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Average Ratings 0 Ratings

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features
design
support

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Write a Review

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

Uncover the concealed links and associations between claimants, providers, and businesses to assist in detecting systemic insurance fraud. The sophisticated analytics offered by NetMap significantly bolster the SIU's capacity to uncover fraud networks within their organization's claims. This software rapidly assesses claim data, public documents, and additional information to highlight patterns that suggest fraudulent behavior. With robust analytics and data visualization tools, SIU analysts can swiftly identify complex patterns of deceitful activities. By condensing weeks of investigative work into just a few hours, NetMap not only enhances the efficiency of organized claims fraud probes but also accelerates the process from detection to referral, ensuring a more effective approach to combating fraud. Moreover, the application of these tools can lead to more informed decision-making and improved overall outcomes for the insurance industry.

API Access

Has API Yes 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

No details available.

Integrations

No details available.

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 Yes 
Mac No 
Linux No 
Chromebook No 

Customer Support

Business Hours Yes 
Live Rep (24/7) No 
Online Support Yes 

Customer Support

Business Hours No 
Live Rep (24/7) Yes 
Online Support No 

Types of Training

Training Docs Yes 
Webinars Yes 
Live Training (Online) No 
In Person Yes 

Types of Training

Training Docs No 
Webinars No 
Live Training (Online) No 
In Person Yes 

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

Verisk Analytics

Founded

1971

Country

United States

Website

www.verisk.com/insurance/products/netmap-analytics/

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 

Product Features

Fraud Detection

Access Security Management No 
Check Fraud Monitoring Yes 
Custom Fraud Parameters Yes 
For Banking No 
For Crypto No 
For Insurance Industry Yes 
For eCommerce No 
Internal Fraud Monitoring Yes 
Investigator Notes Yes 
Pattern Recognition No 
Transaction Approval No 

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