Average Ratings 27 Ratings
Average Ratings 0 Ratings
Description
Frogo delivers a comprehensive fraud prevention platform powered by AI, designed to protect organizations across multiple sectors such as iGaming, financial services, payments, e-commerce, and logistics. Its system monitors user behavior and transaction activity in real time to detect suspicious patterns like brute force logins, unauthorized promo code activations, chargebacks, BIN attacks, or affiliate manipulation. With flexible rule-based scoring, businesses can create or adjust fraud detection policies tailored to their unique risk profiles. Frogo’s multi-layered approach combines static and dynamic rules with predictive AI models, ensuring that both known and emerging fraud schemes are intercepted. The platform provides detailed analytics, customizable alerts, blacklists/whitelists, and investigation modules to empower fraud teams with actionable intelligence. It can also be configured for unique fraud cases, enabling industry-specific defenses. Companies benefit from reduced chargebacks, improved customer trust, and optimized revenue streams by stopping fraud before it causes significant damage. Backed by ISO27001 certification, Frogo ensures compliance, data security, and reliability for enterprises handling sensitive financial and personal information.
Description
To mitigate financial risks and protect their reputations, it is crucial for operators to combat fraud in real-time, especially concerning roaming and national-to-international calls. Many telecommunications providers have implemented various fraud prevention measures; however, the emergence of new technologies continues to unveil additional vulnerabilities. Adopting protective tools against these new attack vectors is often a slow process. As a result, operators are increasingly moving from traditional offline analysis to utilizing network enforcement capabilities that can halt fraudulent calls as they happen. CDR-based systems, which rely on successful call records, unfortunately overlook failed call attempts, limiting their effectiveness to a reactive stance. Consequently, operators are eager to proactively address fraudulent activities at all stages of the calling process. For instance, by tracking the number of call attempts to known black-listed numbers, operators can identify and block PBX hacked devices, as fraudsters typically cycle through multiple numbers before successfully connecting. Moreover, this proactive approach can help in identifying patterns of behavior that are indicative of larger fraud schemes, thereby enhancing overall security.
API Access
Has API
API Access
Has API
Screenshots View All
No images available
Integrations
No details available.
Integrations
No details available.
Pricing Details
No price information available.
Free Trial
Free Version
Pricing Details
No price information available.
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
Frogo.ai
Founded
2025
Country
Cyprus
Website
frogo.ai/
Vendor Details
Company Name
TOMIA
Founded
1999
Country
United States
Website
tomiaglobal.com/real-time-anti-fraud-raf
Product 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
Product 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