As more and more of the business world moves into finance, the areas of risk, fraud, and money laundering are growing at unprecedented speed. As a16z theorized in January 2020, in the coming years, every company will be a Fintech company. That means that soon enough, every company will need to start dedicating themselves to serious fraud protection and KYC.
Unit21, founded by Trisha Kothari and Clarence Chio in 2018, is a no-code service that helps companies monitor fraudulent activity online. In October 2020, the San Francisco-based startup raised $13 million to help expand their team — in just two years, they’d already secured business from Chime, Gusto, Intuit, and Coinbase. It was clear as day: Kothari and Chio had built an indispensable tool to combat fraud and AML in the new era of increasingly online finance.
This week, we gave Kothari a call to learn more about what she’s building at Unit21. We also wanted to learn more about the experience of being a female founder in a heavily male space.
I previously worked at the online lending company, Affirm. I was fairly early on there; there were about 10 engineers when I joined. So I got a chance to build a lot of the original engineering systems. By the time I left, I was leading Identity and Risk Product at Affirm. And so I got to see a lot of the ways we made judgments on sudden decisions and that created the spark for starting Unit21.
My cofounder has a background in machine-learning security; he wrote the O'Reilly book on Machine Learning and Security, and was also a lecturer at Berkeley in machine learning. So, we both had some intuition from our prior work experience on what needed to be built.
But we had a really crazy start to Unit21 — through a crazy set of events, we got into an RFP with eBay. And while we did not win that RFP in the end, because we were a very small company, we were the frontrunners and that really helped us realize that this problem that we we're trying to solve is not just something exciting for my cofounder Clarence Chio and me; it’s something that is really needed in the industry.
Yeah, definitely. Even since we started the company, so much has changed, the entire FinTech ecosystem has changed in the last year more than it had over the last 10 years before it. It's really accelerated, which means that compliance and fraud are bigger and more complex issues than ever, especially for financial institutions that have historically lacked the technological talent. So, effectively, what a lot of companies do is they say, 'Okay, that's fine. We'll build an in-house engineering team that will then write these rules, and they will be only focused on this risk and compliance engineering problem." But that's a huge expenditure of resources that could have gone into core product development. The barrier to creating these tools becomes quite high; you are actually spending money that could have been better spent on different parts of the business.
What we've decided to do is we try to look at the problem from a first-principle perspective and see what has changed in the world around us, and what we need to do to make sure that we are actually solving the problem. What has changed in the world around us is that the types of fraud and money-laundering vectors, and the types of data passing from company to company have become more complex. So, we decided to enable the non-technical business owner — the one who gets promoted or fired based off of their success on this job — to be empowered by the tools, rather than to be reliant on the engineering team.
We work with a lot of payments companies and always thought that for payments companies, there's going to be a certain set of fraud, backdoors, etc. But even among two of our payments companies — Intuit, which has a QuickBooks payment product, and Flywire, which is an international remittance product — the type of data that they will have is going to be very different. So, our goal is really to enable a company to look at their level of risk tolerance, to look at their specific dataset, and then to leverage all of that data and make that accessible to a non-technical person to be able to easily write complex statistical models and deploy highly customized workflows without having to talk to engineering.
There has definitely been an increase in online activity, which means the complexity of the fraud vectors are becoming much more complex than in the past. But I think the biggest change is that there's not a one-stop-shop way to solve this. There are really two components to balance.
One is that fraud and money laundering are constantly evolving. It's a constant cat-and-mouse game. So, if you have somebody who is trying to defraud a particular user, even if you try to stop that attempt, you constantly need to be generating new labels for what is potentially fraud, and then feed that into your system. It's never just like, "Okay, I'm done with this." You really have to make sure that you are evolving your fraud strategy and your AML strategy along the way.
The second thing is that people think of fraud and money laundering as a very static thing. But in reality, the easiest way to reduce fraud is to completely halt transactions and growth. But, obviously, that's really a trade off. So, the question becomes: what are you okay with? The answer is going to be different from company to company. That's been really a big insight that we've had. It's a really tricky tradeoff for companies because you don't want to lose a lot of money on fraud, but you also want to grow and not have to stop every user from coming in. So how can you protect yourself from fraud without creating too much friction? The best way is to add more data, to reduce false positives, and to enable the team responsible for the decision to be empowered to make that decision. Our main goal is to make sure that the individuals who are responsible for this part of the business have the tools necessary so that they can be empowered to handle the problem, instead of having to offload the task to an engineering team.
Yeah, it's a good question. I'm the fortunate beneficiary of a lot of progress and gender equality that's happened over the years, and especially over the last half a decade. But it's definitely still a very male-dominated space. It's important that we get more women involved, given that this Fintech era is going to be so instrumental to the future of finance. But I'm optimistic — I think things are moving in the right direction. It's a very unique time where people actually want to promote people and ideas that are underrepresented.
So, I want to encourage female founders and female CEOs to start businesses right now. We definitely need more of that.
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