Alloy uses portfolio- and account-level machine learning models for risk assessment in real time. These models analyze identity, behavior, and activity signals to detect anomalies as they emerge, from coordinated onboarding attacks to downstream fraud and financial crime. This approach allows financial institutions and fintechs to apply AI flexibly, combining models trained on historical fraud data with adaptive intelligence that surfaces new and evolving attack patterns.

Alloy pairs AI-powered detection with automated response workflows. Once risk is detected, Alloy can contain the threat through policy adjustments, step-up checks, and investigations triggered in real time, allowing teams to control exposure while minimizing disruption to good customers.

Fraud Attack Radar is a specialized AI-driven fraud detection tool that is purpose-built to spot large-scale fraud attacks in your onboarding funnel. Fraud Attack Radar connects patterns across applications to detect coordinated attacks in real time, so your team can act immediately. By using Fraud Attack Radar within the Alloy platform, you can immediately contain mass-scale threats and remediate impacted channels while keeping legitimate customers moving forward in the funnel.

Sometimes, a fraud problem becomes too complex for static decision trees or rule-based systems. In situations like these, multiple weak indicators can combine into a high-risk pattern that no single data solution could detect alone. 

Fraud Signal is a machine learning fraud model that scores risk at the customer level, looking beyond single transactions to capture behaviors across a customer’s application, account, and interactions. It works by combining real-time onboarding data, behavioral signals, and both monetary and non-monetary activity, using pattern recognition to adapt continuously to new tactics and reducing false positives. Fraud Signal can help uncover patterns such as account takeover attempts, money mule activity, and new account fraud.

The Alloy AI Assistant is a native, context-aware AI agent embedded directly within our risk and identity infrastructure. It delivers against a range of purpose-built skills and use cases across fraud and compliance. Rather than deploying separate tools or copilots, Alloy provides one cohesive assistant that works across onboarding, investigations, and ongoing risk management. It’s designed to handle operationally heavy, non-predictive workflows that require completing many interconnected tasks, from suspicious activity reports to complex KYB investigations. Alloy’s AI Assistant works in tandem with Alloy’s decisioning engine, using context from workflows to help prioritize high-risk alerts and progress decisions forward.

Alloy’s AI Assistant is designed to bring agentic automation to any action driven by a standard operating procedure (SOP), giving teams the option to delegate any manual step in the application and investigation review process to AI. It can help reviewers triage alerts, gather and check information, and directly implement suggested next steps. And it's equipped with built-in controls, explainability, and auditability to support human oversight. With predictive intelligence handling probabilistic decisions (e.g., fraud scoring), Alloy’s agentic intelligence expedites procedural work that can’t be straight-through processed (e.g., investigations, data summaries, AML compliance reviews, and verifications).