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Description
Rippleshot is a company focused on detecting and preventing fraud, utilizing advanced artificial intelligence and machine learning techniques to assist financial institutions in identifying and addressing card fraud proactively. Their main product, Sonar, processes millions of card transactions every day, helping to pinpoint compromised merchants and cards at risk, which allows for prompt and precise action against potential fraud cases. Furthermore, Rippleshot provides an AI-based tool that empowers financial institutions to develop effective fraud prevention rules without requiring extensive IT support. By implementing these innovative solutions, banks and credit unions can significantly lower fraud-related losses, avoid unnecessary card replacements, and improve the overall satisfaction of their cardholders. This company is reshaping the approach banks and credit unions take towards fraud detection through a cloud-driven technology that employs machine learning and data analysis, making it easier and faster to identify fraudulent activities. Their commitment to leveraging technology ensures that institutions stay ahead in the ongoing battle against fraud, reinforcing trust and security in financial transactions.
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
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
Rippleshot
Founded
2013
Country
United States
Website
www.rippleshot.com
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