are found. Make sure to click subscribe so you don’t miss any of our future episodes. And on behalf of our team here at Fresh Consulting, thank you for listening.