Digital banking has made convenience the norm, but it’s also made fraud inevitable.
The accelerating pace of digital transactions – real-time payments, mobile banking, embedded finance – creates new opportunities for innovation and opens the door to more sophisticated fraud. This is where AI steps in. Not just as a defense mechanism, but as a strategic game-changer for the banking industry.
In this new landscape, banks can no longer afford to simply ask: “Can we detect fraud?” Instead, banks must ask: “Can we detect the unknown in real time, and respond with speed, transparency, and trust?”
That’s the central question addressed in a new SAS white paper, The future of trust.
Why yesterday’s fraud defenses fall short
For years, legacy rule engines were built for predictable threats – not for today’s adaptive fraud tactics. These systems work well for known attack patterns, such as flagging transactions that exceed a certain threshold, come from unexpected locations, or violate timing norms.
But fraudsters evolve quickly. They learn the rules, adapt their tactics, and exploit blind spots. The result? Increasing financial losses, customer frustration from false positives, and a growing need for smarter systems.
Enter AI, the new fraud fighter
AI is transforming the way banks fight fraud, especially through machine learning (ML)-powered anomaly detection and behavioral analytics. Here’s how:
- Uncovering the unknown: ML models analyze vast amounts of transactional and behavioral data to establish what “normal” looks like for each customer. Anything that deviates from this baseline, even if it doesn’t trigger traditional rules, can be flagged. This is essential for detecting account takeover (ATO), synthetic identity fraud, and authorized push payment (APP) fraud, which often evade older systems.
- Reducing false positives: AI doesn’t just detect more fraud; it does so more accurately. By learning from historical data and adjusting to new patterns, ML models reduce the number of legitimate transactions incorrectly flagged as fraud. That means fewer dissatisfied customers and better operational efficiency.
- Real-time transaction scoring: In the age of instant payments, delays can be disastrous. Modern AI triages transactions in milliseconds, keeping speed and trust intact.
- Self-learning capabilities: Fraud tactics evolve constantly. So must your defenses. AI models can now adapt automatically, and this continuous learning keeps defenses evolving without manual intervention.
Meet the future: Agentic AI
The future of fraud prevention is agentic AI – intelligent agents that not only detect fraud but also make decisions autonomously. Imagine a system that doesn’t just flag a suspicious transaction but evaluates its context, weighs the risk, and makes an instant decision to approve, block, or escalate – all without human input.
SAS is pioneering this space with agentic AI that:
- Actively analyzes transaction streams.
- Continuously learns from new fraud vectors.
- Dynamically updates risk models in real time.
- Automatically engages investigation workflows when needed.
These systems will evolve into proactive fraud agents that constantly scan, learn, and act before fraud even occurs.
The future of trust describes how SAS is building agentic AI into fraud decisioning tools and creating systems that don’t just detect fraud but intelligently manage it.
Real-world application: SAS in action
SAS is already helping financial institutions make this critical shift from rule-based systems to intelligent, adaptive fraud prevention. SAS’s hybrid AI-powered fraud detection suite integrates multiple layers of analytics, combining machine learning and real-time decisioning to deliver a multi-dimensional defense.
Key capabilities include:
- Real-time transaction scoring to detect and stop fraud in milliseconds.
- Behavioral analytics that build individualized customer profiles for anomaly detection.
- Consortium machine learning that harnesses shared intelligence across institutions while preserving data privacy.
- Detection of complex threats like synthetic identity fraud, mule accounts, and mobile payment manipulation.
- Integrated case management tools that automate alert investigation and workflow routing.
What sets SAS apart is its cloud-native, API-first architecture, which enables banks to scale detection capabilities quickly and integrate seamlessly with existing tech stacks – on-premises, hybrid, or cloud-based.
And SAS doesn’t stop at fraud. SAS compliance solutions support real-time watchlist screening, anti-money laundering, know your customer (KYC) processes, and transaction monitoring, all underpinned by the power of SAS® Viya®. This unified approach ensures banks can meet evolving regulatory expectations while maintaining operational efficiency.
Balancing innovation with responsibility
AI’s power must be used wisely, especially in highly regulated sectors like banking. Explainable AI (XAI), built-in audit trails, and compliance-friendly model transparency are embedded throughout SAS solutions, helping institutions maintain transparency, fairness, and auditability in every decision made by AI.
SAS incorporates these principles into SAS Viya, ensuring that AI-driven fraud detection is not only effective, but also trustworthy, responsible, reliable, and ethical.
AI is not just an upgrade
AI is not just an upgrade to existing fraud systems. It’s a complete reimagining of how banks protect their customers. With real-time analytics, adaptive learning, and autonomous decision-making, AI is transforming fraud detection from a reactive process to a proactive shield.
As fraud becomes more sophisticated, so must the tools we use to combat it. And with innovations like agentic AI on the horizon, the future of banking security looks not only intelligent but unstoppable.
This is the future of trust – where human oversight and machine intelligence collaborate to safeguard the integrity of the financial system.
