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Fraud.net
AI-native cloud platform for enterprise fraud detection, risk scoring, and compliance.
What it does
Monitors digital payment transactions in real time using adaptive machine learning models. Screens and continuously monitors entities for Anti-Money Laundering (AML) and Know-Your-Customer (KYC) compliance. Detects account takeovers and identity theft by analyzing dynamic behavioral signals. Automates case management and custom risk-scoring logic via a no-code rules engine.
Why it works
Global Anti-Fraud Network leverages collective intelligence across global digital transactions. No-code rules engine lets risk teams adjust fraud logic without waiting on engineering deployments. Adaptive AI scoring reduces false positive rates, maximizing valid transaction approval rates. Unified architecture combines transaction monitoring, entity screening, and compliance in one platform.
Category: AI & Automation
Team Size: 26-100
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As of 2026
AI & Automation
Revenue: $1M-$10M ARR
AI-native cloud platform for enterprise fraud detection, risk scoring, and compliance.
Overview
Fraud.net provides an AI-native end-to-end risk management and fraud prevention platform tailored for financial institutions, fintechs, payment processors, and e-commerce enterprises. The solution unifies real-time transaction monitoring, entity screening, and account takeover prevention into a single cloud ecosystem. By connecting proprietary data with its Global Anti-Fraud Network, Fraud.net enables organizations to reduce false positives, prevent fraud losses, and automate compliance workflows.
Funding status: Funded
Revenue source: Subscriptions
Customer type: B2B
Pricing: Subscription
Tech stack: Python, Java, React, Node.js, AWS, REST API
Platform: Web
Integrations: Stripe, Shopify, Salesforce, Magento, AWS, RESTful APIs
Founder story
Fraud.net was founded in 2016 by Whitney Anderson and Cathy Ross in New York City. Drawing on deep leadership experience in financial services and e-commerce, the founders set out to eliminate fragmented fraud prevention tools. They built an AI-native infrastructure that combines real-time transaction scoring, consortium intelligence, and automated compliance into a flexible SaaS platform.
What it does
- Monitors digital payment transactions in real time using adaptive machine learning models
- Screens and continuously monitors entities for Anti-Money Laundering (AML) and Know-Your-Customer (KYC) compliance
- Detects account takeovers and identity theft by analyzing dynamic behavioral signals
- Automates case management and custom risk-scoring logic via a no-code rules engine.
Who it's for
- Banking & Financial Institutions
- Fintechs & Digital Payment Providers
- E-Commerce & Digital Merchants
- Insurance & Credit Underwriters
Why it works
- Global Anti-Fraud Network leverages collective intelligence across global digital transactions
- No-code rules engine lets risk teams adjust fraud logic without waiting on engineering deployments
- Adaptive AI scoring reduces false positive rates, maximizing valid transaction approval rates
- Unified architecture combines transaction monitoring, entity screening, and compliance in one platform.
Growth strategies
- Enterprise co- selling partnerships with global payment gateways and core banking platforms
- Product- led expansion via modular API adoption starting with single risk tools
- Thought leadership and compliance research targeted at Chief Risk Officers and CISOs
- Industry recognition and security awards driving inbound enterprise sales leads
Alternatives
Comparison overview
- Fraud.net provides a modular platform that combines transaction risk scoring, AML screening, and a no-code rules engine.
- Unlike chargeback-guarantee providers like Riskified, Fraud.net focuses on adaptable in-house risk scoring and workflow control rather than taking direct liability.