A SaaS? platform that detects emerging fraud rings, maps attack patterns, and turns frontline fraud signals into automated prevention workflows.
Added Jun 11, 2026
Last signal 2d ago
Companies operating large user, content, commerce, identity, or financial platforms struggle to detect new fraud typologies fast enough across multiple abuse surfaces. Fraud teams need to connect behavioral signals, user feedback, identity activity, content patterns, and forensic evidence into actionable prevention decisions before attacks scale.
The product ingests fraud events, user behavior, identity signals, content metadata, feedback, and investigation notes to surface emerging attack clusters and suspicious fraud rings. It provides risk pattern mining, adversarial strategy recommendations, continuous monitoring, compliance-ready reporting, and case handoff workflows for fraud, risk, and engineering teams.
Job postings show multiple companies investing in ML?-driven fraud defense, risk analytics, continuous monitoring, and automated adversarial strategies. The rise of platform abuse, identity fraud, and coordinated attack rings creates demand for tools that translate fraud intelligence into real-time prevention.
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Conduct investigations to catch fraudsters, enforce our product policies, learn scam patterns/ trends and identify product vulnerabilities. Proactively identify automation and efficiency opportunities and drive solutions through analysis, or cross-functional partnerships.
Develop scalable risk-signal pipelines, rules and model-serving infrastructure, decision systems, and enforcement workflows across the ads lifecycle. Build advertiser-verification, account-risk, abuse-prevention, and fraud-detection capabilities that raise the cost of adversarial behavior.
Help customers evaluate Alterya's fraud detection capabilities and align solutions with their fraud prevention strategies. Design and implement customized fraud detection workflows using AI-driven behavioral intelligence and risk signals.
Research, design, and evaluate detection models that identify automated, fraudulent, and malicious activity across Internet-scale data. Dig into massive datasets to uncover the patterns and behaviors that distinguish adversaries from legitimate users.
We leverage our huge amount of data to identify actors using our platform, mitigate crime and catch fraud cases without creating friction for our genuine customers. In order to do this in a scalable and reliable manner, we have teams dedicated to figuring out the customer behind any event that goes through Adyen, do risk assessment, and make good judgement in real time as well as after the event has taken place.
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