Average Ratings 0 Ratings
Average Ratings 0 Ratings
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
No
API Access
Has API
No
Integrations
No details available.
Integrations
No details available.
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Pricing Details
$1,400 one-time payment
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
No
Mac
No
Linux
No
Chromebook
No
Customer Support
Business Hours
Yes
Live Rep (24/7)
Yes
Online Support
Yes
Customer Support
Business Hours
Yes
Live Rep (24/7)
No
Online Support
Yes
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
Yes
In Person
Yes
Types of Training
Training Docs
No
Webinars
No
Live Training (Online)
No
In Person
Yes
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
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