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Average Ratings 0 Ratings

Total
ease
features
design
support

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Write a Review

Description

Fraudio stands out as a premier provider of solutions for detecting payment fraud and combating money laundering, utilizing an innovative AI system that they have patented to safeguard businesses in the payment landscape. This centralized AI architecture links all clients, fostering significant network effects that improve the effectiveness of fraud detection. Their comprehensive services encompass payment fraud detection, merchant-initiated fraud detection, and anti-money laundering solutions, all structured to deliver exceptional results with a flexible pay-per-use model. The platform is designed for scalable growth, ensuring that it can seamlessly adapt to business expansion without increasing costs. By employing sophisticated machine learning techniques and interconnected datasets, Fraudio enhances real-time fraud detection accuracy, minimizing false positives and operational expenses while increasing transaction approval rates. Furthermore, the AI network connects clients to a centralized brain that has been educated on billions of transactions, reinforcing the platform's robustness and reliability in protecting against fraudulent activities. Ultimately, Fraudio's innovative approach positions it as a trusted ally for businesses seeking to navigate the complex landscape of payment security.

Description

Scalarr offers a cutting-edge solution for mobile ad fraud detection through advanced Machine Learning technology. To combat the most significant threats in mobile advertising, Scalarr employs a dual-layered approach with next-generation algorithms that achieve an impressive accuracy rate of up to 97% in identifying various forms of in-app fraud. Users can experience the benefits of Scalarr by exploring its capabilities to overview, analyze, and thwart mobile app install ad fraud using its unsupervised machine learning features before any harm occurs. The platform utilizes both unsupervised and semi-supervised machine learning techniques to automatically spot and understand fraud patterns across vast datasets. By examining countless clicks, installs, and post-install event variables, Scalarr significantly minimizes both false positives and false negatives in its detection process. With a sophisticated model design prioritizing result accuracy and thoroughness, Scalarr stands out as a robust tool that provides actionable insights at the individual conversion level, ensuring advertisers can make informed decisions regarding their ad campaigns. This comprehensive approach ultimately enhances the overall integrity of mobile advertising strategies.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

Adjust
AppsFlyer
Branch
Kochava
Singular
Tenjin
mParticle

Integrations

Adjust
AppsFlyer
Branch
Kochava
Singular
Tenjin
mParticle

Pricing Details

€1,200 per month
Free Trial
Free Version

Pricing Details

No price information available.
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

Fraudio

Founded

2019

Country

Netherlands

Website

www.fraudio.com

Vendor Details

Company Name

Scalarr

Founded

2016

Country

United States

Website

scalarr.io

Product Features

AML

Behavioral Analytics
Case Management
Compliance Reporting
Identity Verification
Investigation Management
PEP Screening
Risk Assessment
SARs
Transaction Monitoring
Watch List

Product Features

Click Fraud

Account Alerts
Activity Monitoring
IP Address Monitoring
IP Blocking
Keyword Tracking
Refund Management
Risk Assessment
Time on Site Tracking

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