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What is Stripe Radar?

Effectively combat fraud by leveraging the vast network offered by Stripe. With the help of Radar, businesses can efficiently identify and thwart fraudulent activities through sophisticated machine learning algorithms that analyze data from millions of businesses worldwide. Fully integrated into Stripe, it requires no additional setup, allowing you to immediately access its features. While traditional fraud prevention methods often struggle with the demands of modern digital enterprises, Radar equips you to distinguish between legitimate customers and fraudsters, utilizing Dynamic 3D Secure for transactions that are flagged as high-risk. The machine learning framework ensures daily enhancements to the accuracy of the models, including those that can be customized to meet your specific business requirements. Furthermore, Radar's algorithms are designed to quickly adapt to emerging fraud trends while addressing the unique attributes of your organization. Stripe facilitates payment processing in 195 countries, catering to a diverse range of sectors, sizes, and business models. Impressively, even if a card is unfamiliar to you, there is an astounding 89% chance that it has already been screened through the Stripe network, highlighting the extensive reach and dependability of our fraud detection services. This capability not only strengthens your defenses but also ensures that your business can thrive as you navigate the intricate landscape of online transactions, keeping your operations secure and efficient.

What is Fraud.net?

Fraud.net stands as the premier framework for managing fraud, utilizing an advanced collective intelligence network, cutting-edge AI, and a state-of-the-art cloud platform that empowers users to: * Integrate fraud data from various sources with a single connection * Identify fraudulent transactions in real-time with an accuracy rate exceeding 99.5% * Reveal valuable insights hidden within vast amounts of data to enhance fraud management strategies Acknowledged in Gartner's market guide for online fraud detection, Fraud.net offers a robust, real-time solution for fraud prevention and analytics specifically designed to meet the demands of businesses. It serves as a centralized command hub, merging data from multiple sources and systems while monitoring digital identities and behaviors, ultimately employing the latest technologies to eliminate fraudulent activities and facilitate secure transactions. Reach out to us today to start your free trial and experience our services firsthand, ensuring your business is protected against potential fraud.

Media

Media

Integrations Supported

Ekata
Emailage
Signifyd
Stripe
TeleSign
TypingDNA

Integrations Supported

Ekata
Emailage
Signifyd
Stripe
TeleSign
TypingDNA

API Availability

Has API

API Availability

Has API

Pricing Information

¢5 per transaction reviewed
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
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

Stripe

Date Founded

2010

Company Location

United States

Company Website

stripe.com/radar

Company Facts

Organization Name

Fraud.net

Date Founded

2016

Company Location

United States

Company Website

fraud.net

Categories and Features

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

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

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