Gauntlet, a financial-risk modeling platform for crypto lending, raised a new round of funding that pushed its valuation to $1 billion.
The $23.8 million Series B round was led by Ribbit Capital, the company said in a statement Monday. Existing investors including Polychain Capital and Paradigm also participated.
Tarun Chitra co-founded Gauntlet in 2018 after about five years at D.E. Shaw Research, the firm led by the billionaire and hedge fund founder David Shaw, and two years at the high-frequency trading company Vatic Labs. He began Gauntlet after consulting with a group of clients whose platforms became decentralized-finance protocols, where smart contracts automatically execute trades without an intermediary. Gauntlet has 32 employees, mainly in New York City.
Gauntlet’s product is akin to running a “stress test” to ensure financial institutions aren’t taking on excessive risks, but on a continuous basis for DeFi platforms, Chitra said. It runs algorithms using data from cryptocurrency exchanges to help DeFi companies decide optimal lending and collateral levels.
His clients include two of the biggest DeFi protocols — Aave and Compound. The companies each pay Gauntlet more than $5 million a year, according to their voting disclosures.
“The data processing is just strictly getting harder,” Chitra said. “We’re trying to invest in our platform, make sure it scales to as many chains as possible.”
Gauntlet plans to use the funding for hiring and expansion into new client categories, including gaming.
Crypto-analytics firms have been popular with venture investors. Last month, Dune Analytics said it reached unicorn status after raising a $69.4 million round led by Coatue.
Another blockchain-analytics firm, Nansen, raided $75 million in December from investors including Accel, GIC and Andreessen Horowitz.
The demand for analytics firms such as Gauntlet also comes with the rise of DeFi, a crypto Wild West where investors sometimes can find double-digit interest rates.
“Some parts of DeFi will advertise very high yields,” Chitra said. “They don’t tell you where the yield is coming from, and you can only figure it out by analyzing the users and the mechanism involved. When we work with a protocol, we do as much diligence on them as they do on us.”
