Solution Brief
Manage payment fraud risk without impacting the customer experience
Anticipate, protect and prevent by using modern analytics and embedded artificial intelligence AI techniques
The issue
Global growth of digital payments and customer demands for speed and convenience have redefined the payment landscape. Banks have embraced new payment technologies, but increased digital transactions have introduced new risks and created new requirements for fraud mitigation.
Managing fraud is serious business. And now, perpetrators are finding even more ways to uncover points of exposure and escape detection of fraudulent activity with the help of AI (for example, by using mule accounts or GenAI created communication). Banks must adopt more effective fraud detection and prevention strategies – and fast – because digital payments are rapidly becoming the preferred choice for customers. Already, payment fraud accounts for large risks, both monetary and reputational.
The challenge for banks is limiting losses from false negatives while at the same time minimizing or eliminating customer interruption by declining valid transactions due to false positives. With the sophistication and velocity of attacks, this will require a solution that can correlate events and quickly apply machine learning to identify the greatest threats using real-time decisioning. Based on these insights, banks can decide which alerts warrant action.
The challenge
Insufficient fraud detection systems
Rules-based systems use static logic and flag too many legitimate customers – and fraudsters find ways to test and circumvent them. The SAS payments fraud solutions increase detection accuracy to reduce false positive numbers across all channels.
Lack of predictive abilities
Rules are often designed reactively to reflect knowledge from past known fraud approaches. They can’t spot emerging patterns of future fraud. SAS can detect emerging patterns and proactively identify new types of fraud using predictive alert analytics.
High business costs
Excessive false positives cause customer friction and reputational damage. Inefficient investigative processes drive up costs and investigators’ workloads. The SAS solution helps organizations detect more fraud and provide better customer service while improving operational efficiency and reducing costs.
Organizational complexity
With the expansion of digital banking, multiple portfolios and related business lines across channels, banks have a more complex matrix of offerings to protect. SAS payment fraud solutions incorporate AI and machine learning based on multiple data sources with a variety of detection requirements, providing a real-time enterprise-wide fraud detection system for banks.
Machine learning techniques provide that layer of intelligence that allows us to identify risk situations, analyze them very quickly and intervene when necessary. We have reduced false positives by 40% and increased our ability to handle anomalies by more than 20%.Raffaele Panico Head of Fraud Management and Security Intelligence, Poste Italiane
Our approach
Banks need to balance mitigating fraud and minimizing friction for customers. We approach the problem by providing software and services to help you:
Strengthen data integration and handle higher data volumes
Connect separate data sources, regardless of format or source. Deliver faster results and increase operational efficiency from growing data volumes using in-memory processing.
Improve the customer experience
Reduce false positives by profiling behaviors and using data across each transaction for greater accuracy at the account, customer and product levels.
Monitor, score and render decisions in real time
Integrate with payment systems to score transactions in real time. Monitor new relationships using data and AI to detect subtle patterns of behavior, prioritize suspicious cases and prepare for future risks with predictive alerts.
Empower the system with AI
Improve fraud detection by confirming the most effective machine learning algorithms using champion-challenger evaluations, simulations and benefit estimations.
Prove and improve operational efficiency
Interactively query data and generate networks with web-based data visualizations. Measure program performance by monitoring custom KPIs in dashboards.
SAS difference
SAS provides the highest level of fraud protection with:
Custom data integration
- Define your own path for how each incoming transaction is transformed, enriched and validated before being sent to the fraud management system.
A central decision hub
- Assess activity at multiple levels, combine multiple analytical approaches and provide a unified view of an account/entity across the entire relationship.
Analysis of nonmonetary customer events
- Understand users’ regular device and navigation patterns and evaluate this behavior when transactions are scored.
Machine learning
- Adapts to changing population behaviors via automated model building so that algorithms get smarter and deliver more accurate results.
Alert management
- Intelligently triages events so that investigators can quickly see potential areas of interest and decide where to focus first.
SAS facts
90%
More than 90% of the top 100 global banks use SAS.
1600
More than 1,600 banks worldwide are SAS customers.
92
SAS has banking customers in 92 countries.