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 cross-platform assistant that helps analysts understand cases and make informed decisions faster. It turns Alloy decisioning data, vendor responses, and risk signals into clear explanations of what happened and why a case needs attention. Available across Evaluations, Applications, and Investigations, it gives analysts the context upfront, with access to underlying details and chat to ask follow-up questions about specific findings. Teams spend less time reconstructing cases, approach reviews more consistently, and have clearer documentation to support their decisions.

Alloy AI Agents automate research, manual reviews, and case resolution across risk and compliance workflows. Embedded in Alloy’s orchestration system of record, they use your data, policies, and operating procedures to gather evidence, assess findings, and take permitted actions. Our KYB, KYC, Fraud and AML Investigation Agents can review watchlist matches, examine documents, research businesses, and investigate potential fraud or money laundering. Depending on how the agents are configured, they can resolve cases or escalate them for human review, reducing repetitive work and helping your team focus on cases that need human judgment.

Our AI agents are powered by Alloy’s agentic harness: the infrastructure to configure, test, deploy, monitor, and manage agents. It connects them to the context and tools needed to act within your workflows, with controls over what they can do, when people step in, and how their work is documented.