Stop eCommerce fraud. Offer a seamless user experience.
Oscilar works with ecommerce companies like you who are disrupting the retail market. At the heart of it, real-time and accurate fraud prevention system that powers a safe and frictionless ecommerce user experience. Oscilar enables you to access to the right data at the right time, make changes quickly using a no-code UI, take advantage of sophisticated fraud and risk models, and reduce manual reviews.

Remove transactional friction and maintain safety
Offer a frictionless user experience by flagging only high-risk transactions without overusing the annoying 2-factor authentication. Oscilar continuously analyzes user behavior to detect suspicious transactions in real-time.
Prevent account takeovers and farming
Prevent identity theft
Stop bot attacks
Detect similar or shared properties between supplier and customer (or between customers)
Detect supplier receiving repetitive orders from the same customers
Compute aggregates and historical lists to analyze supplier behaviortically prevent policy abuse
Fewer manual reviews. Faster manual reviews.
Minimize labor-intensive manual reviews by automatically delivering important transaction data to your analysts through a user-friendly interface. Oscilar combines the power of behavior analysis, device, IP, phone, email intelligence with Machine Learning to detect fraudulent transactions accurately. Get intuitive analytics and reporting in real-time at your fingertips to support your decisions.
User behavior analysis powered by machine learning
Historical lists of email, IP, phone, device data
Real-time search, exploration, visualization to rapidly resolve cases
Reduce promotion abuse
Prevent fake accounts and synthetic identities using real-time entity resolution and user behavior analysis. Ensure only valid identities benefit from promotions by preventing multi-accounting using our advanced fraud prevention technology.
Multi-accounting
Fake accounts
Synthetic identities
Oscilar enables you to accurately prevent fraud by synthesizing historic and real-time data signals and enforcing your custom rules.
Powered by machine learning.
risk management platforms at Apple, Uber and LinkedIn.