What is SAS Fraud Decisioning?
SAS Fraud Decisioning is a cloud-native fraud detection and prevention solution on SAS Viya that uses real-time decisioning, AI, machine learning, predictive analytics and automated investigation workflows to detect, prevent and manage fraud across the customer life cycle. Organizations use SAS Fraud Decisioning to identify suspicious activity, reduce false positives, improve customer experiences and respond to emerging fraud threats in real time.
How SAS Fraud Decisioning works
SAS Fraud Decisioning helps banks, credit unions, payment providers and other financial institutions detect, prevent and investigate payment fraud, account takeover fraud, application fraud, synthetic identity fraud, check fraud and digital fraud in real time. By combining fraud analytics, machine learning, data orchestration and real-time decisioning, the solution helps you identify suspicious activity earlier, reduce fraud losses, improve productivity and enhance the customer experience.
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Reduce false positives & customer friction
Reduce false positives by profiling customer behavior across transaction types and channels to improve fraud detection accuracy. Integrated alert triage and investigation workflows support both analyst-led reviews and automated decisioning for legitimate customer transactions.
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Respond faster to fraud threats
Profile, score and evaluate 100% of transactions in real time using high-throughput, low-latency processing. Detect suspicious activity and respond to fraud threats immediately while minimizing delays for legitimate customers.
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Gain a holistic view of fraud activity, customer behavior & events
Gain an enterprise-wide view of fraud activity, customer behavior and transaction events across channels. Connect fraud monitoring, investigations and customer interactions to uncover hidden relationships and improve fraud detection decisions.
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Integrate internal & external fraud data
Connect internal systems, external data providers and third-party fraud intelligence sources through flexible data orchestration. Enrich transactions with contextual insights that improve fraud detection, risk assessment and decision accuracy.
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Improve fraud operations & decisioning efficiency
Deploy and optimize machine learning models using champion-challenger testing while developing fraud strategies that combine business rules, anomaly detection and real-time decisioning. Continuously improve fraud detection performance as fraud patterns evolve.
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Scale fraud detection with cloud-native architecture
Support growing transaction volumes with secure, scalable cloud-native infrastructure designed for fraud detection and real-time decisioning. Increase operational flexibility while reducing infrastructure complexity and cost.
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Extend your fraud strategies with advanced fraud models
Accelerate fraud detection with prebuilt fraud models designed to complement your existing SAS Fraud Decisioning environment. These models help organizations identify emerging fraud threats faster while strengthening real-time decisioning across high-volume transaction environments.
Prebuilt fraud models
Deploy production-ready fraud models that are designed for real-time fraud detection and decisioning at enterprise scale, helping teams reduce implementation time and accelerate value.
Advanced threat detection
Leverage broader transaction behavior patterns to identify emerging fraud schemes, suspicious activity and evolving attack vectors earlier.
Seamless strategy integration
Integrate advanced fraud models with existing business rules, machine learning models and decision strategies to strengthen fraud detection performance without disrupting operations.
Fraud detection & prevention use cases
SAS Fraud Decisioning helps financial institutions detect, prevent and investigate fraud across payments, account onboarding, customer authentication and digital commerce channels.
Detect payment fraud threats resulting from scams
Use industry-leading fraud analytics and machine learning to monitor payments, nonmonetary transactions and events to detect payment fraud, payment scams and social engineering.
Uncover money mules & funnel accounts in real time
Detect money mule activity, funnel accounts and account takeover fraud by monitoring customer activities, transaction behavior and account maintenance events across channels in real time.
Catch synthetic fraud faster in new-to-bank relationships
Identify synthetic identities and application fraud earlier by combining identity verification, behavioral analytics and fraud risk assessment during customer onboarding.
Prevent check fraud loss & exposure
Quickly access all data relevant to making a risk assessment of a check transaction, including past customer activity, transaction details and check image analysis discoveries.
Avoid giving criminals access to more credit via application fraud
Prevent bust-out fraud before it arises by assessing the risk of new-to-bank credit applications with a lower referral rate and straight-through processing.
Stop accepting fraudulent e-commerce payments
Detect fraudulent e-commerce transactions across merchants and third-party payment processors while minimizing friction for legitimate customers.
Maximize remote identity verification
Improve digital onboarding and customer authentication by incorporating third-party identity data, fraud signals and verification services into real-time fraud decisions.
Detect emerging fraud threats earlier
Use machine learning, adaptive analytics and prebuilt fraud models to identify changing fraud patterns and emerging attack vectors before they result in significant losses.
Key features
SAS Fraud Decisioning combines real-time fraud detection, fraud analytics, machine learning, data enrichment, orchestration and decisioning; model management and governance; alert triage and case management; dashboards and reporting; and prebuilt fraud models on a cloud-native platform for enterprise fraud management.
Cloud-native fraud decisioning
Deploy fraud detection and decisioning capabilities in cloud environments that can scale to support changing transaction volumes and business demands. Open integration, flexible deployment options and elastic computing resources help maintain performance while optimizing operational costs.
Real-time profiling, scoring & decisioning
Build customer trust by profiling, scoring and decisioning transactions in real time with millisecond response times. Analyze 100% of transactions as they occur to identify suspicious activity, stop fraud losses and protect legitimate customer interactions.
AI-powered fraud detection & analytics
Machine learning, adaptive analytics and anomaly detection techniques help identify emerging fraud threats, uncover hidden patterns and automatically recommend new rules and scenarios. Continuously improve fraud detection accuracy while reducing false positives and adapting to evolving fraud schemes.
Flexible data orchestration
Orchestrate internal and external data sources to provide the context needed for accurate fraud detection and decisioning. Integrate transaction, customer, account and third-party data regardless of source or format while leveraging in-memory processing for high-performance analytics.
Data enrichment & third-party integration
Enrich fraud decisions with customer, transaction and third-party data sources. Configure how incoming events are transformed, validated and enhanced before entering fraud detection workflows, helping improve risk assessment and decision accuracy.
Fraud strategy testing & optimization
Evaluate fraud detection strategies using champion-challenger testing, A/B testing and impact analysis. Compare models, rules and data providers to determine which approaches deliver the best fraud detection performance and customer outcomes, then quickly deploy improvements.
Prebuilt fraud models
Accelerate fraud detection with prebuilt fraud models designed for high-volume, real-time decisioning environments. These models help identify emerging fraud threats earlier by leveraging broader transaction behavior patterns and can be integrated with existing rules, models and fraud strategies.
SAS Viya is cloud-native and cloud-agnostic
Consume SAS how you want – SAS managed or self-managed. And where you want.
SAS Fraud Decisioning frequently asked questions
What is SAS Fraud Decisioning?
SAS Fraud Decisioning is a cloud-native fraud detection and prevention solution on SAS Viya that helps you detect, prevent and manage fraud across the customer life cycle. It combines real-time decisioning, machine learning, predictive analytics, data orchestration and case management to identify suspicious activity, reduce fraud losses and improve customer experiences.
How does SAS Fraud Decisioning detect fraud in real time?
SAS Fraud Decisioning profiles, scores and evaluates transactions as they occur, using business rules, analytics and machine learning models to assess risk and determine the appropriate action. You can analyze 100% of transactions in real time to identify suspicious activity, stop fraudulent transactions and reduce delays for legitimate customers.
What types of fraud can SAS Fraud Decisioning help detect and prevent?
SAS Fraud Decisioning helps organizations detect and prevent a wide range of fraud types, including payment fraud, payment scams, account takeover fraud, application fraud, synthetic identity fraud, check fraud, digital fraud and e-commerce fraud. It can also help identify money mule activity, funnel accounts and other emerging fraud threats.
How does SAS Fraud Decisioning use machine learning and AI?
SAS Fraud Decisioning uses machine learning and advanced analytics to identify patterns, detect anomalies and uncover emerging fraud threats that may be difficult to find with rules alone. You can combine AI and machine learning models with business rules and decision strategies to improve fraud detection accuracy while reducing false positives.
What are SAS Fraud Decisioning fraud models?
SAS Fraud Decisioning fraud models are prebuilt fraud detection models that extend existing fraud decisioning strategies. Designed for high-volume, real-time environments, these models help you identify emerging fraud threats earlier by leveraging broader transaction behavior patterns. They integrate with existing rules, models and decision strategies to strengthen fraud detection without disrupting current operations.
Can SAS Fraud Decisioning integrate with existing data sources and fraud systems?
Yes. SAS Fraud Decisioning can integrate with internal and external data sources, third-party information providers, case management systems and reporting platforms. Flexible data orchestration and enrichment capabilities help you incorporate additional context into fraud decisions and existing fraud workflows.
What are the benefits of cloud-native fraud decisioning?
Cloud-native fraud decisioning enables you to scale fraud detection capabilities as transaction volumes change while maintaining high performance and low latency. It also simplifies deployment, supports continuous innovation and provides the flexibility to run in cloud environments that align with organizational requirements.
How is SAS Fraud Decisioning different from traditional fraud detection systems?
Traditional fraud detection systems often rely heavily on static rules and siloed data. SAS Fraud Decisioning combines real-time data enrichment, machine learning, advanced analytics, business rules, decisioning and investigation workflows in a single platform. This helps you detect emerging fraud threats faster, reduce false positives and make more accurate fraud decisions at scale.