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Description
No software agent is installed on employee devices, as our application retrieves data directly from the network. This ensures that regardless of whether your organization operates remotely, in a hybrid model, or employs a bring-your-own-device approach, you can effectively monitor employee activities in line with your organizational structure. Investigations can be accelerated by pinpointing atypical behaviors or potential risks, utilizing insights derived from machine learning, advanced analytics, and extensive experience safeguarding major corporations and financial institutions globally. It is crucial to recognize that whether an internal threat is deliberate or accidental, understanding the details is essential. By visually mapping the connections between odd behaviors and users, the identification of insider threats, as well as externally initiated fraud, is significantly streamlined. Our robust system enhances the capability to discern unusual patterns or risks, leveraging a wealth of data enriched by sophisticated technologies and years of expertise in high-stakes security. Ultimately, this comprehensive approach empowers organizations to maintain a secure environment while adapting to evolving workplace dynamics.
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
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
Bottomline
Country
United States
Website
www.bottomline.com/risk-solutions/internal-threat-management
Vendor Details
Company Name
MedCXO
Country
United States
Website
medcxo.com/fraud/
Product Features
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