November 14, 2017
Launched in 2006, Badoo is the largest social discovery network in the world. The London-based tech pioneer has over 326 million members and 400,000 new members join globally every day. Badoo’s vision has always been to stay one step ahead of the curve, pioneering what are now considered more standard features, such as location-based matching and focusing on the importance of privacy, safety and security. Badoo takes payments for premium services, such as Spotlight and Super Powers, which enhance the standard account features. With ThreatMetrix, Badoo could:
- Streamline the online experience by passively authenticating trusted users in real time
- Automate the detection of high-risk payments using dynamic global intelligence from the ThreatMetrix Digital Identity Network
- Reduce requirement for ongoing support for policies/rules and analyst training
- Dramatically reduce the requirement for costly and labor-intensive manual reviews
“We integrated ThreatMetrix four years ago. Since then we’ve consistently managed to maintain a low chargeback rate and high conversion despite what fraudsters throw at us.”
– Matthew Davies, Badoo
When Badoo began accepting card payments, it became a target for fraudsters attempting to use stolen credentials, which led to a high level of chargebacks. Multiple payment service provider (PSP) partners complicated the set up, so Badoo decided it needed an independent fraud detection partner to deal with transactions before they were passed to the PSPs. Badoo was also experiencing high levels of false positives and high dropout rates as a result of increased friction, so it was looking for a provider to optimize its fraud rules and reduce its number of manual reviews.
“The range of functionality ThreatMetrix offers means we can make a bespoke solution for every type of fraudster. We’re constantly testing new rules to make sure we’re a step ahead of the game.”
– Matthew Davies, Badoo
The Power of Global Shared Intelligence to Detect High-Risk Events in Real Time
The best way to tackle complex, global cybercrime is using the power of a global shared network. The ThreatMetrix Digital Identity Network collects and processes global shared intelligence from millions of daily consumer interactions including logins, payments and new account applications. Using this information, ThreatMetrix creates a unique digital identity for each user by analyzing the myriad connections between devices, locations and anonymized personal information. Behavior that deviates from this trusted digital identity can be accurately identified in real time, alerting Badoo to potential fraud. Suspicious behavior can be detected and flagged for review, step-up authentication or rejection before a transaction is processed, creating a frictionless experience for trusted users.
The ThreatMetrix Policy Engine also allowed Badoo to create new fraud rules that have pushed conversion rates up to 98.5 percent and can be constantly modified and fine-tuned to reduce false positives and improve conversion rates.
Key Features of the ThreatMetrix/Badoo Partnership
- ThreatMetrix Trust Tags enable Badoo to differentiate between fraudsters and legitimate users. Trust can be associated dynamically with any combination of online attributes, such as devices, email addresses, card numbers or any other attributes involved in accepting, rejecting or reviewing a transaction.
- ThreatMetrix Smart ID helps recognize returning devices even when cookies are deleted or disabled. Derived from the analysis of many browsers, plug-in, and TCP/IP connection attributes, Smart ID generates a confidence score that detects multiple fraudulent account creations or sign-in attempts from a single device.
- Deep connection analysis technologies give Badoo a clearer view of suspicious events. Fraudsters often attempt to hide behind location and identity cloaking services such as hidden proxies, VPNs and the TOR browser. With Proxy piercing technology, ThreatMetrix examines TCP/IP packet header information to expose the Proxy IP address and True IP address.