FraudGrade is the world's first one-size-fits-all solution to online fraud. Using artificial intelligence and machine learning to accurately assess the risk related to any potential online customer world-wide on desktop, mobile apps, and mobile browsers.
Requiring only an Email Address and IP Address to perform a review, you can assess risk in the background before the user has even reached a checkout form.
FraudGrade deploys over 17,200+ risk-based fraud rules with a combination of Email Address Validation, IP Address Validation, Domain Validation, Proprietary Data, and Merchant Data to evaluate customers for indicators of fraud. The combined logic of all fraud rules and data validation provides a powerful and highly effective defense against online fraud which can be seamlessly integrated with any online business.
Filter merchant data to check if the email has ever been associated with a confirmed fraudulent transaction.
Determine if the mailbox actually exists and can receive email or if it's fake.
Determine if the email is a disposable address, is blacklisted, and many more fraud risks.
A sophisticated but extremely accurate method to assess risk of online fraud.
A method which requires big data and is proven to successfully assist in determining fraudulent behavior.
Quickly detect if a user is behind a proxy, vpn, tor exit node, or blacklisted.
Providing City, State, Country, and even lattitude/longitude to pinpont the user in question.
Filter merchant data to check if the IP has ever been associated with a confirmed fraudulent transaction.
Over 17,200+ fraud rules that have been generated by screening millions of transactions.
Working with thousands of merchants, we have accumulated the largest list of fraudsters online.
A useful method to assist in the precise detection of fraudsters using custom email domains.
Minimize Fraud, Maximize Profit, Control Cost.
We process thousands of transactions every single day. If we didn't use FraudGrade to assist with risk management, we would need a team of at least 20 people instead of just 2.James DesmondSenior Risk Manager, Trackalytics