DataVisor collects $40m for fraud detection, AML solutions

DataVisor, a provider of fraud detection solutions, has closed a $40m Series C round, led by Sequoia Capital.

The round, which also feature participation from existing investors New Enterprise Associates and GSR Ventures, will see Rock Wang, managing director at Sequoia China, join DataVisor’s board of directors.

Founded in 2013, DataVisor’s fraud detection solutions use machine learning to identify various types of fraud and abuse, including fraudulent transactions, fake content, spam and abuse, identity theft, application fraud and money laundering. Its full-stack risk platform provides end-to-end protection against attacks by modern cybercriminals, and is based on a combination of a proprietary unsupervised machine learning engine and aggregated digital information from DataVisor’s Global Intelligence Network.

Headquartered in Mountain View, California, and with offices in Beijing and Shanghai, the company plans to use the new funds to expand its global footprint in the fraud detection and prevention market.

“Online fraud is on the rise in China and globally and many enterprises are investing in advanced artificial intelligence (AI) solutions to tackle the threat. DataVisor’s platform delivers best-in-class technology,” said Neil Shen, founding and managing partner of Sequoia China.

“DataVisor’s solution is the first proven unsupervised machine learning technology successfully deployed at scale. Its platform uniquely identifies new and unknown fraud signals, which means that businesses can stay a step ahead of the fraudsters instead of lagging behind. The company has shown great momentum and we are excited to partner with the team to support its continued growth.”

Using unsupervised machine learning, DataVisor claims to provide the ‘industry’s most advanced’ AML transaction monitoring solution that can drastically reduce false positives and false negatives compared to current TMS solutions.

With traditional transaction monitoring solutions relying on rules or supervised machine learning models that require constant tuning as bad actors, DataVisor’s engine analyzes hundreds of millions of accounts and events to identify hidden patterns between accounts. As well as reducing false positives while increasing detection coverage, by creating human-understandable rules, DataVisor’s solutions allows clients to meet strict compliance requirements.

The company claims to have protected more than 2 billion users globally from some of the largest financial institutions and Internet properties in the world, including Pinterest, Yelp, Alibaba Group, Dianping, Toutiao, Cheetah Mobile and Tokopedia.

Copyright © 2018 RegTech Analyst

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