00:00Tiene más de 20 años implementando soluciones para prevenir el fraude y el lavado de dinero.
00:18Promueve la inteligencia artificial colaborativa que permite el aprendizaje sin comprometer la
00:24privacidad de los datos en el sector financiero. Fundó su propia empresa a los 14 años.
00:30En la transición al Y2K se especializó en ingeniería inversa y llegó a ACI para crear el primer sistema
00:38de inteligencia artificial dedicado a la lucha contra el lavado de dinero.
00:43Cleber Martins, vicepresidente de Inteligencia de Pagos y Soluciones de Riesgo de ACI Worldwide
00:50en Milenio Negocios.
00:51Bienvenidos a Milenio Negocios, este programa que hacemos todas las semanas.
01:01El día de hoy me acompaña Cleber Martins.
01:03Él es el vicepresidente de Inteligencia de Pagos y Soluciones de Riesgo para ACI Worldwide.
01:09Cleber, thank you very much for being with me today.
01:12And we're talking about money laundering, a topic that in Mexico lately has been in the
01:18news related to, very related to financial institutions.
01:22And I know that ACI Worldwide is focused on the payment ecosystem.
01:27You, however, are an absolute expert in money laundering and artificial intelligence solutions.
01:34So, I wanted to begin this interview with that.
01:38Can AI lead the world to less money laundering?
01:43How and how soon?
01:48Regina, yes, that's the quick answer and we get to the details.
01:53So, first of all, thank you so much for having me here.
01:55Uh, AI is definitely the way that, you know, we can scale to what needs to be done in order
02:03to prevent and actually, uh, just, just react faster to the tracks that came in the directions
02:11of the financial ecosystem.
02:12AML or money laundering is one track, fraud is another track.
02:16And AI is the way that the financial institutions have to scale up and be able to have much more
02:22control of what's happening on their environment.
02:25So, definitely, that is the way to go.
02:28Now, um, the US Treasury Department of, a few months ago, mentioned Mexican banks and
02:33money laundering and, and, and the normal reaction was the Mexican regulator, regulators
02:39said that there would be more regulations for new license in the bank system.
02:46So, if you want to become a bank, the process is going to be harder.
02:49It's also regulation.
02:51It's also a road in other sectors where it sort of makes the competition less.
02:58And then it makes it more complicated for the clients also to take advantage, which means
03:03there's a problem for the, for the end client because the services and solutions can become
03:09more expensive.
03:10And in that sense, I wanted to ask you, um, is there a way to have a more proactive risk
03:16management that, that doesn't lead to less competition in the financial sector?
03:21So, Regina, definitely the rules are necessary.
03:26So, the regulators have to establish the rules.
03:29It's about, you know, keeping accountability where it needs to be.
03:33The financial system, they, especially the banks, they have a lot of, uh, spending they need
03:39to do to comply with that regulation.
03:40It is expensive and it makes it more expensive for the entire ecosystem.
03:45The customers end up paying for that at the end of the day.
03:48In the other hand, the regulation cannot be, oh, the regulation is also known by the criminals.
03:55So what the criminals will try to do, and that's their job at the end of the day, is try
03:59to go around the regulation and bypass.
04:02So for money laundering to go through, they need to understand the regulation, they need
04:06to be able to go around it.
04:08So what really helps the financial ecosystem are the tools, the technology that is able
04:14to see everything that's happening and act over it.
04:18So the technology at the end of the day, as much as it sounds like an expense that the
04:24financial ecosystem has to go through, it's actually reducing the overall, overall burden
04:31of this regulatory environment.
04:33So the technology should help you to stay on the top of the regulation, but most especially
04:38to stay ahead of the criminals trying to go around the regulation.
04:42While we believe that technology may be expensive as well as it is to comply with the regulation,
04:49it's way more expensive.
04:50The reputational damage that ends up happening, not only with the bank, but with the entire
04:55ecosystem, right?
04:57And if you think about, you mentioned the customers and how customers end up suffering with that.
05:02At the end of the day, the consumer, the customer, they're just trying to do, to transact, the
05:07good customers, the legit customers are the majority.
05:12And yet they have to go through a much harder process trying to do what they're trying to do.
05:17If the financial ecosystem is not well prepared to handle that from, you know, the size of the
05:24institutions, the entrance, the new entrance to the ecosystem.
05:28We do want you to have an ecosystem that is democratic and, you know, the more competition,
05:33the less expensive it overall becomes for the consumers.
05:37So from our perspective as technology providers, we want to make sure that everything we build
05:43is very democratic.
05:44And we've been on that journey, democratic meaning that even the smallest institutions
05:49or new entrants, they need to have the same high-end technology and capabilities as the
05:55larger ones.
05:56And at the moment, we make it available and we're very successful doing that.
06:00Then we enable them to compete at the same level with the same protection.
06:05Okay.
06:06Let's talk a little bit about predictive analytic systems and real-time fraud monitoring, because
06:13those two things are something that help financial institutions stay on top of what is going on.
06:19And so we've been hearing about collaborative artificial intelligence in these systems, but that means
06:27sharing information.
06:28And in the financial sector, sharing information is something that hasn't been so easily done,
06:33especially in Latin American countries, particularly in Mexico.
06:37How should we work further together to get to that point where we are cyber secure ahead,
06:48but also being able to share information without sharing those privacy issues about money and
06:56profiles and clients?
06:58Well, so let's just start by making it clear that sharing information is no longer the way to go with
07:05the latest on technology.
07:06The latest on technology has sold for that.
07:08And I'll get back from that point.
07:10Okay.
07:10So you made a very important point about how real-time changed the game.
07:15So in the past, you could actually wait for the things to happen and you'd be able to revert
07:22those things when you find the problems.
07:24You'd have more time to react, not only for money laundering, but for fraud, but with real-time payments,
07:30with digital customers willing to come in and onboard very quickly and start using new products,
07:35all that competition for that digital consumer, right?
07:39It's way faster than new generations.
07:41So you cannot alone give yourself the rights to just play after the fact.
07:45You need to act as things are happening.
07:48So if you think about, you mentioned predictive analytics.
07:51Predictive analytics have always been about understanding from the history and predicting
07:56what is about to happen next.
07:58Now predictive analytics had to evolve to understand on what's happening right now.
08:03The context of each payment, the context of each new account that is created is very important
08:10to stop fraudulent and money laundering activity before it happens.
08:16So the real evolution that happens in machine learning or artificial intelligence at this point
08:21is being able to understand that context in real time and act with that context at hand.
08:28First, to make sure that good customers are doing what they are there to do without much friction,
08:33as well as impeding or stopping the fraudulent or money laundering activity to just pass through.
08:40Now, if you think about the ecosystem, the ecosystem have one perspective of it.
08:47So money laundering is about moving money between different institutions or different products,
08:52but mainly between different institutions.
08:54If you think about the new fraud that's raising worldwide with the scams, it's involving multiple
09:01institutions.
09:01So the criminals convince the customer to send money from one side to the other side,
09:05and each of those banks are only seeing one perspective of it.
09:08So the real challenge with the collaboration is the criminals are seeing more than each individual
09:15financial institution is able to see.
09:17And once the criminal has more visibility for what's happening,
09:20it's really difficult for each of those institutions to understand and stop.
09:25Now, if they collaborate, they have more context and they have better technology than the criminals
09:32will ever have.
09:33So the collaboration becomes the real tool, the real artifact that will change the game.
09:40Now, as you mentioned, sharing intelligence, sharing data becomes a problem, right?
09:45Because you don't want to share your secrets, your customer's data, the customer doesn't want to share
09:49their data.
09:50So the new technology is based in a concept called federated machine learning.
09:55So imagine that in the past, you need to take the data and take it somewhere to learn.
10:00Now, it doesn't work like this anymore.
10:02We take the learning where the data is, and at the end of the day, the data stays where it resides,
10:09the learning goes there, and the learning gets exchanged.
10:13And this is machine learning, the metadata.
10:15It's not something that can expose any of the data behind, but it's about the new generation of
10:20artificial intelligence that empowers this collaboration at a level that was never possible before.
10:27Now, for this collaboration, what needs to happen?
10:31Do financial institutions need to get in touch with the regular, you know what I mean?
10:36Like, how can we get there? Because the problem is, as you mentioned, that the people committing
10:43the crimes have more points of view of the information, have better ways.
10:49They're always learning really fast.
10:51They're faster.
10:53And so how does the ecosystem and the sector in general have to come together to be able to
11:01to have this machine learning in real time with analytic systems that are collaborative and that
11:07allow it to sort of catch in the moment and be able to protect and ensure that these risks
11:16start going down instead of up?
11:19And Regina, this is the conversation that's happening worldwide.
11:22It just came back from India last week, and that was mainly the whole week on that one.
11:27So each region or each country is taking a different approach, but similar somehow.
11:32So in some countries, we have the center infrastructure, the one that is empowering
11:37immediate payments, is stepping in and organizing that collaboration.
11:42So each member of that center infrastructure, they have a piece of the technology that just speaks
11:48the same language, right?
11:49And they complement the capabilities they had before.
11:53In some other regions or some other countries, we have like processors, institutions that are there
11:59helping banks already doing some sort of interaction between financial institutions,
12:03is stepping up and, you know, being the one that is organizing this.
12:08And very honestly, in some countries, a large bank is stepping up and saying, hey,
12:13I have the ability to, I will help the market.
12:16Here's what we're going to do together.
12:17So it's about sitting together and together taking responsibility.
12:21I think there's, you know, financial institutions have very strong leaders, very smart people,
12:27and they talk and they are, you know, in meetings together, in collaboration together.
12:31Once they sit down and they talk and they take that collective responsibility to fight against
12:36financial crime, they get stronger than the criminals.
12:39Whether it comes from the same infrastructure, from one large bank, from a processor, someone just,
12:44you know, a technology company that's in the middle, it will work.
12:48It's just about working together.
12:51Thank you so much for, for your time, for this interview.
12:54I know that this is something that we in the, in the Mexican audience here in Millenio would
12:58like to hear some more.
13:01That's it.
13:01Thank you so much, Eugenia.
13:02Thank you.
13:03Thank you, Clever Martin, de ACE Worldwide.
13:06Nos vemos la próxima semana.
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