SAS Fraud Management - Detailed Review

The SAS Fraud Management System

The SAS Fraud Management system, a prominent tool in the finance sector, is equipped with several key features that leverage advanced analytics, AI, and machine learning to combat fraud effectively. Here are the main features and how they work:

Advanced Analytics and Machine Learning

SAS Fraud Management uses embedded profiling and machine learning capabilities to generate real-time, risk-based decisions. This includes patented signature-based analysis technology and advanced analytic modeling controls. These features enable the system to detect and adapt to changing fraud behavior patterns, ensuring more effective and robust models to combat new fraud schemes.

Real-Time Transaction Scoring and Decisioning

The system scores 100% of all transactions in real time using in-memory processing, which delivers high throughput and low latency response times. This capability allows for immediate decisioning on transactions, reducing the risk of fraud and minimizing delays. Transactions are processed at speeds of over 10,000 transactions per second with latency of less than 50 milliseconds.

Single Platform with Multitenancy

SAS Fraud Management operates on a single platform that supports multitenancy, enabling different departments and channels to share the same installation. This simplifies the infrastructure and makes it more efficient for organizations with multiple lines of business.

Simplified Data Management

The system houses all internal and external data from multiple sources on a single platform, using a flexible enterprise orchestration system. This integration allows for a single interface to access data from various client source systems or third-party data providers, making data management more streamlined and efficient.

Alert Management

The alert management feature handles alert resolution, manages payment and risk decisions, performs hot listing and blocking, and conducts downstream fulfillment actions from a single interface. This centralized approach ensures that all fraud-related activities are managed cohesively, reducing the time and effort required to respond to fraud threats.

Real-Time Profiling and Scoring

SAS Fraud Management profiles, scores, and makes decisions on transactions in real time, using millisecond response times. This real-time profiling helps build customer trust by defending against fraud loss while protecting customer loyalty. The system can evaluate both the likelihood of an account being in a fraudulent state and the likelihood of an individual transaction being fraudulent.

Industry-Leading Fraud Analytics

The system uses industry-leading fraud analytics and machine learning to monitor payments, nonmonetary transactions, and events to detect various types of fraud, including payment scams, social engineering, account takeover fraud, and synthetic fraud. It also prevents check fraud and application fraud by assessing risk in real-time.

Cloud-Native Technology

SAS Fraud Decisioning, part of the SAS Fraud Management suite, is built on a cloud-native platform. This allows for scalable, flexible, and cost-optimized operations, enabling organizations to scale up or down according to their business needs and respond quickly to new threats.

Model Management and Governance

The system includes features for model management, governance, and development. It allows for the deployment of custom machine learning models and the transition between different models using champion-challenger capabilities. This ensures that models are continuously updated and improved based on prior results, and it supports responsible AI with embedded model interpretability, fairness, and bias monitoring.

Customer Experience and Operational Efficiency

By reducing false positives and improving the accuracy of fraud detection, SAS Fraud Management enhances the customer experience while minimizing friction. The system’s ability to integrate with case management and reporting systems, along with its customizable data integration and enrichment, simplifies operational processes and increases operational efficiency.

Conclusion

In summary, SAS Fraud Management leverages AI and machine learning to provide real-time fraud detection, efficient data management, and enhanced customer satisfaction, making it a comprehensive solution for financial institutions to combat fraud effectively.