Ratings and Reviews 56 Ratings
Ratings and Reviews 0 Ratings
What is Fraud.net?
Best-in-class, Fraud.Net offers an AI-driven platform that empowers enterprises to combat fraud, streamline compliance, and manage risk at scale—all in real-time. Our cutting-edge technology detects threats before they impact your operations, providing highly accurate risk scoring that adapts to evolving fraud patterns through billions of analyzed transactions.
Our unified platform delivers complete protection through three proprietary capabilities: instant AI-powered risk scoring, continuous monitoring for proactive threat detection, and precision fraud prevention across payment types and channels. Additionally, Fraud.Net centralizes your fraud and risk management strategy while delivering advanced analytics that provide unmatched visibility and significantly reduce false positives and operational inefficiencies.
Trusted by payments companies, financial services, fintech, and commerce leaders worldwide, Fraud.Net tracks over a billion identities and protects against 600+ fraud methodologies, helping clients reduce fraud by 80% and false positives by 97%. Our no-code/low-code architecture ensures customizable workflows that scale with your business, and our Data Hub of dozens of 3rd party data integrations and Global Anti-Fraud Network ensures unparalleled accuracy.
Fraud is complex, but prevention shouldn't be. With FraudNet, you can build resilience today for tomorrow's opportunities. Request a demo today.
What is Auger.AI?
Auger.AI offers a robust solution aimed at ensuring the accuracy of machine learning models. Our Machine Learning Review and Monitoring (MLRAM) tool plays a crucial role in keeping your models' precision consistent over time. It also evaluates the return on investment for your predictive analytics efforts! MLRAM's compatibility with any machine learning technology stack enhances its flexibility and adaptability. Failing to regularly assess the accuracy of your machine learning system lifecycle could lead to financial losses due to inaccurate predictions. Additionally, the ongoing requirement for model retraining can be expensive and may not resolve issues related to concept drift. MLRAM provides substantial advantages for both data scientists and business stakeholders, including features such as accuracy visualization graphs, performance alerts, anomaly detection, and automated optimized retraining. The process of integrating your predictive model with MLRAM is incredibly straightforward, requiring just a single line of code. We also offer a free one-month trial of MLRAM for qualifying users. With Auger.AI, you can leverage the most reliable AutoML platform available, empowering your organization to enhance its predictive capabilities to the fullest. This comprehensive approach ensures that your machine learning initiatives remain efficient and cost-effective over time.
Integrations Supported
Amazon Web Services (AWS)
Ekata
Emailage
Google Cloud Platform
Microsoft Azure
Signifyd
TeleSign
TensorFlow
TypingDNA
Integrations Supported
Amazon Web Services (AWS)
Ekata
Emailage
Google Cloud Platform
Microsoft Azure
Signifyd
TeleSign
TensorFlow
TypingDNA
API Availability
Has API
API Availability
Has API
Pricing Information
Pricing not provided.
Free Trial Offered?
Free Version
Pricing Information
$200 per month
Free Trial Offered?
Free Version
Supported Platforms
SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux
Supported Platforms
SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux
Customer Service / Support
Standard Support
24 Hour Support
Web-Based Support
Customer Service / Support
Standard Support
24 Hour Support
Web-Based Support
Training Options
Documentation Hub
Webinars
Online Training
On-Site Training
Training Options
Documentation Hub
Webinars
Online Training
On-Site Training
Company Facts
Organization Name
Fraud.net, Inc.
Date Founded
2016
Company Location
United States
Company Website
www.fraud.net
Company Facts
Organization Name
Auger.AI
Date Founded
2019
Company Location
United States
Company Website
auger.ai/
Categories and Features
Click Fraud
Account Alerts
Activity Monitoring
IP Address Monitoring
IP Blocking
Keyword Tracking
Refund Management
Risk Assessment
Time on Site Tracking
Data Visualization
Analytics
Content Management
Dashboard Creation
Filtered Views
OLAP
Relational Display
Simulation Models
Visual Discovery
Decision Support
Application Development
Budgeting & Forecasting
Data Analysis
Decision Tree Analysis
Monte Carlo Simulation
Performance Metrics
Rules-Based Workflow
Sensitivity Analysis
Thematic Mapping
Version Control
Deep Learning
Convolutional Neural Networks
Document Classification
Image Segmentation
ML Algorithm Library
Model Training
Neural Network Modeling
Self-Learning
Visualization
eCommerce
CRM
Catalog Management
Channel Management
Customer Accounts
Data Security
Email Marketing
Inventory Management
Kitting
Loyalty Program
Mobile Access
Multi-Store Management
Order Management
Product Configurator
Promotions Management
Returns Management
Reviews Management
SEO Management
Shopping Cart
Templates
Financial Risk Management
Compliance Management
Credit Risk Management
For Hedge Funds
Liquidity Analysis
Loan Portfolio Management
Market Risk Management
Operational Risk Management
Portfolio Management
Portfolio Modeling
Risk Analytics Benchmarks
Stress Tests
Value At Risk Calculation
Fraud Detection
Access Security Management
Check Fraud Monitoring
Custom Fraud Parameters
For Banking
For Crypto
For Insurance Industry
For eCommerce
Internal Fraud Monitoring
Investigator Notes
Pattern Recognition
Transaction Approval
Machine Learning
Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization
Payment Processing
ACH Check Transactions
Bitcoin Compatible
Debit Card Support
Gift Card Management
Mobile Payments
Online Payments
POS Transactions
Receipt Printing
Recurring Billing
Signature Capture
Predictive Analytics
AI / Machine Learning
Benchmarking
Data Blending
Data Mining
Demand Forecasting
For Education
For Healthcare
Modeling & Simulation
Sentiment Analysis
Categories and Features
Deep Learning
Convolutional Neural Networks
Document Classification
Image Segmentation
ML Algorithm Library
Model Training
Neural Network Modeling
Self-Learning
Visualization