Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
Lengthy document examinations can impede the efficiency of account initiation and underwriting procedures, but relying solely on automation is not a viable solution. We assert that implementing automation without incorporating fraud detection measures can lead to dangerous oversights, which is why Inscribe offers a comprehensive Risk Intelligence solution that not only identifies fraudulent activities but also streamlines processes and evaluates creditworthiness, enabling quicker customer approvals. Depending on mere assumptions to spot altered documents can leave your organization vulnerable to fraud and financial losses. You may find yourself inundated with document assessments, hindering your ability to scale your business while minimizing risk. Our mission has always centered on this challenge, and over the years, we have honed our machine learning algorithms, ensuring they continuously adapt and improve. Thanks to our pioneering efforts, you can trust that our models will consistently deliver the highest level of reliability and effectiveness in the industry, setting a benchmark for others to follow. By choosing Inscribe, you are not just investing in a product; you are securing a partnership that prioritizes your success and safety in a fast-evolving financial landscape.
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
COMBO Network
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
Inscribe
Founded
2017
Country
United States
Website
www.inscribe.ai/
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