The acquisition will augment the work Razorpay has been doing in AI, machine learning and big data as it looks to improve payment experience and avoid fraudulent transactions
Bangalore: India’s first converged payments solution company, Razorpay, today announced its acquisition of Thirdwatch, an Artificial Intelligence (AI) driven company specializing in big data and machine learning for real-time fraud prevention, for an undisclosed amount.
By applying AI to fight fraud at scale, the Gurgaon-based data science company has significantly boosted Razorpay’s quest to build and introduce innovative technological solutions to facilitate the transformation of Indian economy from a cash driven infrastructure to a less cash ecosystem. Thirdwatch, now a wholly-owned subsidiary of Razorpay will be based at the company’s headquarters in Bangalore.
Considering the changing landscape, the role of fraud has been significantly underrated in economic analysis. Estimates suggest that by FY’22, the Indian e-commerce industry is expected to reach $150 billion. With around 4-5% transactions being fraudulent, Indian ecommerce players will lose over $5bn to fraudulent transactions by 2020.
Over the last four years, Razorpay has been actively involved in solving problems towards strengthening the fintech and banking ecosystem. Acquisition of Thirdwatch is aligned with Razorpay’s long term strategy of building core-competencies in big data and artificial intelligence (AI) by bringing in disruptive minds that can solve unique business problems in the industry.
Excited about its first acquisition, Harshil Mathur, CEO and Co-Founder of Razorpay said, “This acquisition is a perfect fit. Our war is against cash, hence we want to address all problems surrounding it through new integrated data science technologies. Fraud has been the albatross around ecommerce companies’ necks for the longest time and we believe through this acquisition we will empower businesses across industries to digitally transform and disrupt, by improving their response and redressal mechanisms of combating fraud.”
He added, “The team at Thirdwatch comes with an exceptional understanding and expertise in AI, machine learning and data sciences and together we envision a future where AI will help e-commerce firms not just combat fraud but maintain a competitive advantage and significantly improve merchant profitability. Together, I believe we can help reduce frauds by 30-40% by next year.”
Shashank Agarwal, Founder of Thirdwatch said, “We’ve always believed in developing technologies that will not just limit e-commerce transactions to be secure and seamless but also make the systems intelligent with real-time insights through AI. A similar commitment was echoed by the Razorpay team and that’s what impressed us and brought us together.”
He added, “Fraud has been one of the largest and longest concerns for ecommerce companies. Most of their systems frequently fail while identifying fraudulent patterns and therefore not capable of differentiating between genuine customers and fraudsters. There is a dire need for a data driven solution to help identify these patterns and reduce losses of any kind, to help the marketplace function at an optimal level. We are really excited to be part of the Razorpay family, and together, we hope to make AI accessible and helpful to every business, amplifying human gumption with intelligent technology”
Considering the pace at which digital adoption in the country is increasing, with digital transactions growing 50% y-o-y, the problem is becoming even bigger. While there are a number of short-term pressures, Indian companies must start preparing for the future to combat risk of fraud.
Razorpay has been charting an exponential growth since its inception. They grew by 500% in the last one year. They company currently powers digital payments for 3,50,000 businesses like IRCTC, Airtel, BookMyShow, Zomato, Swiggy, Yatra and Zerodha, among others and plans to increase this to 450,000 by 2020. This converged payments solution company expects a 5x growth in its revenue by the end of the next fiscal year.
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