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Description
FraudShare is an innovative platform created by LIMRA aimed at tackling account takeover fraud within the financial services sector. It grants users real-time access to data on incidents and threat indicators linked to ATO attacks, allowing businesses to take proactive measures against fraudulent schemes. Users receive prompt email notifications and have the option to access data through export capabilities or an API, which streamlines the process of identifying and averting similar attacks. The platform's correlation analysis features enable organizations to identify and connect related incidents, revealing additional threat indicators that are essential for thorough investigations. Additionally, FraudShare provides valuable industry statistics and trending insights derived from verified fraud cases, helping companies grasp the dynamics and repercussions of ATO fraud. This wealth of information empowers organizations to make strategic choices to bolster their fraud prevention efforts and stay ahead of evolving threats in the financial landscape. Ultimately, FraudShare serves as an essential tool for enhancing collective defenses against increasingly sophisticated fraud tactics.
Description
Safeguard against account takeovers, fraudulent new accounts, and multifactor authentication fatigue with the capabilities of PingOne Protect. This solution assesses various attack vectors, assigns risk ratings, and offers valuable insights, enabling the activation of mitigation tools that thwart potential threats while ensuring that genuine users can authenticate without difficulty. By leveraging intelligence-driven policies, PingOne Protect amalgamates the outcomes of diverse risk indicators to derive a comprehensive risk score. This score is linked to specific policies that dictate the level of friction applied during user interactions, which may include techniques like CAPTCHA, password resets, selfie verifications, and push notifications. Enhance the effectiveness of each predictor, consolidate the predictors, integrate signals from external sources, and implement overrides as necessary. The predictors encompass bot detection, IP velocity, user velocity, anomalous velocity, user location discrepancies, IP reputation, usage of anonymous networks, risk behaviors of users, models of user-based risk, detection of new devices, identification of suspicious devices, and custom or third-party predictors, thereby providing a robust solution to manage risks effectively. By utilizing these comprehensive measures, organizations can significantly bolster their defenses against various forms of cyber threats.
API Access
Has API
API Access
Has API
Integrations
Abstract Security
Knak
Streamline AI
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
LIMRA
Founded
1916
Country
United States
Website
www.limra.com/en/solutions-and-services/regulatory-and-compliance/fraudshare/
Vendor Details
Company Name
Ping Identity
Founded
2002
Country
United States
Website
www.pingidentity.com/en/platform/capabilities/threat-protection/pingone-protect.html
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