Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
Enforcement offers a robust defense that deters fraudsters from conducting attacks in the first place. Arkose Labs employs a cutting-edge method of step-up authentication that introduces varying levels of risk-based friction, thereby exhausting the resources of fraudsters while providing genuine customers with an enjoyable means to validate their identity. This enforcement mechanism operates as a challenge-response system, working seamlessly with Telemetry to verify requests that are unfamiliar. As a result, only authentic interactions are forwarded to the enterprise, ensuring that digital businesses can confidently engage with true customers. Arkose Labs’ strategy effectively transfers the focus of potential attacks from the business itself to their own platform, thereby enhancing security. By rerouting dubious sessions to an independent verification platform, a protective barrier is established between fraudsters and their usual targets, transforming the landscape of attack strategies. Consequently, businesses can conserve their valuable resources and efforts, no longer needing to address the fallout from attacks. This innovative approach not only safeguards transactions but also reshapes industry standards for online security.
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
No
API Access
Has API
No
Integrations
Anti-Captcha
No
Arkose MatchKey
No
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Customer Support
Business Hours
Yes
Live Rep (24/7)
No
Online Support
No
Customer Support
Business Hours
Yes
Live Rep (24/7)
No
Online Support
Yes
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
Yes
In Person
Yes
Vendor Details
Company Name
Arkose Labs
Founded
2008
Country
United States
Website
www.arkoselabs.com
Vendor Details
Company Name
TOMIA
Founded
1999
Country
United States
Website
tomiaglobal.com/real-time-anti-fraud-raf
Product Features
Cybersecurity
AI / Machine Learning
Yes
Behavioral Analytics
Yes
Endpoint Management
Yes
IOC Verification
Yes
Incident Management
Yes
Tokenization
Yes
Vulnerability Scanning
Yes
Whitelisting / Blacklisting
Yes
Product Features
Fraud Detection
Access Security Management
No
Check Fraud Monitoring
No
Custom Fraud Parameters
No
For Banking
No
For Crypto
No
For Insurance Industry
No
For eCommerce
No
Internal Fraud Monitoring
No
Investigator Notes
No
Pattern Recognition
No
Transaction Approval
No