Compare Guardian Analytics Fraud Detection vs. IBM Trusteer

Guardian Analytics Fraud Detection is ranked 14th in Fraud Detection and Prevention while IBM Trusteer is ranked 1st in Fraud Detection and Prevention with 1 review. Guardian Analytics Fraud Detection is rated 0, while IBM Trusteer is rated 9.0. On the other hand, the top reviewer of IBM Trusteer writes "The features were pretty straightforward". Guardian Analytics Fraud Detection is most compared with NICE Actimize, Splunk User Behavior Analytics and IBM Trusteer, whereas IBM Trusteer is most compared with ThreatMetrix, NICE Actimize and IBM Safer Payments.
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287
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1,822
Comparisons
1,187
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1
Average Words per Review
247
Avg. Rating
9.0
Top Comparisons
Compared 37% of the time.
Compared 11% of the time.
Compared 9% of the time.
Also Known As
FraudMAP
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Guardian Analytics
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IBM
Overview

Guardian Analytics Fraud Detection is the first fraud prevention solution to use behavior-based anomaly detection. To complement our expertise in behavioral analytics, we actively study fraudsters’ techniques to make sure we’re always one step ahead. We are also the only solution that automatically and immediately protects 100 percent of users and account holders against all types of threats and schemes, and dynamically adapts to new attacks and changes in legitimate user behavior. In addition to fraudulent payments, we detect account takeover, reconnaissance, and fraud set-up activity that indicate possible criminal activity in the early stages of an attack so our customers can proactively intervene before there’s any money movement. And we do it all without rules and without disrupting users’ normal activity or process.

IBM Trusteer Pinpoint Detect, helps protect digital channels against account takeover, fraudulent transactions, and can detect end user devices infected with high risk malware. Trusteer Pinpoint Detect is a cloud-based solution that can transparently build user profiles and continuously authenticate online identities to more efficiently differentiate between a true user and fraudsters. It is designed to enable a real-time risk assessment with an actionable recommendations, employ behavioral biometrics capabilities to seamlessly build models based on patterns of mouse movements in real-time and analyze patterns against learned user behavior and known fraud patterns, identify access using compromised credentials and provide actionable recommendations to help detect and mitigate fraudulent activities and control and create custom policies to help you rapidly build and deploy countermeasures leveraging machine learning and advanced analytics.
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Sample Customers
Illinois Community Bank, NEFCU
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