“Fraudsters’ mindsets ultimately come down to money and how much they can get out of an attack. We recognized that the cost of circumventing the Arkose Labs solution was prohibitively high, whereas the cost-benefit analysis was in the fraudsters’ favor fo alternative fraud controls.”
“Our first line of defense against organized fraud is the
Arkose Labs solution. We are delighted by the
customization options and the high levels of service and
attention we receive from the Arkose Labs team.”
Priya Bonthu, Engineering Leader.
Fraud and abuse prevention
New Account Registration
Protect tech platforms from fraudsters creating new accounts at scale with the intention of disseminating spam or abusing good users.
Prevent attackers from stealing content and user data through high velocity, malicious scraping attacks.
Safeguard user accounts from ATO attacks and fraudsters carrying out large-scale credential stuffing attacks to hack into user accounts.
Launch promotions to entice new customers with confidence, by preventing fraudsters from taking advantage in order to get sign up credits or free access to platforms.
Stop fraudsters from using bogus or hacked accounts to send spam and other malicious content at scale, aiming to scam users out of money or sensitive credentials.
Secure communication channels from malicious actors looking to target sensitive commercial information or important files shared on tech platforms.
The Arkose Advantage
Powerful Analytical Tools
Get actionable insights into user intent.
Stop Bots Entirely
100% SLA guarantee against bot activity.
A third party acts as a buffer between the bad guys and your business.
Bankrupt the Business of Fraud
Make fraudsters expend resources so it becomes unprofitable for them to continue.
Constantly Learning Platform
Prevent attacks both now and in the future with a feedback loop between risk engine and step up challenge results.
Protect against a wide range of fraud and abuse with a single solution.
Arkose Labs Fraud and Abuse Prevention Platform uses deep analysis to determine the context, behavior, and past reputation of every request. Traffic is then classified and triaged based on its risk profile, with suspicious traffic presented with enforcement challenges that differentiates between true users and fraudsters with certainty. A continuous feedback loop hones this process so fraudsters are faced with time-sapping challenges, while good users are not impacted.