Fraud.net provides AI and machine learning models that detect and prevent fraud across finance, e-commerce, insurance, and other industries.

Fraud.net provides AI and machine learning models designed to detect and prevent fraud across many industries. The platform uses deep learning, neural networks, and proprietary data science methods to identify and stop fraudulent activity.
Its solutions serve sectors including financial services, e-commerce, travel, hospitality, insurance, wealth management, and consumer lending. The platform offers four core tools:
Fraud.net can detect many types of fraud, including account takeovers, application fraud, synthetic identity fraud, business email compromise, and collusion. It also supports KYC/AML processes, payment fraud detection, and mobile fraud prevention.
Additional capabilities include multi-factor authentication, continuous risk monitoring, dark web intelligence, ISP intelligence, and a Collective Intelligence Network for sharing fraud insights across organizations. A Fraud Dictionary helps users learn key terminology, and the company publishes case studies, industry reports, webinars, and API documentation for developers.
One caveat: the platform doesn’t always clearly adhere to data privacy regulations and may require significant setup to perform at its best.
Shakti Jauhar, the CEO, created Fraud.net. The company’s goal is to provide AI and machine learning models that detect and prevent fraud across industries.
The platform is built for professionals who need a system to fight fraud, including CEOs and directors, technology and security officers, and fraud managers and analysts.
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