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Description
FraudGuard® stands out as the premier decision-making tool available in today's market, utilizing sophisticated analytics, comprehensive reporting, defect trend analysis, and audit trails that are crucial for a compliant loan origination process. No other automated system can rival the extensive array of data sources and functionalities that FraudGuard integrates into a singular quality assurance platform. Lenders can rely on FraudGuard for superior analytics supported by experienced product support and development teams. By harnessing a mix of public, private, and proprietary data, the FraudGuard platform assists lenders in detecting potential fraud risks and inaccuracies in mortgage applications, ensuring adherence to regulations while enhancing the efficiency and speed of the application review process, ultimately leading to improved loan quality. The platform's advanced reporting capabilities deliver actionable insights and tailored recommendations that are essential for informed loan decision-making, reinforcing its value in the lending process. Thus, FraudGuard not only streamlines operations but also promotes greater trust and reliability in the entire mortgage lending ecosystem.
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
First American Data & Analytics
Website
dna.firstam.com/solutions/mortgage-fraud/fraudguard
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