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- RSA Labs
Implementation of a Fraud Adaptive Authentication recommendation engine. This engine would monitor the state of a customer’s environment and raise suggestions to help prioritize AA configuration changes or future investment to reduce digital risks.
Customers frequently struggle to effectively utilize the AA product and features. Therefore, they may face more threats and potential fraud losses.
There are many causes of these struggles:
- Lack of visibility into current threads and fraud patterns.
- System mis-configuration or implementation issues.
- Data source silo’s leading to poor visibility, intelligence and business context.
A recommendation engine can provide improved guidance by utilizing several KPI’s and associated risk scores. This engine would leverage insights gathered from:
- Overall AA implementation data sources
- Product performance in terms of data losses
- Customer performance in terms of fraud losses
- Customer product engagement and feedback
- Customer activity in the RSA anti-fraud community network (EFN, Link)