DataVisor, which provides fraud detection software, announced today that it has raised $40 million in a round led by Sequoia Capital China. Existing investors New Enterprise Associates (NEA) and GSR Ventures also joined.

The software analyzes client data and uses machine learning to identify fraudulent transactions, spam and abuse, identity theft, application fraud, insider abuse, money laundering, and more. It is sold on a subscription basis and can be deployed either on the cloud or in a private datacenter.

The Mountain View, California-based startup uses a technique known as unsupervised machine learning to detect those fraudulent transactions. Unsupervised learning aims to detect patterns within data without first being provided a set of labels for how to categorize that information.

Cofounders Yinglian Xie and Fang Yu spent several years working on computer security at Microsoft Research before founding DataVisor in December 2013.

They shared that the startup has more than 30 customers globally, including Alibaba Group, Cheetah Mobile, Pinterest, Tokopedia, and Yelp.

In this day and age of digital transactions and cloud-based data, cybersecurity is a big concern for companies around the world. Other startups trying to tackle this issue include Feedzai and Sift Science.

To date, DataVisor has raised a total of $54.5 million in disclosed funding. The Series B amount led by Genesis Capital is undisclosed.

DataVisor will use the fresh injection of capital to increase sales and marketing efforts, hire more engineers, and build out product lines to address new use cases.

Rock Wang, managing director…

[SOURCE]