Solutions overview
Harness the power of your data to reduce fraud and increase payment acceptance
Tailor-made fraud protection
Detect and stop fraud faster with clear insights
Adaptive solutions for emerging threats
Defend against ATO, promo abuse and seller fraud
Optimize conversion with agnostic authentication
Manage PSD2 and take control of authentication
Online payment fraud
Understand chargebacks, fees & detection
Machine learning for fraud detection
Models, risk scores & thresholds
Link analysis & graph networks
Draw deeper insights from data
Account takeover fraud
Prevention strategies & reputational risk
Policy abuse
Uncover & stop hidden costs
PSD2 & SCA
3D Secure, TRA & exemptions
Global payment regulation map 2022
Track PSD2 & more with a full report
Resource Zone
Deep dives on fraud & payments topics
Blog
The latest fraud & payments updates
API & developer docs
APIs, glossary, guides, libraries and SDKs
About Ravelin
Discover the story about Ravelin
Careers
Join our dynamic team
Customers
Read more about our happy customers
Partners
Join our partner programme
Uncover & stop hidden abuse
Resource zone
Read more about our happy custmomers
Account takeover (ATO) is when a fraudster gains control of a genuine customer account. It causes financial losses, erodes brand value and damages customer loyalty.
Your customized machine learning model is built on your business data for greater accuracy.
Automatically block suspicious logins using machine learning and our breached credential database.
Empower analysts to review orders, devices and successful logins linked to ATO and block further logins.
Help customers keep their accounts to minimize customer churn and protect your brand.
Promotion abuse is when customers unfairly take advantage of your offers. This creates hidden losses for your business, weakens product value and damages the brand image.
Limit single customer or linked network promo usage to prevent losses through referral abuse and sign-up rewards abuse.
Draw insights on how customers use different promotions, hidden losses and impact on customer value and churn.
Enable your team to label promo abusers through manual reviews to stop sophisticated abusers and fraudsters.