How Chainalysis Stops Crypto Scams Before They Happen! | Jonathan Levin - Thinking Crypto News & Interviews

Episode Transcript
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Speaker 1 (00:00):
We screen really every single website that is created in
the world every day against our models to see whether
there are new scam websites being created every single day.
And we have to be at the tip of the
spab so that we can protect what addresses they're using
on that scam website, so that we can protect all

(00:20):
the users around the world before they get scammed. It's
a constant game of katamaus and now the MISA using AI,
so we got to get better as gats.

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visit the link in the description. Hey, folks, welcome into
the Thinking Crypto podcast. I'm your host Tony Edward and
we're recording at Station three in New York's Financial District.
And joining me is Jonathan Levin, who is the co

(01:40):
founder and CEO of Chanalysis. Jonathan, great to have you.
Great to veha Jonathan. I've read about chainnalysis and cover
chainalysis news over the years. You guys have been doing
some amazing things and you have a perspective on blockchain
which I think a lot of people may not have
because you're looking at the data, the analytics, the transaction.

(02:00):
So I'm excited to dive into that and nerd out
a bit. But tell us a bit about yourself. Who
are you, how do you start chainausis and things like that.

Speaker 1 (02:07):
Yeah, So I'm Jonathan. I grew up in the UK.
I came to the us for chain analysis. But how
I got into crypto was actually, you know, a typical
British story. I was sitting at the pub with my
friend Tom. We had a few beers and he told
me we should start arbitrage trading bitcoin back in twenty twelve,

(02:28):
and you know, I didn't do that, as otherwise we
wouldn't have started chainalysis, and so instead I went down
sort of a rabbit hole of understanding really the big
questions the bitcoin was asking, which is, you know, why
does the state have a monopoly on the issuance of money?
Why is the Internet dominated by a few major firms.

(02:51):
How are we going to construct a global payment system
for everyone to join the Internet economy? And you know,
those types of questions led me to think that they
actually needed to be a company that could tell those
stories with data rather than just think about, you know,
the use cases. And you know, that's really how chang

(03:14):
Alsis was born, is really out of a necessity to
be the company that knows the most about how and
why people actually use crypto. And that's that's really what
we've been doing for the last eleven years.

Speaker 2 (03:26):
And you've certainly been a leader net space and it's
a funny story. You mentioned, you know, you learned about
it from a friend and a pub I have a
similar story. I was at Buffalo Wild Wings with four
other friends. One buddy was trading big oney and he's
telling us about it where you're having beers and wings.

Speaker 3 (03:41):
I'm like, what is this? It sounds like a scam.

Speaker 1 (03:43):
I mean, it's the best way to learn about it.
I mean, you know, you stay for a few beers
and it starts to make more and more sense, right,
I mean, it just it just happens.

Speaker 2 (03:52):
Yeah, it's funny, you know, initially my reactions as a scam,
but then he kept bringing it up every other time
we would go out, and he was started making some money,
and of course then from there I went down the
rabbit hole.

Speaker 1 (04:02):
Yeah, it's really really interesting. So we started Chainalysis, and
really the purpose behind it was to make sure that
crypto exchanges at the time in twenty fourteen fifteen had
a really time, really hard time getting bank accounts, and
one of the fundamental questions that banks had for crypto
businesses was well what are your users actually doing with

(04:27):
those crypto assets? And the exchanges were having a really
hard time explaining to banks what the use cases for
crypto were and really what individual users were doing with
their crypto, And so we built chainalysis to allow for
crypto businesses to actually get bank accounts for the first

(04:49):
time because they could suddenly explain really where the money
was coming from, where the money was going to, what
their users were actually using cryptocurrencies for.

Speaker 2 (04:57):
That's pretty profound. The the use initial use case for
what you guys were doing was to help get banking. Yeah,
but now we can go beyond that because it could
be used for marketing user behavior, habits and in building
the proper solutions. What are the habits of users, what
do they gravitate to and things like that.

Speaker 1 (05:17):
Yeah, I think that when people think about the blockchain,
there's definitely a lot of talk about transparency, but actually,
like that's what chainolsis provides to the businesses in this space,
is the transparency about what are users actually doing with cryptocurrency,
What is happening in stable coins, what's happening in DeFi,
what are the intersections of these different worlds. You read

(05:40):
a lot about these different use cases of crypto, but
no one really understands how they actually fit together. And
you know, really what the blockchain is really good at
is providing that complete map of all of those pieces
of activity, and you need the analytics and data that
Chainousis has in order to be able to understand those flows.

Speaker 2 (06:00):
So how does chain elsis plug into all these blockas
there are many out there, right, how are you what's
the execution look like to Is it an API driven
feed and you're monitoring it through software and things like that.

Speaker 1 (06:12):
Yeah, So we actually run a lot of nodes ourselves,
and we use some node providers out there to run
nodes on our behalf. And then we'll take all of
the data off of those nodes and index them and
normalize them to understand how to compute things like the
balances for individual addresses and wallets, and we transform that

(06:37):
data into a system of looking at how does money
move on those blockchains, and we can then recreate sort
of all of the different ways and which wallets have
transferred value from one place to another, what has the
role being of smart contracts in transferring value? And then

(06:57):
we go and label all of those different was ballets
and smart contracts with the real world entities that stand
behind them. So we go out and we find the
information about which wallets are controlled by coinbase or okax
or buy bit or binance, and then also you know
what are all the other use cases of crypto, So

(07:18):
what are the merchant services, what are the scams, what
are the hacks, what are the pieces of ransomware that
are out there? And so you know, together we we
we build that comprehensive map of hundreds of thousands of
entities that are really providing services within the crypto economy
and how all of them have transacted over all time.

Speaker 2 (07:43):
You know, it's interesting because you're you're you're getting a
full view of the landscape by doing that, and I'm curious,
who are the folks that are using your services? Is
it governments, tradify crypto native firms and things like that.

Speaker 1 (07:55):
Yeah, really it's you know, obviously the government, which we
can touch on. I would say that anyone who's putting
a cryptocurrency transaction in a blockchain is using us, but
in some way, and that could be at the really
low level where people are using us to monitor the
security of smart contracts or even blockchain integrity or staking.

(08:20):
They use our product Hexagate to be able to do that.
And really that goes into the real nuts and bolts
of how blockchains work. Every smart contract action, every change
in keys of governance protocols, any change in price of
an oracle like, everything can be monitored at that low

(08:41):
level for us all the way up to the way
that transactions work and really how value is moving across
the blockchain. And then that's really sort of everyone from
the exchange landscape that is using US and all the
biggest wallets and exchanges around the world.

Speaker 2 (08:58):
So you're getting all this data, certainly you're data mining,
you're aggregating it, but are you able or to people
who are using your platform able to see real time
transactions as well?

Speaker 1 (09:08):
Yeah? So really, I mean, if you think about our
observability product that I was just mentioning, that is all
about preventing hacks or fund loss in real time. And
if you think about you know, our scam prevention that
we offer as well, it's all real time screening transactions.
And so if you are one of the largest exchanges

(09:32):
in the world, if you are a large wallet in
the world, you're using chain analysis to be able to
screen against risk in real time, to make a real
time decision about whether you should process that deposit, process
that payment, or make that withdrawal or credit that account.
And that's something that we pride ourselves on, is that

(09:54):
you know, really you can have a comprehensive risk monitoring
solution for this new payment instrument in a way that
mirrors what you get in traditional finance.

Speaker 3 (10:05):
Oh absolutely.

Speaker 2 (10:06):
I don't know if you can share details, you know,
but as much as you can. What are some of
the common scams that you're seeing that people are trying
to do?

Speaker 1 (10:14):
Oh, we love this, so we love we love a
good scam. Ut So there's lots of different scams that happen.
I mean what we obviously track the different types. I
would say that, you know, one that we're very familiar
with is you know, the investment scams that are popping up.
You know, we screen really every single website that is

(10:37):
created in the world every day and screen that against
our models to see whether there are new scam websites
being created every single day, and we have to be
at the tip of the sphere making sure that we
can you know, detect those scam websites that look like
scams that we've seen before, so that we can make

(10:58):
a you know, deposit and withdraw or we can detect
what addresses they're using on that scam website so that
we can protect all the users around the world before
they get scammed. So we we like a we like
a high yield investment product better than the next person.
We go out there, we make you know, we make

(11:20):
that identification and then we monitor those websites to be
able to you know, mitigate against you know, scams if
you are a major exchange and you're allowing users to
withdraw to those websites. So that's why one type of scam.
The other types of scams that we see, I mean
we see scams on on Telegram, on TikTok, on Facebook,

(11:40):
all these places. A lot of it is really about
you know, selling goods and services that people are in
desperate need for. People want to buy you know, music
theater tickets, or they want to buy you know, a
couch on Facebook marketplace, or you want to buy Some

(12:01):
people are buying cars on Facement marketplace. Some people are
buying pets on Facement marketplace. Like wherever someone is buying
an object, you know, there is someone selling a fake object.
And I think that, you know, from our perspective, like
those are all you know, damaging the consumer. The consumer
is not always losing crypto in those examples. You know,

(12:23):
sometimes sometimes the users are losing their dollars, but a
lot of the infrastructure is paid for in crypto, and
some of that laundering activity is also in crypto. We
at Chaine Analysis we like to close what I call
the intelligent sloop and so we like to look at

(12:44):
the full life cycle of any threat to the industry
or to public safety, and we want to close as
many intelligence sloops as possible. So we will go out
and we will go and identify these scams, will identify
them on the whatever the scammer is using to victimize someone,
we'll collect that information. So whether that's a cash app tag,

(13:07):
whether that's a PayPal email address, whether that's you know,
a xell phone number, like, we'll go out, we'll collect
those things and make sure that we can provide it
to the relevant people to prevent the fund loss ultimately
from the consumers.

Speaker 3 (13:20):
You mentioned.

Speaker 2 (13:20):
You go out and you look at these different websites,
and my background is in search marketing, So are using
some sort of search engine crawler, like a bot crawler
to go out there like Google.

Speaker 1 (13:29):
Yeah, we we call we built our own crawlers to
be able to go and do this, and you know,
we we we ultimately are looking at the ability for
us to use at alms to now go and index
those websites, interact with those websites, and we're using a
lot of AI under the hood to actually go and

(13:50):
have those types of interactions.

Speaker 2 (13:52):
Yeah, I was going to ask you about AI. How
are you leveraging that? So do you have AI agents
doing things?

Speaker 1 (13:56):
Yeah, so we we have what we would call like
undercover AI agents, if you will. There are essentially you know,
going out and making transactions and looking at websites and
building our data set and so really like that's you know,
the force of us actually learning for ten years how
to go do this manually and ultimately be able to

(14:19):
train these agents to be able to go out there
and protect the industry.

Speaker 2 (14:23):
So as the blockchain and web three ecosystem grows, you
get trac FI coming in building and much more, There's
going to be a lot of transactions. Jonathan, Right, how
is chainelsis prepared to handle that?

Speaker 1 (14:33):
Yeah, it's a great question. I mean we think about
this a lot. I think that you know, ultimately, like
there are some scale advantages of being in the place
of chainalysis, the market leader of all of analytics. And
so you know what we think about is how do
we make sure that we can continue to collect all
of the data at scale to label these things. You've

(14:54):
heard that one of the strategies is to not use
humans and use agents and yeah, but also you need
to be able to architectural systems in a way that
is scalable, you know, Solana and base Us scaling, and
you know, you need to be able to identify all
of the different tokens that trade on those blockchains. And

(15:15):
actually all of that actually comes down to you know,
great engineering for you know, scaling these systems, and you
know we've been we've been doing that for eleven years
and have a good understanding of it.

Speaker 2 (15:27):
You mentioned Solana. You know, we we've seen a lot
of meme coins launch and Solana would pump that fund.
Are you monitoring that as well?

Speaker 1 (15:34):
Yeah, well we'll monitor all of the different meme coins
on on Solana, you know in the you know, tens
of millions I guess today and as Wild Yeah, it's
been it's been something that we have really had to
re engineer our systems to handle these types of different
use cases, and you know, we used to think about

(15:54):
individual token support. We don't think about individual token support
for a blockchain today. We think about blockchain support, and
tokens come for free in our architecture, and so we
actually have now scaled to those larger blockchains where there
are tons of different tokens being issued and all of

(16:17):
our customers can benefit from seeing anything to do with
any of those tokens that move on that platform with
no humans at chain analysis getting involved in supporting that.

Speaker 2 (16:27):
So we talked about the crypto exchange cohort. What about
governments and tradify? Oh, how are they leveraging your services?

Speaker 1 (16:36):
Yeah, when you think about the government, I mean they
were actually some of our first customers and really today
we serve over three hundred and fifty government agencies in
sixty five countries around the world. We have a very
large presence among the way that governments really understand what's
happening on the blockchain, and you know, for us, that's

(16:57):
all about making sure that they have the tools at
their disposal to follow the money on the blockchain for investigations,
public safety, national security, and regulatory oversight. And the regulatory
oversight piece is the thing that has changed the most
over the last couple of years, where we went from
a world of sort of where the US was just

(17:20):
enforcing against crypto businesses and we've now moved to a
world of which the regulators are now tosked with overseeing
the market. And actually that puts us in a different place,
which is we can actually equip government agencies with the
tools that they need to have better visibility about what's

(17:40):
happening in the crypto market than they even have on
traditional markets that they supervise, and that power changes the
way that they should be thinking about policy, It changes
the way they think about examining these companies, and it
changes the way that there can be a much more
fruitful collaboration between the venues and their regulators. And really

(18:06):
that's for us like such a powerful thing for the
industry because it means that we're going to have like
a pragmatic regime that all the venues, all the real businesses,
can innovate faster while the government stays comfortable that they
have the visibility they need.

Speaker 2 (18:24):
Yeah, I've heard data from Chanels's reference in congressional hearings,
which is amazing. So you have one of the core
pillars of this industry too. That's needed for this industry
to grow because you've got to have the insights, the
data and analytics to monitor all these things.

Speaker 1 (18:41):
Yeah, I mean, we spend a lot of time on
Capitol Hill. I've been on Capitol Hill myself, and you know, really,
you know, we spend time educating people with the data.
And I think that this is like what I first
got started with in crypto was people were telling really
good stories, and we need good storytellers, we need people
who are going after use cases. We need all of

(19:02):
those things, but we also need to be very grounded
in the actual data about how people are using cryptocurrency.
Is what is this stable coin volume that is existing
in the world today, Like, what are the flows looking
like between different countries, what are the types of use
cases that we actually see getting traction And when we
come to the government and we explain to them that,

(19:25):
you know, there is a very small percentage of the
overall activity that is related to criminal activity, and we
can show them the evidence of some of these use cases.
So really that changes the posture of the policymakers.

Speaker 2 (19:38):
Well, absolutely, you know, as you're saying that, I thought
of are you able to delineate between bought activity like
fake transactions and real real Yeah.

Speaker 1 (19:47):
We spend a lot of time looking at you know,
fake tokens, fake transactions, fake volumes like yeah, these are
all things that you can pick up as you are
actually looking at the blockchain and looking at these different transactions.

Speaker 2 (20:04):
And then for trad five, are they approaching you now saying, hey,
we need to get plugged in soil we know what's happening.

Speaker 1 (20:09):
Yeah, I would say that. You know, this is something
that has been one of the fastest growing parts of
the chainalysis market today is how trad file is actually
moving into the space to offer products and services to
their customers. And really, when you think about trad fi,

(20:31):
trad fi have a much lower risk threshold than anyone
who's in crypto today. So anyone who's in crypto today
is like very much an innovator, very much someone who
likes to be able to offer new products and services
and move really quickly. You know, traditional finance is in

(20:52):
the business of you know, they've got a huge brand
to protect, they have greater scrutiny from regulators, they have
a lot bigger risk and compliance teams than you know,
even what we have in some of the largest crypto exchanges,
and so what they really want is they want to
be able to access chainalysis, build a full program around it,

(21:15):
build a scalable solution for them to be able to
transact on the blockchain. And actually we start to see
some of the more major banks, you know, take the
steps towards public chains, and that's a really really exciting
moment for the industry.

Speaker 2 (21:32):
So on that note, many of these banks and trad
fin institutions, they have, for example, an in house wall
garden blockchain permission private, but it bridges to public blockchains
because that's what the liquidity is, the settlement. So are
you able to also plug into their private if they
allow it?

Speaker 1 (21:49):
Yeah, so we would. But you know, fundamentally, like the
way that I think about chain analysis is that the
value of chainalysis is to be able to understand what's
happening on public blockchain infrastructure. It's something that we are
really well placed to understand the most about that ecosystem.
And I think that with all value and money transfer,

(22:12):
the game is always about liquidity. It's always about where
is the most liquidity and how does that create the
most efficient market? And so that will always be on
a public blockchain. And that's something that I think is
being realized by trade Fire, is that we start to

(22:33):
see demand for ubiquitous, instant, low cost payments and value
transfer of all types, and that can only really exist
on public infrastructure. It can only really exist in a
world where everyone can tap into that common standard that

(22:56):
no one really owns in its entirety, that no one's
in can of saying who's in and who's out. And
so this is where I think the traditional finance world
is realizing that ultimately more and more liquidity is going
to end up on this public infrastructure that's universally accessible,
and they need to be ready for that.

Speaker 2 (23:17):
Yeah, that absolutely makes sense. So on that note, what
does your vision board look like for a chainalysis by
twenty thirty, you know, as legislation comes in. You know,
what do you guys, what do you see chainalysis in
five years?

Speaker 1 (23:29):
Yeah? I think that the way that we think about
chainalysis in five years is that we are the company
that is the intelligence layer for all value that moves
on the blockchain. And you know, the way that I
see it is that today there are a few thousand
entities transacting on chain at scale that are our customers

(23:52):
and the people that we serve, and ultimately like that
needs to become like fifty thousand, like there needs to
then become one hundred thousand, that needs to become then
a million businesses who are significantly moving value on the blockchain.
And so once you go up those sort of two
orders of magnitude, chainnalysis becomes really this ubiquitous layer of

(24:14):
data and analytics that powers all of those different enterprise
use cases that get us there. And really I think
that to some extent, not that we fade all the
way into the background, but that you know, the whole
ecosystem is running on chainalysis data to be able to
assess risk, build better products, build their business cases, build

(24:37):
new financial products. And we really sit there as like
a common layer of intelligence across the whole industry.

Speaker 2 (24:45):
And that industry is global, Jonathan, So I can't imagine
you know, this scaling that you have to do in
demand power that you will need. Obviously at AI helping you,
but you know, people are like, hey, I want to
see what's happening in Europe specifically or in Asian markets.

Speaker 3 (24:58):
You're able to do that.

Speaker 1 (24:59):
Yeah, So we actually have boots on the ground in
over twenty nine countries around the world. You know, that's
something that we are really happy to be able to
localize our support for those different markets and something that
you know, I went around the world with a backpack

(25:20):
building these markets. Luckily I didn't have to carry suitcases
of cash and we just went in with crypto and
made it a lot easier to build these markets. But actually,
you know, I think that you know, that is starting
to pay off for us as we know locally support
and serve governments and industry in those different countries around

(25:42):
the world.

Speaker 2 (25:42):
So, speaking of international I read recently that chanelso has
got the first ever academic evaluation blockchain intelligence data by
independent academic researchers some tu Delf Netherlands. As a mouthful
you can tell us a bit about that, Yeah, sure.

Speaker 1 (25:57):
So you know, really, when you think of about the
data and intelligence that chainalysis has, it's really hard for
people to independently evaluate what is the quality And the
best way to analyze the quality of the data is
to have people who have access to the real wallets

(26:17):
that people are interested in tracking and judge independently whether
chain analysis had the real information about the wallets that
then law enforcement had actually seized from those targets. And
so this study essentially was a partnership between the Dutch
police and the university to use information that the Dutch

(26:42):
police had seized from criminal entities and test whether chain
analysis had an accurate representation of those wallets. And they
went to our competitors and they asked them for the data.
And once the data started to look like they weren't

(27:02):
going to be looked on favorably, one pulled out of
the study and the other actually threatened to sue the police.
But in the traditional sort of Dutch fashion, they actually
sort of put that in the paper, and so you
can go read that the Dutch police talked about how
the one of the competitors of chainalysis threatened to sue
them even if they released anonymous data showing the quality

(27:27):
of that competitors information. So you can see that. You know,
for us, when they came to us and said, like,
we'd like to include you in the study, we take
our responsibility as the market leader incredibly seriously and we said,
for sure, you can do it, and we'd love to
hear any feedback you have about the accuracy that we
have and so what we saw in that instance was

(27:50):
we had a very high coverage rate. So we detected
ninety five percent on average of the wallets that they
were sort of looking at. So that tells you the
extent that we could actually go and detect it, and
we had, you know, less than aner point not one
percent or around nor point not one percent false positive

(28:14):
rate on all of the addresses for actors that are
intending to evade our detection and make our lives difficult.
And so if you think about that, like that's the
thing that has actually allowed chainnalysis evidence to be the
only evidence that actually stands up in court that has
the scientific method behind it, that has the rigor behind it.

(28:36):
And so both for government agencies that need to be
able to rely on scientific evidence where you can back
up really the analysis that's happening about what's happening on
the blockchain, and for businesses that want to make really
hard decisions about the risk of their customers, you know,

(28:58):
they come to chain analysis to have that golden standard
versus people that aren't willing to have their data inspected
and held up to scrutiny.

Speaker 2 (29:08):
I think I know the answer to this question, but
with the tokenization market on the rise, people are tokenizing
different assets, goal money market funds and so forth. Is
it the same blockchain transactions that you're able to monitor
or you have to do something different there?

Speaker 1 (29:20):
Yeah, I think it's roughly the same from our perspective.
I would say though that you know, again, if you
think about the risk that someone's willing to take on
a tokenized security, and even like a tokenized equity, you're
starting to get new forms of value transfer, new types

(29:42):
of relationship between the issuer and those assets and maybe
the custodian, and so you started to get like a
more complex financial instrument than we've seen before in the blockchain, right,
And what that means for us is that we help
companies like Securitize think about how to monitor for all

(30:05):
types of manipulation, all types of risk that's involved in
those types of smart contracts. And that's something that we
as chain ours think that that is the future. And
those entities that are helping people tokenize those instruments and
the people that stand behind those instruments are going to

(30:27):
have a need for much greater risk management than even
an asset like bitcoin or ethereum, where you don't have
a counterparty on the other side. And so the moment
that you start to have counterparties and the moment that
these relationships become more complex, the more you need to
actually understand the mechanics of what's happening on the blockchain.

Speaker 2 (30:48):
I did want to get your thoughts on DeFi because
DeFi has had its struggles and its headwinds at its face.
You know, I often say version one point zero of
anything is not great. We've seen a lot of hacks
and vulnerabilities. Are things getting better?

Speaker 1 (31:02):
Yeah? I think things are absolutely getting better. And I
think that you know, I think when you think about
the sort of evolution of you know, compound, are the
curve even sort of balancer even though they recently were hacked.
I mean, you know, the level of sophistication and the

(31:22):
level of scrutiny on these protocols has improved them a
lot since the early days. And I would say that
there's two things that I think about that are really
important for people to pay attention to. One is there
are blue chip defied protocols. There are like really the
top end of the market that have faced sort of

(31:44):
very high levels of scrutiny that have had, you know,
billions of dollars go through them. Those those types of
places are vastly improved from really DeFi one point zero,
which is like now a long time ago. But I
think that, you know, one one thing is the technology
getting better and more robust, and I think that that

(32:07):
is getting a lot better. The other thing, though, is
like the sophistication of the teams is also improving, and like,
I love technology more than anyone, but you have to
understand where technology meets humans. And actually these teams that
are helping you manage and really create these protocols are

(32:30):
now starting to have much more sophisticated mechanisms of pausing protocols,
of intervening when necessary. And actually, you know, I think
that you know, while the original vision of true DeFi
of it being fully decentralized and fully every like code
is law and all of that good stuff, like, there

(32:53):
is like a place in the market for something that's
a bit more hybrid, something that has level of control
that is fully automated and executes permissionlessly, but actually that
there is still some governance behind it, and there is
an adaptability, and there is upgrades, and there is the

(33:13):
ability to have teams intervene in worst case scenarios, and
I think that we are still going to find our
way in terms of our ability to capture the most
value for the consumer from people who are able to
both have the sort of programmability and the predictive nature

(33:34):
of DeFi with some of the controls in place of
the teams that can actually help adapt to crazy circumstances.

Speaker 2 (33:43):
Oh yeah, and then having Chaine Elsis as a resource
to be able to you know, maybe developers and these
folksho are working on things can get a better view
of what's happening behind the scenes and they can build things.

Speaker 3 (33:53):
That are better.

Speaker 1 (33:54):
Yeah.

Speaker 3 (33:55):
I think it's when when on that.

Speaker 2 (33:56):
Front, I know you've got to go soon, So I
didn't want to ask what's on your role map and
we'll hit some wrap up questions.

Speaker 1 (34:02):
Yeah. Sure. So we are really busy at chain oursis
thinking about really building you know, this risk platform that
allows people to monitor for the anti money laundering risk
that we're probably best known for the fraud prevention side
on scams and really all of the security questions that
trad FID tokenization happens, and really anyone in the industry

(34:25):
who's moving money needs to be worried about, and we've
we've built some interesting things and continuing to work on
some things. On the security side. For example, we've built
a model to detect whether your hot wallet is being
compromised or not. We look at anomalous activity and try
and help exchanges counter that type of risk. We've built

(34:48):
products that help with the by bit hack scenario, and
we're constantly responding on the security side to the latest
threats that we are seeing happen on the blockchain. On
the scam prevention side, we're continuing to expand on you know,
everyone's favorite scam and you know, we're not quite in
the romance scam space, but we're definitely we're definitely looking

(35:10):
at every every type of scam type. And then I
would tell you that, you know, on the compliance end
of things, like we're really looking at much more automation,
much more thinking about how do we build more flexibility
into how people are monitoring for those types of risks
and how do they how do they make sure that
there is good decision making happening but you have all

(35:32):
the information at your fingertips. We've done lots of good
stuff on the investigation side. Over the past few months,
and you know, we're really continuing to help law enforcement
find the best ways to look at our data more
holistically as well as you know, seize funds when they
come across it on investigations using a new product that

(35:56):
we're that we put in the market called wallet scam,
which we're really excited about, has already helped seize you know,
hundreds of millions of dollars in criminal proceeds. And so, yeah,
really really excited about you know, the roadmap on both
our public sector offerings and our private sector offerings.

Speaker 2 (36:11):
That's awesome and exciting, and it's good to hear that
the good actors have tools like change alsis because the
bad actors, you know, they're up to no good all
the time.

Speaker 3 (36:21):
So it's a constant battle.

Speaker 1 (36:22):
Yeah, it's a constant game of catamouse. And now the
MYSA are using AI, so we got to we've got
to get better as as cats.

Speaker 2 (36:32):
Oh absolutely, all right, wrap up questions, because I know
you got to go first. If you could create your
own metaverse, would the theme be That's.

Speaker 1 (36:38):
A great question. I think that the theme for me
is actually everyone would ride around my metaverse on a
bicycle and so, you know, I'm a I'm a big cyclist,
and I wish that we lived in the world with
no cars and you know, everyone just moved around space
and bicycles and so I actually, I would love to

(36:58):
live in a metaverse where there were no cars and
you know, only bicycles.

Speaker 3 (37:02):
Awesome rapid fire questions. Favorite food.

Speaker 1 (37:05):
Favorite food is going to be all Japanese food, and
you know that could be anything from you know, sushi
to ramen, to on to really koseki and everything else.

Speaker 3 (37:17):
I love Japanese food.

Speaker 2 (37:18):
And favorite musician or band.

Speaker 1 (37:20):
I'm gonna have to say, hi, am So, I'm actually
h I'm actually engaged to the bass player of High
am So. She's uh, I've been I've been on I've
been on tour with them this year and it's been
you know, yeah.

Speaker 3 (37:35):
She she listens.

Speaker 1 (37:37):
A favorite movie, Usual Suspects.

Speaker 3 (37:42):
Favorite book.

Speaker 1 (37:44):
It's a hard question. I think that uh, you know,
in a in a business context, it's really dense. But
High Output Management by Andy Grove is an incredible book
and something that I think of daily.

Speaker 2 (38:00):
I have to check that one out. We're not working
at chanalysis, what are you doing for fun?

Speaker 1 (38:04):
I'm running by schools in very weird places, and you'll
catch me cheffing every once.

Speaker 3 (38:10):
In a while. Very cool, Jonathan.

Speaker 2 (38:12):
We're going to have to do a round two, maybe
in twenty twenty six, as you continue to roll out
some great products. But thank you so much for joining me.

Speaker 1 (38:18):
No, thanks so much, Sanning, really appreciate it.

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.css-14f5ked{margin:0;word-break:break-word;display:-webkit-box;-webkit-box-orient:vertical;box-orient:vertical;-webkit-line-clamp:2;overflow:hidden;}How Chainalysis Stops Crypto Scams Before They Happen! | Jonathan Levin