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ease
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

To safeguard your business's integrity and steer clear of dubious transactions involving high-risk third parties, implementing robust Big Data screening solutions from SAP is essential. By leveraging advanced software, you can enhance your ability to identify and prevent irregularities, thereby reducing the chances of fraud and minimizing financial losses. The SAP Business Integrity Screening application enables swift detection of unusual activities through adaptable rule configurations and predictive analytics, which assist in highlighting possible fraudulent behaviors. Protecting your revenue stream and curtailing losses related to fraud can be achieved by efficiently screening large volumes of transactions to identify anomalies, thereby decreasing the number of false positives. Furthermore, by examining exception-based scenarios alongside behavioral analytics, businesses can prevent future occurrences and develop effective strategies for addressing anomalies and fraud. You can also fine-tune your detection methodologies through calibration and simulation tools, allowing for what-if scenarios based on historical data to evaluate the most successful strategies. This proactive approach not only enhances your fraud detection capabilities but also fosters a culture of vigilance within your organization.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

SAP Joule

Integrations

SAP Joule

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

SAP

Founded

1972

Country

Germany

Website

www.sap.com/products/financial-management/fraud-management.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

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