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RSA Fraud & Risk Intelligence Suite: Overview
This overview provides a brief description of typical Adaptive Authentication customer, inputs, the risk engine, and the risk score.
Features
Real time digital channels fraud detection and prevention including transaction monitoring and inbuilt step-up authentication
RSA Adaptive Authentication analyses the risk of user activities in the web and/or mobile channel. The RSA Risk Engine builds profiles of users, IPs, devices, statistical patterns of genuine and fraudulent activity. The risk engine provides the statistical likelihood of a given user activity being fraudulent. The policy manager allows building of business rules on top of the risk engine analysis.
Features
Device Profiling
Device profiling analyzes the device from which the user is accessing an organization’s website or mobile application. RSA Adaptive Authentication compares the profile of a given device with previous devices used by the individual in the past. The device profile is used to determine whether the current device is one from which the user typically requests access or if the device has been connected to previous known fraud. Parameters analyzed include IP address and geolocation, operating system version, browser type and other device settings.
Features
Behavioral Profiling
Behavior profiling is a record of typical activity for the user. RSA Adaptive Authentication compares the profile for the activity with the usual behavior to assess risk. The user profile determines if the various activities are typical for that user or if the behavior is indicative of known fraudulent patterns. Parameters examined include frequency, time of day and type of activity. For example, is this payment amount typical for the user and is the payee someone the user usually transfers money too?
Benefits
Risk Engine
- RSA RISK ENGINE: The RSA Risk Engine is a self-learning, statistical machine learning technology that utilizes over 100 indicators to evaluate the risk of an activity in real time. Datasheet with title “RSA AAOP RiskEngine” attached for reference
- MACHINE LEARNING METHOD: The RSA Risk Engine uses a Naive Bayesian statistical approach to calculating the risk score. A Bayesian approach looks at the conditional probability of an event being fraudulent given the known facts or predictors.
- RSA ECOSYSTEM APPROACH: Leverage existing investments and utilize your own business insights: In addition to proven, predefined risk indicators, the RSA Risk Engine provides organizations the option to ingest their own third party risk indicators to both further enhance fraud detection and augment their existing, current set of Anti-Fraud...
- RSA EFRAUDNETWORK: Cross-institutional, confirmed fraudulent indicators increase your fraud detection (Large percent of fraudulent transactions in RSA Adaptive Authentication have an entry in the RSA eFraudNetwork) Datasheet with title “RSA eFraudNetwork Datasheet” attached for reference
- Omnichannel protection: Protect consumers across channels through a centralized Anti-Fraud hub
- Case management API: Leverage the built-in case management tool or integrate your preferred case management application
App Resources
Case study 1 - HONG LEONG BANK INTRODUCES INTELLIGENT ANTI-FRAUD SERVICES FOR ITS CUSTOMERS WITH RSA
RSA Adaptive Authentication was able to individually profile each of our users’ behavior and to actually continuously learn their new behaviors. We were convinced that the system was able to achieve a high rate of detection and minimize the rate of false positives
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