Welcome to Nasdaq trade talks,
where we meet with the top thought leaders and strategists in emerging technologies,
digital assets and regulatory landscape, and capital markets.
I'm your host, Jill Malandrino,
and joining us this afternoon, we have Ranjan,
CEO of sardine AI,
as well as Joe Robinson, CEO of hummingbird.
We're here to discuss the automated future of compliance.
It is great to have the both of you with us.
Welcome to Trade Talks.
So let's kick it off with you.
Let's discuss why we're seeing such a rise in AI fraud incidences.
Yeah. No. Absolutely. So one of the fundamental reasons is that when internet was built,
no one actually built sender verification.
So you could originate a phone call or
a text message and pretend to be a bank by spoofing the phone number.
And no one is actually going to test if
that phone number actually truly belongs to the bank.
That's the fundamental reason the entire financial system is broken.
Uh, is built on a broken fundamental Into the architecture of the internet.
However, that doesn't mean that we can't
actually stop these deep fakes or these scam attacks.
That is where sardine plays front and center.
We are constantly stopping, you know,
AI based deepfake attacks during ID verification or whenever somebody is
making a transaction at a bank under the guise of a social engineering scam artist.
Then we are detecting if the transaction is being made by a bad actor who's, you know,
controlling the victim's screen,
or is the bad actor making instructions on
a phone call to the victim and they're making a transaction?
So yeah, we can still stop these AI scams and deepfakes.
So I think part of the challenge is as well,
is the fragmentation sometimes that's associated with compliance as it relates to silos.
And I think that's a really big challenge that needs to be addressed
here. Oh, you're on mute.
Thank you. Um, you think about the perspective of
the folks trying to fight the crimes inside the financial institutions,
the banks, credit unions, payment companies,
they can generally see the activity that's occurred within their own institution.
But criminals are smart, right?
They're going to blend activities and illegal behavior across institutions,
across different payments, across different channels.
And so that results in the information silo that you're referring to.
It's one of the key challenges in financial crime enforcement
is our heroes of the financial industry are always kind of operating with,
um, you know, one side of the story or sometimes even less than that.
Yeah. And part of the challenge, too, is,
is that you have the good actors and the bad actors employing some of
the same types of technologies in real time.
Yeah. I know the the same technology that makes our lives easier and
gives customers or consumers
a good user experience can be exploited by bad actors, right?
So, for example, for online identity verification using, uh,
video selfie technology, you could actually
now open a bank account online without showing up to a bank.
But that also means that bad actors have at their disposal
the same technology and they can pass like a using face swapping.
They can pass themselves off as as me or Joe
and try to open a bank account pretending to be us.
However, other technologies like sardine,
we're always staying one step ahead of the bad actors,
and we can still detect these deepfakes on the basis
of the fact that when you're injecting a deepfake video,
you're taking control of the webcam,
or you're doing things like you're doing a video selfie,
but the phone is face down.
So we go into these deep behavior insights to tell you what is real versus fake.
We actually find that criminals are
often some of the most creative technologists in the world.
They'll try anything.
It's worth it to them, right?
If they can get, uh,
particular fraud scheme to work or a money laundering channel or something like that,
the hours and hours are, you know,
the thousands of people that might have working on these crimes.
It pays off for them to be very early adopters of
new technology before controls and protections actually pick up. So yeah.
That's a good point that you you bring up Joe,
because a number of these bad actors are very well funded as well,
especially when you're thinking about nation states and so forth.
So what would be an example of compliance AI in action?
Absolutely. There's different ways to apply AI that are very fruitful here.
So you know, there are things on customer diligence using AI
to better understand the counterparties of transactions,
the customer that owns an account,
things like that, their superior detection mechanisms,
which suits touch on a little bit about how do you detect deepfakes,
how do you detect selfies and bad behavior and things like that.
Um, and then in the operation procedures of investigations,
there's lots of ways to use AI to speed up information gathering,
to speed up collaboration with law enforcement so they
can actually go after and prosecute the crimes.
Um, and just generally to ensure that
the investigations are leveraging the best data that's out there in the market.
So and leveraging a technology like AI is
what allows continuous compliance to to work basically.
Yeah, 100%.
So we've built technologies to automate onboarding reviews or sanctions reviews,
negative news reviews or customer due diligence, etc..
If you think about it, many of the banks,
they at least spend 30% of their budget on compliance operations and using AI.
We are seeing that 95% of onboarding can be automated,
55 to 75% of sanctions reviews can be automated.
So these are pieces of technology which can help banks
become more efficient in their operational.
Are you seeing silos being broken down because of
this type of technology where you're able to have different business units?
As an example, um, you know,
your crime team or your anti-money laundering team,
your risk and financial operations and so forth.
are these types of technologies allowing a bird's eye view across the enterprise?
Yeah, actually highlighting a really important point,
Joe, which is within a particular institution,
there might be multiple teams in different practice areas
that are doing the same investigative work,
the same diligence work.
And so, yeah, um,
one of our focus areas is essentially to break down
those barriers and make sure that every team has
the full extent of prior investigation work they might have done
on a particular typology on a subject.
Um. And increasingly we're seeing cross institution,
uh, sharing as well.
So banks working with the fintech partners that they
bring on banks working with each other through, uh,
sections of regulation that allow them to collaborate on investigations, uh,
and banks and public and private sector working
together on some of the investigation work through these,
these data and investigative procedures.
Yeah, I think it's a key point that you brought up and not just in finance in particular,
but I think public private partnerships,
you could even include academia in there as well.
These technologies are going to be influential when it comes to
thinking about reregulation and policy making,
as you look forward to the future.
Yeah, 100%. So if you really think about it,
you know, the BSA, AML regulations, right?
They were written like several decades ago and they
need to probably evolve with the changing times, right?
Um, and for instance,
when we are filing SARS suspicious activity reports,
it goes into the ether and no information comes
back to the filing entity as to what was actually done with it.
Right. So what, you know, uh,
the these new pieces of technology are just enabling us
to get more and more efficient when it comes to even transaction monitoring alerts.
You know, when you're generating
all these transaction monitoring alerts or compliance alerts,
you don't have to hire like as high as huge a team to review them,
because I can help you,
you know, reduce the false positives.
And then the next iteration would be let's work with the regulators
into having some sort of a back and forth with
them about what happened with the SARS? Right.
Right. So I think that's an excellent point that you bring up,
because sometimes the function with compliance can feel as if you're checking the box.
Right. But then to your point, what happens with it?
What have we learned? How do we mitigate that risk going forward? How do we detect it?
How do we employ agentic AI so that we can, you know,
predict or recognize behavioral patterns,
whether for good or bad actors,
to mitigate this risk?
I feel, you know, just checking the boxes over the past number
of decades has hasn't been very useful.
Yeah, that's that's that's an accurate statement.
And I think the outside of AI,
there's other new forms of technology that have come out right,
like zero knowledge proofs, etc.,
which can be used in cases like this without for,
you know, for the,
the financial regulators to share information back with the, with the banks,
even though they don't need to necessarily say that,
hey, I made an arrest or what have you.
And but you can at least,
you know, if a bank could query, uh,
FinCEN and have some idea that,
hey, what happened with the SA that I filed?
That would be a step in the right direction?
Yeah, it certainly would be.
And Joe, when you think about, um,
early adopters and employing or building models and just, you know,
a compliance, um, cyber first mindset across the enterprise.
I think from a competitive perspective,
that certainly is going to be an advantage as it relates
to scalability and not falling behind.
I think at the end of the day, it'll be more cost effective.
And certainly, you know,
cement your place in in the competitive landscape.
What are your thoughts around that?
There there are direct advantages to keeping your costs of
compliance down through efficiency and operations.
And then there are indirect advantages as well,
where regulatory issues can be a huge issue that can sink the ship later on.
So, um, keeping both of those in mind as you're investing in
better compliance technology and better anti-financial crime technology generally,
um, both of those factors can affect the bottom line.
How are these technologies Technology is deployable at this point.
Are you starting to see more adoption come online, Joe?
Absolutely. We've actually seen a real surge in use of
AI for investigative work over the first two quarters of this year.
There's a lot of chatter about that since 2023,
but financial institutions tend to be more conservative
about adopting new technology for for good reasons.
But over the last two quarters,
we've seen a lot of exciting development with our own products and with in the market
on how people are applying AI to increase their investigation throughput.
So the communication of information to law enforcement,
as well as the quality and depth of the work that they're able to do.
Yeah, I would imagine you're seeing the same thing as well.
And also when you think about your outlook, you know,
to Joe's point, 2023,
certainly there was a ramp up there.
And of course, you know, generative AI became part of
the consumer vernacular in November 2022, right.
With ChatGPT and all of these new products were pushed out,
whether it's internal or external,
to keep up with the competitive landscape. Escape?
Yeah. No. Absolutely. So what we are finding is that, you know, um,
our agentic AI technologies are now, uh,
live with close to 20 of our customers,
which includes fintechs, banks, etc.
and they're using it day in and day out to do to use the agent A.I.
as a copilot to do sanctions reviews or even in
fully autonomous mode to do an onboarding review or, you know,
doing a transaction flow to screen the counterparties or to do
what we call an Osint or open source intelligence search, where, you know,
you look up the counterparty,
for example, I'm a restaurant,
but I am, you know,
uh, making a huge payment to,
uh, to an auto parts supplier.
So that doesn't make sense, right?
So those types of patterns can be explained and inferred much better by using Agentic AI.
All right. I appreciate both of your insights.
Thanks for joining us on trade talks.
I'm Jill Malandrino, global markets reporter at Nasdaq.
Thanks for having us Jill.
Thank you.