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features
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support

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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

Benford's law serves as a tool for uncovering patterns indicative of improper disbursements. It involves examining audit trail reports from QuickBooks or other bookkeeping software to pinpoint unusual activities like voids and deletions. Additionally, it entails identifying multiple payments made for identical amounts on the same day. A thorough review of payroll runs is conducted to detect any payments exceeding the established salary or hourly rates. Payments made on non-business days are also scrutinized. Statistical calculations help in identifying outliers that may suggest fraudulent activity, and duplicate payments are tested for validation. Vendor files in accounts payable are analyzed for names that may be suspiciously similar, and investigations are conducted to uncover fictitious vendors. Comparisons of vendor and payroll addresses are evaluated using Z-Scores and relative size factor tests. While data monitoring and surprise audits have shown to significantly reduce fraud losses, only 37% of organizations implement these critical controls. For businesses employing fewer than 100 individuals, the average loss due to fraud is estimated at $200,000, highlighting that smaller enterprises often lack the necessary resources to effectively detect and address fraudulent activities. Consequently, it is essential for small businesses to adopt more robust fraud detection mechanisms to safeguard their financial integrity.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

No details available.

Integrations

No details available.

Pricing Details

No price information available.
Free Trial
Free Version

Pricing Details

$1,400 one-time payment
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

MedCXO

Country

United States

Website

medcxo.com/fraud/

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

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