Socure To Address Identity Fraud With Machine Learning, Gets USD30 Million In Series C Funding

Artificial Intelligence News

Socure_To-Address-Identity-Fraud-With-Machine-Learning-Gets-USD30-Million-In-Series-C-Funding Socure To Address Identity Fraud With Machine Learning, Gets USD30 Million In Series C FundingToday, where developments in technologies like Artificial Intelligence and Machine Learning gaining more traction, identity fraud is also taking commonplace in businesses. According to a study, 6.64 percent of consumers, or around 16.7 million people reportedly witnessed to it, in the year 2017. While more than 2.6 million records were stolen or disclosed in over 1,100 data breaches worldwide last year. Keeping this mind, the New York-based leader in high-assurance digital identity verification Socure hopes to put its Cloud-based identity verification and fraud prevention solution.

To stimulate its market expansion and cultivate its sales, marketing, research, and customer support teams, the startup has completed a USD30 million series C funding round. The fund will allow the company to expand its footprint in new markets of the United States that required precise, automated identity verification technology. The funding round was led by Scale Venture Partners, with the participation of contributors Commerce Ventures, Two Sigma Ventures, Synchrony, Flint Capital, along with new investor Sorenson Capital. With this Series C round, Socure’s total capital reached to USD 57.5 million. According to CEO Tom Thimot, with this fund, they will grow their new strategic US market footprint including healthcare and the public sector. He further cited that the company’s workforce grew more than double this year and shifted into a larger office near New York City’s Penn Station. Currently, Socure has six top U.S card issuers and a top five online retailers in its clients’ list, among over 100 other brokers, payment providers, and other companies.

Its digital ID verification suite, called as Aida, leverages a wealth of Machine Learning and Predictive Analytics methods to validate people from thousands of offline and online email, phone, address, social media, and IP data points from over 300 sources in real time.