MOZN announced a major leap in its Enterprise Fraud Management (EFM) solution with the introduction of AI Rule Builder, empowering fraud teams to turn control decisions into production-ready fraud rules in minutes instead of waiting days for engineering and QA cycles. The first of its kind in the region, MOZN AI Rule Builder brings natural language rule creation into a unified enterprise fraud management solution, enabling institutions to generate, govern, and deploy high‑impact fraud rules at unprecedented speed while staying tightly aligned with existing data models and real‑time processing constraints.
As fraud attacks become more automated and adaptive, financial institutions face growing pressure to close the gap between identifying a new threat and enforcing the control needed to stop it. In many organisations, even when fraud teams know exactly which behaviour they want to block or scrutinise, translating that intent into optimised rule logic, engineered variables, and tested deployments can still take days, stretch response times and leave exposure windows open longer than they should be.
MOZN’s AI Rule Builder addresses this challenge by allowing users to describe their intended controls in plain language and automatically generating the corresponding rule expressions across a wide range of scenarios. From simple rules to advanced patterns that use velocity-based variables and time-based aggregations, the capability is designed to accelerate how institutions create and maintain the rules that power real-time fraud defences.
AI Rule Builder extends MOZN’s AI-native Financial Crime Prevention solution by adding an intelligent rule creation layer to its broader fraud decisioning architecture. Within a single FRAML environment, institutions can detect suspicious activity in real time, design and adapt both simple and complex fraud rules faster and manage investigations on the same shared data and case management foundation.
Powered by advanced large language models, the feature intelligently translates natural language prompts into rule logic aligned with the institution’s data structure, field availability, and streaming engine requirements. The generated rules are presented in a clear, human-readable format, allowing users to review, refine, and approve conditions, thresholds, time windows, and risk scores before activation, with full traceability for model risk and governance functions.
“With AI Rule Builder, we are fundamentally transforming how fraud controls are created and operationalised,” said Malik Alyoussef, Co-founder, Chief Product & Technology Officer, MOZN. “Fraud prevention can no longer depend on static rules and delayed response cycles. By using generative AI to handle the heavy lifting of rule construction, we empower fraud teams to respond to emerging patterns at the speed of thought, while maintaining the transparency and oversight required for enterprise-scale compliance.”
MOZN is focused on helping institutions address the wider, end‑to‑end challenges of financial crime prevention. In close partnership with strategic forward‑deployed teams, MOZN pairs its AI‑native EFM platform with embedded, Arabic‑speaking experts who help institutions modernise controls, streamline investigations, and align change with regulatory expectations. Together with an award‑winning EFM solution recognised by Chartis, Forrester, and IDC, this ecosystem ensures that innovations translate into stronger, end‑to‑end protection for customers and the financial system.
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