Fraud is not a new problem. Some historians date back to 300 BC, when a Greek merchant by the name of Hegestratos took out an insurance policy on his boat filled with corn with the intention of sinking it and collecting money from it. ‘insurance. A few millennia later, fraudsters are more likely to surf the web than on the high seas.
But modern crooks face a challenge at Forter, which just closed a $ 300 million oversubscribed venture capital round to further expand its fraud detection activities in online transactions through machine learning. Tiger Global Management, a prolific Silicon Valley company, led the Series F funding round, which nearly tripled Forter’s valuation to $ 3 billion in the half-dozen months since its previous cycle. Third Point Ventures and Adage Capital Management also joined Forter’s latest capital injection, alongside existing investors including Bessemer Venture Partners and Sequoia Capital.
It’s no secret that e-commerce has exploded during the pandemic: in the United States alone, digital retail sales totaled $ 791.7 billion in 2020, up 32.4% from compared to 2019, according to recent Census Bureau data. Of course, the same goes for fraud. Forter CEO Michael Reitblat is loath to disclose specific tactics popular with scammers so as not to inspire underhandedness Forbes readers, but he notes that fraud related to unattended frequent travelers and hotel points has jumped. Likewise, Forter grew its customer base by roughly 70% and nearly doubled its annualized revenue in 2020 to around $ 116 million.
“I almost feel bad to say that it is interesting to see how creative fraudsters are,” says Reitblat. Since its inception in 2013, the New York-based company has raised more than $ 500 million in venture capital and employs more than 300 people.
How does Forter work? The company says its algorithm analyzes thousands of data points to “holistically” rate every online transaction, item return, or loyalty point redemption that occurs at a customer’s site. The system typically replaces a customer’s internal fraud detection program that might refuse transactions that meet certain general criteria, for example, if a potential buyer lives in a country with a high percentage of fraudulent transactions. Forter claims to process roughly $ 250 billion in transactions per year, up from $ 100 billion at the end of 2019 (in 2018, Forter was processing a meager $ 50 billion per year).
“We don’t want to generalize, we don’t want to say ‘this address is bad’, because an address is neither good nor bad,” explains Reitblat. “People can be bad, they can do bad things. Everything else is circumstantial, so we want to make sure we let all the right people through.
Forter’s clients cover the digital economy. Notable names include Nordstrom, Sephora, Instacart, and Burger King. Travel booking site Priceline started using Forter in 2018 after seeing a false “stubborn” rate of decline, says Eric Lorenz, vice president of strategy and operations at Priceline. Priceline’s problem was not unique; Retailers can lose significant revenue due to transactions that are inappropriately declined because they simply appear problematic. A 2019 report predicted false declines could cost traders and issuers around the world a combined $ 443 billion in revenue by 2021, when actual fraud is expected to reach $ 6.4 billion. (The results come from a study by the AITE group commissioned by ClearSale, a small fraud prevention company founded in Brazil.) On average, Forter claims to mitigate 85% of false declines, while blocking 75% of fraudulent transactions.
“We saw the opportunity in this space as not really focusing on reducing fraud, but giving retailers the peace of mind or the assurance that they can sell without fear of fraud,” says Rajesh Ramanand, CEO of Signifyd, a San Fraud Detection Company based in Jose, Calif., which competes with Forter. Ramanand, who previously worked as a risk manager at PayPal, points out that demand for the Signifyd product as well as revenue nearly doubled last year. According to him, the company now processes “hundreds of billions” of transactions each year.
Launched in 2011, Signifyd is one of Forter’s main rivals. The 450-person company got a valuation of $ 1.34 billion in mid-April via a $ 205 million funding round led by Owl Rock Capital, and its clients include Samsung, Rite Aid and the Spanish clothier at Mango fashion. Forter’s second major competitor is Riskified. Founded in 2012, the New York and Tel Aviv-based company earned a unicorn valuation in 2019 after closing a $ 165 million round led by General Atlantic, and it employs more than 500 people. Riskified clients include Canada Goose, Wayfair and Prada. These three category leaders all use machine learning algorithms to detect fraud or its absence, and they offer to reimburse merchants for chargebacks related to fraudulent transactions that have not been approved.
It’s still anyone’s game, but Forter is hoping the depth of its data will help it triumph. (Its database covers over a billion customers worldwide.) Reitblat uses a metaphor of vaccination to describe its value: “Let’s say a new fraudster attacks one of our customers, then we find out how stop it. From that point on, all of our other customers are almost immune to the same attack. ”
This righteous cycle has a benefit for Forter, says Elliott Robinson, an associate in Bessemer’s San Francisco office who participated in the round and led his $ 125 million Series E in November. “Data is the new oil,” he quipped. “Forter was the first company to combine all the data.”
Forter is eight years old, but Reitblat and his two co-founders have been immersed in fraud prevention for decades. Reitblat began his career in the Israeli military intelligence unit before joining Fraud Sciences, an Israel-based online fraud detection company that was acquired by PayPal in 2008 for $ 169 million. Its co-founders, Liron Damri and Alon Shemesh, also worked at Fraud Sciences, but Reitblat first met Damri at boarding school.
“We’ve figured out that the way e-commerce works, fraud will always be a problem,” says Reitblat.