Latest / The Payments Shed / Ep. 13 - The Future of AI in Banking with Rens Troost, Co-Founder & CTO of Rational Exponent @ Money 20/20 USA 2025

Transcript

Ep. 13 - The Future of AI in Banking with Rens Troost, Co-Founder & CTO of Rational Exponent @ Money 20/20 USA 2025 · The Payments Shed

• 0:01
  Welcome back to the Payment Shed podcast.
• 0:03
  Today we are joined by Rens Truce from Rational Exponent.
• 0:07
  Yep, Rens, please introduce yourself.
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  I'm Rens, Truce CTO and founder of Rational Exponent.
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  Our job is to provide prudence as a platform and to bring you
• 0:15
  the Bank of the future today, and we can talk about what that
• 0:18
  means. And everyone's talking obviously
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  about AI in particular. Where are you guys seeing
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  results with AI in your world? Well, a lot of people are using
• 0:26
  AI for fairly shallow use cases. People are using it for content
• 0:29
  generation. People are using it for vetting
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  marketing messages. We've gone to a more interesting
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  place. What we're trying to do is to
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  look at broken bureaucratic processes, which are the gating
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  systems at the heart of every bank, and make them a whole lot
• 0:41
  better. And the place where we're
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  starting is in second line of defense risk management, which
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  sounds like a mouthful, but it actually is what stops progress
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  from happening at most organizations.
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  And yet it is a critical function that must be performed.
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  And trust is obviously a big part of what we talk about in
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  payments and the regulation side of things that sits around that
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  kind of trust point. How do you guys, I guess look at
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  the compliance side of things with your platform?
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  Well, our platform automates the processes for both prudence and
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  compliance in banks. So it's actually right at the
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  heart of what we do. If you look at some of the
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  things that are going on in the industry right now, for
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  instance, revolutes, ongoing struggles to get a banking
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  license in the UK, you'll realize that as a fintech or
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  even as like a traditional financial firm, there's nothing
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  to be gained by trying to go around the system or short
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  circuit at it. You have to go right at it.
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  And going right at it means complying with rules as they
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  are, but doing it in a new way. We bring that new way and that's
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  what we're doing. And you talked about AI being,
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  you know, fairly shallow in in some ways.
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  Where are you seeing good use cases of AI being properly
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  implemented and and used for, I guess you know, a lot more
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  beneficial processes. Well, all of the software
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  developers, including the ones on my team, wonder how they did
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  their job before AI. So absolutely that's the case.
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  But what we're doing with our platform Reagent is we're
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  basically infusing the risk operating model of a bank with
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  AI and turning it into a closed loop where you can make sure
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  that your policies conform with regulations, make sure your
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  actual practices conform to the policies that you believe you
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  conform to Evidence that to the regulators when they come to do
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  an examination. And what I find most exciting is
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  in a closed loop, be able to affect the product introduction
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  and product approval process. So by using AI in the right ways
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  and we can talk a little bit about what those right ways are
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  and how they preserve accountability across all of
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  those processes. What we hope to be able to do is
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  to take all of the smaller banks, all of the non
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  traditional banks, all of the people who are disadvantaged by
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  the current manpower heavy way of doing this thing and be have
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  them be able to punch with the big boys.
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  Do you see a difference between legacy banking providers and the
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  more sort of neo bank? Well, I think yes.
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  And like what you have is in legacy banks and like if you
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  look at the big 5 banks in the United States, they have 10,000
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  people plus in their risk functions.
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  If you look at smaller banks, if you look at fintechs, if you
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  look at a bunch of the new D5 providers and all that thing,
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  they can barely spell compliance as it's spelled by the
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  regulators. So there's a very big difference
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  in culture, history, understanding, and yet over
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  time, whether it's a deregulatory administration or a
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  or a stricter administration, you need to be able to play the
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  rules of the game as they are set.
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  So we hope to be able to level the playing field for all of
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  these people and do so in a way that's just fantastic place to
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  work, which is not always the case in Risk.
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  And I get the feeling you've maybe got a few opinions on some
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  of these providers in the market, but they're not also
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  addressable customers for you, right.
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  If they do operate in a way that that you deem to be, you know,
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  slightly non compliant or they're struggling around that
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  compliance piece, they've got to be great customer fit for you
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  guys. Right.
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  Well, absolutely. I mean there's a whole legacy
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  ecosystem of like products called GRC systems and there's a
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  lot of workflow products that are used in the management of
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  risks and the management of exceptions and the management of
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  transaction flows and the new product introduction.
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  But a lot of them are wrapped around and are built for an
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  operating model. It is incredibly human heavy.
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  One of my touchstones is an old book from the 1960s called The
• 4:14
  Mythical Man Month, and it's observation was that the
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  productivity of a team plummets geometrically as the size of the
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  team expands. What do you think that says
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  about a 10,000 person risk management team, right?
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  So AI, right, is not going to replace everybody's jobs, but
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  what it is going to do is take the best people in your
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  organization, amplify them to where they can do the jobs that
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  would otherwise require 10 men or 10 women to be able to do.
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  In the future, we'll be able to have a much more streamlined
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  organization and the AI itself will maintain the model.
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  This is critical about trust and AI will maintain the model of
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  accountability that the regulators are comfortable with.
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  Nobody wants and in European law one is prevented from having
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  unaccountable computer systems making decisions that can't be
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  challenged. We maintain the human
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  accountability by amplifying the humans and the actual people who
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  are responsible for independent risk management, for compliance,
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  for prudential activities in the bank can have their own decision
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  process mirrored by the agents that work in the multi agentic
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  framework. That Reagent brings that's it's
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  a mouthful, but it means this technology that is under the
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  control of people and makes people more productive and
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  happier. I think it's a great way of
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  putting it. I think there's always been this
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  innate fear that AI is going to replace everyone and everything,
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  that the way you determine that it will make your best people
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  better, that's a great way of looking at it, right?
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  Across human history, every technology introduction, from
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  the introduction of the looms that the Luddites fought against
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  and probably to the introduction of the wheel that we don't have
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  anything about, has had winners and losers.
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  But overall, it's created more opportunities than it has
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  destroyed. And I think that's going to be
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  the case with AI as well. What I would like to see in the
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  future, like if if I'm a very optimistic person, you can
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  probably tell that like I think that we're going to have a world
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  where a lot of people are powered to do things that
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  formerly they would have to become a small cog in a very
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  large machine to affect any part of.
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  So more of that please. And that's what we're trying to
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  bring right now with like rational exponent.
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  And we're obviously here at Money 2020 in the USA.
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  Why is this such an important event in your calendar?
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  Well, in my calendar, this is possibly the most important
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  event of the year aside from the meetings that we have with our
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  customers. We've been working for about two
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  years on Rational Exponent for about 13 months on the
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  development of the platform that we are launching here at Money
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  20, 20. A reagent is now open for
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  business as a something that anybody can buy.
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  We have already deployed in a number of times in banks.
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  So we've had our early adopter customers.
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  So it's fantastic to be here with basically the entire
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  innovation ecosystem for the financial services industry.
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  Now a lot of the people who come here, they come here for things
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  that are obviously exciting innovations.
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  They come here for crypto, they come here for stable coins.
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  Way too many people come here to like sell, identicate products
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  around fraud and payments and those kinds of things.
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  And many of those products are fantastic and many of them are
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  going to sync without a trace. But it's the people who are
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  here, not at the booths and not on the stages in general, are
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  the people who are in the banks looking for an advantage,
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  looking for how the system is going to work going forward,
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  especially right now in the time of massive regulatory change,
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  regulatory change here in the US, of course, regulatory change
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  back home in England. There's all kinds of things
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  happening and So what Reagent is aimed at doing is whatever
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  direction the regulator steer us in, whatever direction the
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  innovation ecosystem ends up making affordances that drive
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  you one way or the other, we help you to be able to adapt to
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  it quicker. So to bring on the change and.
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  How do you find, so obviously you're in the UK, you're in the
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  USA, how do you find dealing with completely different
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  regulations in different? Markets, it's challenging and as
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  a result, I do what I frequently have done, which is I introduce
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  products in the United States because it's bigger, because
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  it's actually a better place to take risks.
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  And I actually love the way that Britain manages innovation and I
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  really love the way that the PRA works and the Bank of England
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  works to foster innovation. But look at the size of the
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  market here, look at the size of the ecosystem and we're striking
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  partnerships. So with a lot of fintechs and
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  other other non traditional banking organizations here as
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  well. You've got to be in the United
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  States, yeah. That's a fairpoint.
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  Yeah. I think we can see with the Uka
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  lot of companies start in the UK and then come to the States.
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  But doing it this way, you may be getting over the hardest part
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  first, right? And then you roll it back into
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  other markets from? From the US, yeah.
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  It's also the case that the AI ecosystem is here and like,
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  there's some fantastic talent here, there's some fantastic
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  vendors and partners, and, you know, it's a moving target what
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  the regulations around AI are. But we know what the risk
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  frameworks are. By the way, the American
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  standards organization, NIST, is fantastic at laying out how to
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  think about AI risks. And we've imbibed all of that in
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  the creation of our systems. Because if you're going to build
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  systems that help banks manage risk, be prudent and attain
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  compliance with a bunch of things, you better do it in a
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  way that doesn't introduce new risks that you don't understand.
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  So again, the Americans are leading a bit in this area.
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  Fantastic. Well, just before we finish up,
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  there's a little segment we do at the end of of every chat that
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  we have with our guests called the Shelf of Shame, where you
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  nominate something that really grinds your gears, whether it be
• 9:16
  in payments, in business, in fintech, whatever you want to
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  choose. What's going to be your
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  nomination for The Shelf of Shame?
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  Well, I think a lot of people probably are going to share this
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  one. Every company now, if you look
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  at their television ads, if you look at their marketing
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  materials, they're all AI companies, aren't they?
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  Funny that. I like real AI companies,
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  companies that were born to actually take advantage of the
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  new AI that's been around since 2016.
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  People who say they've been doing AI for the last 25 years,
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  sure, a lot of banks have been doing all banks.
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  You might say they're still that were around 25 years ago, have
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  been doing machine learning for the last 25 years.
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  It's an entirely new ball game. So it really grinds my gears
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  when everybody tries to AI wash themselves.
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  OK, fantastic. Well, thank you for coming on
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  the payment shed. Thank you so much.
• 10:00
  See you.