Fraud.net: AI Fraud Detection and Risk Management
Fraud.net helps financial institutions and e-commerce businesses detect and prevent fraud. It is designed for teams that need to support compliance for AML and KYC requirements.
At a glance
- Category
- Browse Security tools
- Best for
- Medium to large enterprises, Financial services companies, Payment processors, E-commerce stores, Fintechs
- Pricing
- Pricing was not clearly available from the provided evidence. Buyers should confirm current pricing on the vendor website.
- Key use cases
- Fintech Onboarding, Merchant Risk Monitoring, Transaction Fraud Prevention, Compliance Automation
- Integrations
- TSYS integration
- Official website
- Visit Fraud.net official website
Fraud.net is a risk management platform designed for medium to large enterprises that handle transaction volumes and require regulatory adherence. It uses machine learning and graph neural networks to identify patterns and entity connections.
The software is designed for payments processors, fintechs, banks, and e-commerce stores. It supports activities from onboarding risk assessment through ongoing transaction monitoring and case management.
Buyers can use the platform to support complex requirements such as Anti-Money Laundering (AML) and Know Your Customer (KYC) compliance. It also includes data orchestration to help unify risk data from different sources.
Buyers should confirm their internal technical capacity for integration and determine if their specific regulatory needs align with the platform's supported compliance frameworks.
Key Features
Risk Scoring
Provides transaction risk scores in under 100 milliseconds using customized machine learning models.
Entity Screening and Monitoring
Supports risk checks during onboarding and monitors entities for suspicious changes.
Anomaly Detection
Identifies behaviors and patterns that deviate from established norms to flag potential risks.
Graph Neural Networks
Analyzes connections between entities to discover hidden high-risk relationships.
Compliance Tools
Supports adherence to regulations including AML, KYC, and KYB requirements.
Data Orchestration
Unifies and enriches data flows to help reduce silos between fraud, compliance, and credit risk teams.
AI Agents
Designed to automate routine fraud analysis tasks and data extraction.
Use Cases
Fintech Onboarding
Using entity screening for identity verification of new users and businesses.
Merchant Risk Monitoring
Performing policy checks and portfolio-level insights for merchant accounts.
Transaction Fraud Prevention
Detecting and blocking fraudulent transactions in real time across payment channels.
Compliance Automation
Managing AML and KYC screening processes to help meet regulatory standards.
Best For
- Medium to large enterprises
- Financial services companies
- Payment processors
- E-commerce stores
- Fintechs
Integrations
- TSYS integration
Pricing
Pricing was not clearly available from the provided evidence. Buyers should confirm current pricing on the vendor website.
FAQ
Who is Fraud.net designed for?
- It is designed for medium to large enterprises, including payment processors, financial institutions, fintechs, and e-commerce businesses.
How does Fraud.net handle compliance?
- The platform provides tools for entity screening and monitoring to help businesses meet AML, KYC, and KYB regulatory requirements.
What is the speed of the risk scoring?
- Fraud.net provides authorization scoring in under 100 milliseconds.
Source category: Security
Source subcategory: Fraud Detection
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Categories
Software Type
How AI is used
Fraud.net is an enterprise risk management platform for financial services and e-commerce companies. It supports fraud detection and compliance workflows using machine learning and entity intelligence. Buyers should evaluate their technical resources as the platform requires integration for data orchestration.
Pros & Cons
Pros
- Transaction scoring under 100ms
- Combines machine learning with a global anti-fraud network
- Explainable AI models for risk score transparency
- Support for AML and KYC compliance
Cons
- Designed for larger organizations
- Requires technical integration for data orchestration and custom model setup
- Pricing is not clearly listed
