Chainalysis’ Michael Gronager knows your crypto customer

Michael Gronager once didn’t know what KYC meant. Now his blockchain analytics company is helping the financial world apply it to crypto.

Michael Gronager

Chainalysis CEO Michael Gronager spoke with Protocol about trailblazing blockchain analytics.

Photo: Chainalysis

Michael Gronager found himself on the back foot at a conference in London a decade ago. Then an executive at Kraken, he was chatting up a Mastercard executive who kept mentioning terms like KYC and AML.

“I did not know what they meant,” he told Protocol. “I knew nothing about finance.” Now CEO at Chainalysis, a top blockchain analytics company, he’s solving customer verification problems for a broad range of financial players. In other words, KYC and AML are driving business his way.

Gronager called the incident “kind of funny and a little bit embarrassing,” but it definitely illustrates the kind of dilemma faced by the technologists who were pioneering crypto then.

It was an odd moment for Gronager, who had co-founded Kraken with Jesse Powell after concluding that bitcoin and crypto was “a big paradigm shift in computing.” But that conversation helped shape his path forward: In just a few years, he pivoted to another segment of the crypto industry focused squarely on the finance jargon that befuddled him in London. It was also an area where he could play to his strengths as a veteran big data technologist.

“I could see that there was a need for a scalable process to do origin of funds and transaction monitoring of crypto,” he told Protocol. “There was an opportunity to build a blockchain analytics company. Back then, that didn't exist. No one really understood what that was.”

In an interview with Protocol, Gronager talked about how Chainalysis blazed the trail in on-chain analysis. He also shared his regrets about how blockchain analytics could have softened the blow of the crypto market crash and his hope that the technology will eventually play an important role in derisking the controversial industry.

This conversation was lightly edited for clarity and brevity.

Can you talk about your decision to leave Kraken, where you were a co-founder, to launch Chainalysis?

That's a great question. It's always fun to tell the story again because every time you remember something new and there's another angle.

My entire career has been around big data. I did my Ph.D. in quantum mechanics. I was doing computational physics on different distributed computer systems. I dived into virtual reality. There was big data in terms of 3D models visualized. Then I moved to doing computational physics at CERN, the particle accelerator there.

I stumbled upon bitcoin in 2011. When I saw bitcoin for the first time, I was like, “This is a paradigm shift in computing. This could be something on the size of the internet, if not bigger. And it's something I need to spend time on.” I left my career in the public sector. I dived deep into bitcoin. I was basically trying to figure out: How do you run a business here?

Of course, there were crypto exchanges. But to be honest, I knew nothing about finance. I can tell you a story that is kind of a bit funny and a little bit embarrassing. I was at a conference in London, probably back in 2012. I'm talking to one of the top people of Mastercard in the coffee break before I go on stage. And he's talking about words like KYC and AML. And honestly, I did not know what they meant. So I'm basically trying to Google it before I go on stage. Suddenly I realized, “Ah, oh, yeah, I actually know what that is. I know what they're talking about.”

I'm not from the finance industry. I'm from big data. I joined Kraken because I was probably one of the few people interested in the industry who had a real career, who had a background working at big organizations, building an operational framework, who understood how to work with governments because I'd done that in my research. When I joined the founding team of Kraken, I’d been very, very deep in the source code of bitcoin. I've been contributing to the core protocol, and had built wallet systems that were way ahead of the industry.

Did Jesse Powell invite you to join, and how did that conversation go?

I met Jesse at the first crypto event I attended in New York in 2011. We were both early in the industry. We started talking and basically connected. We had the same views on the industry around a need for running things in a more professional manner. We were looking at the Mt. Gox exchange [hack] and deeply concerned about that. We were discussing [the idea] that someone needs to do something better than that. We stayed in contact from there on. In 2012, I realized that he wanted to build an exchange. I became part of that team and we started building Kraken.

In 2013, FinCEN issued its first guidance around cryptocurrencies. One of the things I keep reminding regulators today when they look back at the industry is everyone in the industry in 2011, 2012, 2013 — they were techies. They knew nothing about finance. There was no idea of this being finance. This was cool. You could buy a pizza with it. Maybe you get rich. That changed in 2013 with the guidance from FinCEN. The banks would not let you use the platform because they were afraid of being part of a money-laundering scheme. They couldn't understand what we were doing.

I realized that with all of the anti-money laundering policies of different countries, everyone talks about transaction monitoring. You could not assess the origin of funds in an online exchange without adding a ton of paperwork and a ton of verification of that paperwork. So I could see that there was a need for a scalable process to do origin of funds and transaction monitoring of crypto. That was the summer of 2014 when we really started to look into those things.

I made presentations for our own banks around what could be done in crypto: It's way more transparent than you think. I had conversations with regulators around the transparency of crypto. I kept saying how transparent crypto is in principle. And they didn’t understand.

One of the things I keep reminding regulators today when they look back at the industry is everyone in the industry in 2011, 2012, 2013, they were techies. They knew nothing about finance. There was no idea of this being finance. This was cool. You could buy a pizza with it. Maybe you get rich.

I basically realized that this is an opportunity. There's an opportunity to build a blockchain analytics company. Back then, that didn't exist. There was no blockchain analytics. No one really understood what that was. That was exactly the company that I wanted to build. I just didn't realize that before that point. I wanted to build something cool in crypto, and it turned out to be blockchain analytics.

I had to leave Kraken. I discussed that with Jesse. He could see it was a good idea. Initially, I was thinking it could be part of Kraken, but it didn’t make sense because it was so different.

There were a lot of people who didn't believe this was even a thing back then. So it was impossible to get funding. There was a belief that crypto was meant to be anonymous, and I was going to break that and that was not right. So there was pushback initially from investors and others.

Can you give an example of a conversation that sticks out for you, maybe an investor or someone saying, “Are you crazy?”

I will not put his name on it, but I talked to an investor who invests in basically everything in the industry and also invested in Chainalysis in the end. I remember sitting in their office.

By mid-2015, I had sold to the FBI and to other government agencies. It was kind of clear that what we are building is useful. But the investor was like, “Yeah, you can sell for like $30,000 to the FBI. But how many other FBIs are there? This is going to be niche.” No one really saw that the size of this market would be counted in billions at some point.

That's a good segue to my next question: How do you make money?

One of the very, very early decisions was basically thinking the most valuable companies on the internet today are selling things online, B2B, and charging money for it. I wanted to build a company where you get recurring revenue, where people subscribe to a service, a good way to grow the revenue over time. The most valuable companies are typically SaaS companies that can build recurring revenue. They have good multiples because there's a lot of stickiness in that revenue. So we did that initially. We are still doing that.

The change that happened in 2015 was the realization that our data and software is actually so powerful, and we don't want it in the hands of the wrong people. So we had to create a vetting process in the sales process where we don't want the FSB from Russia to buy it or others to get access to it. That would today be called enterprise SaaS. It typically moves the deal sizes from thousands of dollars to hundreds of thousands of dollars. So that's where we are today.

We could have predicted that something was about to fall apart.

Our average deal size is more than $100,000. And we see huge growth in our customers because we talk to them a lot. The account sizes are growing 50% year-over-year basically, so there's a lot of growth in the accounts that we are selling to. In the early days, the main customer was government. It still is. So we have 200 public-sector institutions in some 50 countries in the world, roughly, that are our customers. Sixty percent of our revenue today is from the public sector.

They're not touching crypto in terms of buying and selling cryptocurrencies. But they want to be able to trace it. So if a hack happens, if they think it's being used for selling drugs or other things online, they want to trace the funds. They want to build a court case. The product enables them to be smart about crypto and do these investigations. That we ended up becoming a very big business.

Then we have the other side of the business, which is the private sector. In the private sector, the typical customer would be a crypto business. It could be a crypto exchange. It could be a gaming platform. It could be a DeFi platform. It could be others in the crypto space that need compliance and also want to have business intelligence information about their customers.

A lot has changed in the last decade in crypto and blockchain. What has been the most difficult change for the business?

When we see times like the last couple of years, when the entire world was [into] crypto — and we saw that back in 2017, as well — it's actually hard to run a business because, first of all, everyone thinks they're going to be rich tomorrow. Everyone gets weird. You suddenly realize there's a few people in the company who might be key people that suddenly got rich on crypto and don't need to work anymore. I've seen that in Kraken back in the day.

You're basically operating in an ecosystem that’s growing so fast, it's really hard to make the right decisions and do the right things. We have seen some extremely fast bull runs where the market just explodes, capital keeps flowing in, new protocols are being launched, new projects are being launched, and you basically are being pulled in all directions all the time.

I can see the opportunities growing 10x a day, which is amazing. But at the same time, I need to make decisions at a millisecond level in terms of where I should deploy resources. Where should we grow? What should we do? If I make the wrong choice, I might lose out on the biggest opportunity. What we saw last year was hard.

Can you give an example of a decision that was hard, and maybe a mistake that you made?

A good question. One is from the last bull run in 2017. We saw the ICOs. Everyone in crypto did an ICO. They all launched funds that way. Everyone else wanted to do an ICO and everyone was like, “Why are we not doing an ICO?”

My gut feeling told me not to do it. But I wanted to play it out to the team. So I remember an event where we were discussing it and I just pretended to the team that I wanted to do it just to see their reaction. And everyone got a little bit concerned because I was basically telling them we're going to launch an ICO. We're going to raise money this way.

And people are like, “Yeah, but is it legal? We're selling to the SEC as one of our customers. They might not like that we are doing an ICO.” We basically ended up not doing it because of the premise that it's actually not well understood from a regulatory point of view, whether it was legal or not.

Then a few months or half a year later, the SEC actually cracked down pretty hard on ICOs. They felt that this was selling unregulated securities and it was wrong. So I'm happy we didn't do it. But it was also one of these things that had we done it right, it might have been an opportunity. It's hard to say. And I would say this today: I would say I feel that there [could] have been a core piece of regulatory innovation that I could have created to enable the ICOs to be a success.

What do you mean?

What happened in the crypto space in the early days was really interesting. We saw that you couldn't trace cryptocurrencies. It was more and more dangerous and all of that. Because of what we innovated at Chainalysis, it was suddenly not a risk for society anymore. There was no need to go hard on it from a regulatory point of view.

So I always think about every time we see challenges from a regulatory point of view, it's easy to create technology where you can move funds super fast and make investment schemes like we saw with Three Arrows and terra-luna. That's the easy part. The hard part is to create the regulatory technology that enables these technologies to work with low risk or less risk. That's kind of the foundation of Chainalysis.

Every time I see a challenge in the industry, I'm like, “This is an opportunity for us. If we make the right innovation now, we can change the industry.” Otherwise regulators will come in and it's done. I'm always like, “Can we do this fast in that situation?”

I still don't know what we should have done. But I'm always thinking that there might have been a way where we could have enabled regulators to get the right oversight and feel they did the right thing for consumer protection and other things through technology. That would have been an opportunity for the company.

You mentioned Three Arrows and Celsius. What are some of the things that you think could have been done better with blockchain analytics given what happened?

The challenge in the industry today is there's a cross section between traditional finance and crypto. What happens today is that many of the crypto exchanges operate also like traditional finance. Someone is a well-known customer and they will operate on credit. So they will call the exchange and say, “I'm going to buy $10 million of bitcoin tomorrow.” And they say, “OK, you just do it. You can hand in the money later.”

Of course, that happens in traditional finance: Big private equity companies getting loans from very big established banks to buy more private equity that's highly, highly leveraged investments. In the crypto space, we saw the same. We saw it with Three Arrows. We saw it with Celsius and others. Suddenly that's not something I can see on the blockchain. I don't know. I can't see that. So the challenge here becomes: how do we include that information? There were deals happening in terra-luna that were not visible on-chain.

Ifdecentralized means that I'm my own bank, and everything is out of reach of governments, they're wrong.

But I would still say — if I should point fingers at myself and blockchain analytics — I think that when our industry and what we're building at Chainalysis matures even more, there will be a situation where a lot of these schemes and all of these layered investments will actually be more clear. You can build products that can showcase them.

Both on Celsius and terra-luna, we were trying to assess: Could we have predicted this with our data? And the answer was, sadly, yes. We could actually have seen that stuff was going on. We could have predicted that something was about to fall apart. And now, we are, of course, focused on enabling that [kind of prediction].

If we can do these things, it means that that's a very valuable product. It derisks your investment. Suddenly, if you can get early warning that this is falling apart, you can leave in time, and that makes the investment less risky. I think that that product could really help regulate the industry. So I think that there's stuff that can be done in blockchain analytics. But there will be parts where, as I said, if it happens on a phone call, I cannot know about it.

I'm assuming you're using AI to figure these out.

We are. Not on the phone-call side. Not even AI could do that.

Crypto is now 13 years old. What do you say to those who argue that it is no longer as decentralized as it was in the beginning?

If decentralized means that I'm my own bank, and everything is out of reach of governments, they're wrong. But if decentralized means that, like the internet, we build a platform where anyone in the entire world can create a company based on that protocol and participate in that and be a partner in that without any approvals from anyone, then it is decentralized.

Today you can start a business operating on bitcoin in any corner of the globe. You can do that on Ethereum. You can write a smart contract in Bangladesh. You can write a smart contract in Australia. You can write it anywhere on the globe. You can deploy it to the blockchain and you can build a great big business and it's very decentralized and very ubiquitous. Then it's a huge success. And at the same time, you can own it yourself. You don't need a provider. Everything is available everywhere.

But if you then look at the concentration of funds and other things, that will follow another pattern. We will see a concentration of cryptocurrencies. We'll see a concentration of other resources. I think it's a success in that sense. In the sense of the concentration that happens with wealth, that's a law of nature. That's not something we should try to break. It's just how it is. It's fine. It's OK.

But you just described earlier a problem about some transactions that you will not see on the blockchain where people will be able to concentrate their resources and their power to do things that may not be beneficial to everyone.

As the crypto industry grows and it becomes a bigger and bigger part of finance, I think people will see that hiding becomes hard. It's actually hard to hide. Even for North Korea, we've seen they stole a lot of funds over the last year. We have prevented them from cashing out. We have also helped in seizing the funds when they try to cash out. So we have seen that even for a nation-state actor, it's not a free game. You actually meet resistance here, and that's only going to be more in the future. That will be a healthy balance, hopefully.


Judge Zia Faruqui is trying to teach you crypto, one ‘SNL’ reference at a time

His decisions on major cryptocurrency cases have quoted "The Big Lebowski," "SNL," and "Dr. Strangelove." That’s because he wants you — yes, you — to read them.

The ways Zia Faruqui (right) has weighed on cases that have come before him can give lawyers clues as to what legal frameworks will pass muster.

Photo: Carolyn Van Houten/The Washington Post via Getty Images

“Cryptocurrency and related software analytics tools are ‘The wave of the future, Dude. One hundred percent electronic.’”

That’s not a quote from "The Big Lebowski" — at least, not directly. It’s a quote from a Washington, D.C., district court memorandum opinion on the role cryptocurrency analytics tools can play in government investigations. The author is Magistrate Judge Zia Faruqui.

Keep ReadingShow less
Veronica Irwin

Veronica Irwin (@vronirwin) is a San Francisco-based reporter at Protocol covering fintech. Previously she was at the San Francisco Examiner, covering tech from a hyper-local angle. Before that, her byline was featured in SF Weekly, The Nation, Techworker, Ms. Magazine and The Frisc.

The financial technology transformation is driving competition, creating consumer choice, and shaping the future of finance. Hear from seven fintech leaders who are reshaping the future of finance, and join the inaugural Financial Technology Association Fintech Summit to learn more.

Keep ReadingShow less
The Financial Technology Association (FTA) represents industry leaders shaping the future of finance. We champion the power of technology-centered financial services and advocate for the modernization of financial regulation to support inclusion and responsible innovation.

AWS CEO: The cloud isn’t just about technology

As AWS preps for its annual re:Invent conference, Adam Selipsky talks product strategy, support for hybrid environments, and the value of the cloud in uncertain economic times.

Photo: Noah Berger/Getty Images for Amazon Web Services

AWS is gearing up for re:Invent, its annual cloud computing conference where announcements this year are expected to focus on its end-to-end data strategy and delivering new industry-specific services.

It will be the second re:Invent with CEO Adam Selipsky as leader of the industry’s largest cloud provider after his return last year to AWS from data visualization company Tableau Software.

Keep ReadingShow less
Donna Goodison

Donna Goodison (@dgoodison) is Protocol's senior reporter focusing on enterprise infrastructure technology, from the 'Big 3' cloud computing providers to data centers. She previously covered the public cloud at CRN after 15 years as a business reporter for the Boston Herald. Based in Massachusetts, she also has worked as a Boston Globe freelancer, business reporter at the Boston Business Journal and real estate reporter at Banker & Tradesman after toiling at weekly newspapers.

Image: Protocol

We launched Protocol in February 2020 to cover the evolving power center of tech. It is with deep sadness that just under three years later, we are winding down the publication.

As of today, we will not publish any more stories. All of our newsletters, apart from our flagship, Source Code, will no longer be sent. Source Code will be published and sent for the next few weeks, but it will also close down in December.

Keep ReadingShow less
Bennett Richardson

Bennett Richardson ( @bennettrich) is the president of Protocol. Prior to joining Protocol in 2019, Bennett was executive director of global strategic partnerships at POLITICO, where he led strategic growth efforts including POLITICO's European expansion in Brussels and POLITICO's creative agency POLITICO Focus during his six years with the company. Prior to POLITICO, Bennett was co-founder and CMO of Hinge, the mobile dating company recently acquired by Match Group. Bennett began his career in digital and social brand marketing working with major brands across tech, energy, and health care at leading marketing and communications agencies including Edelman and GMMB. Bennett is originally from Portland, Maine, and received his bachelor's degree from Colgate University.


Why large enterprises struggle to find suitable platforms for MLops

As companies expand their use of AI beyond running just a few machine learning models, and as larger enterprises go from deploying hundreds of models to thousands and even millions of models, ML practitioners say that they have yet to find what they need from prepackaged MLops systems.

As companies expand their use of AI beyond running just a few machine learning models, ML practitioners say that they have yet to find what they need from prepackaged MLops systems.

Photo: artpartner-images via Getty Images

On any given day, Lily AI runs hundreds of machine learning models using computer vision and natural language processing that are customized for its retail and ecommerce clients to make website product recommendations, forecast demand, and plan merchandising. But this spring when the company was in the market for a machine learning operations platform to manage its expanding model roster, it wasn’t easy to find a suitable off-the-shelf system that could handle such a large number of models in deployment while also meeting other criteria.

Some MLops platforms are not well-suited for maintaining even more than 10 machine learning models when it comes to keeping track of data, navigating their user interfaces, or reporting capabilities, Matthew Nokleby, machine learning manager for Lily AI’s product intelligence team, told Protocol earlier this year. “The duct tape starts to show,” he said.

Keep ReadingShow less
Kate Kaye

Kate Kaye is an award-winning multimedia reporter digging deep and telling print, digital and audio stories. She covers AI and data for Protocol. Her reporting on AI and tech ethics issues has been published in OneZero, Fast Company, MIT Technology Review, CityLab, Ad Age and Digiday and heard on NPR. Kate is the creator of and is the author of "Campaign '08: A Turning Point for Digital Media," a book about how the 2008 presidential campaigns used digital media and data.

Latest Stories