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Description

Create, implement, and oversee fraud detection algorithms even if you lack prior machine learning expertise. Utilize your historical data alongside over two decades of Amazon's expertise to develop a precise and tailored fraud detection solution. Begin identifying fraudulent activities right away, effortlessly improve your models with personalized business rules, and apply the outcomes to produce essential predictions. With Amazon Fraud Detector, a fully managed service, customers can swiftly recognize and address potential fraudulent actions, significantly increasing their ability to combat online fraud. This service not only simplifies the model-building process but also allows for ongoing adjustments to keep pace with evolving fraud tactics.

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 Yes 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

AWS AI Services Yes 
Amazon Web Services (AWS) Yes 

Integrations

AWS AI Services No 
Amazon Web Services (AWS) No 

Pricing Details

No price information available.
Free Trial No 
Free Version Yes 

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 No 
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 Yes 
Live Training (Online) No 
In Person No 

Types of Training

Training Docs No 
Webinars No 
Live Training (Online) No 
In Person Yes 

Vendor Details

Company Name

Amazon

Founded

1994

Country

United States

Website

aws.amazon.com/fraud-detector/

Vendor Details

Company Name

MedCXO

Country

United States

Website

medcxo.com/fraud/

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 

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 

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