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Description
Feedzai offers a comprehensive AI-driven platform designed to combat financial crime across its entire spectrum—from new account fraud and transaction monitoring to anti-money laundering (AML) compliance. Leveraging advanced behavioral analytics, Feedzai profiles normal customer activity to swiftly detect suspicious or fraudulent behavior. The platform supports real-time risk scoring and fraud prevention across various payment methods and geographic regions. Feedzai is trusted by retail and commercial banks, payment service providers, merchant acquirers, core banking providers, and government agencies worldwide. Its unified approach reduces fraud losses, optimizes operational workflows, and enables secure transactions. Feedzai’s solutions are fully compliant with regulations and integrate easily into existing systems. The platform has demonstrated significant improvements in fraud detection rates, reduction of false positives, and faster model deployment compared to legacy systems. By securing $8 trillion in payments annually, Feedzai is a leader in financial crime prevention and customer trust.
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
CatalystPay
Ekata
Synctera
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
Feedzai
Founded
2011
Country
United States
Website
www.feedzai.com
Vendor Details
Company Name
MedCXO
Country
United States
Website
medcxo.com/fraud/
Product Features
AML
Behavioral Analytics
Case Management
Compliance Reporting
Identity Verification
Investigation Management
PEP Screening
Risk Assessment
SARs
Transaction Monitoring
Watch List
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
Risk Management
Alerts/Notifications
Auditing
Business Process Control
Compliance Management
Corrective Actions (CAPA)
Dashboard
Exceptions Management
IT Risk Management
Internal Controls Management
Legal Risk Management
Mobile Access
Operational Risk Management
Predictive Analytics
Reputation Risk Management
Response Management
Risk Assessment
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