Frogo Reviews & Ratings

Frogo

5.0 out of 5 stars

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features 0 out of 5 stars
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Ratings and Reviews 39 Ratings

Total 5 out of 5 stars
ease 5 out of 5 stars
features 5 out of 5 stars
design 5 out of 5 stars
support 5 out of 5 stars

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What is minFraud?

minFraud is a specialized service that supports businesses in fighting against online fraud by providing risk assessment scores and relevant data regarding digital transactions. It’s worth exploring whether the minFraud service meets your organization's requirements. The riskScore is generated in under half a second, employing a mix of machine learning techniques and human evaluation of fraud trends identified throughout the network. This score is derived from a comprehensive dataset comprising over 3 billion online transactions that minFraud analyzes annually for a variety of online businesses. In some scenarios, such as evaluating online behaviors like account logins, incentivized traffic, or application downloads, an IP address may be the only data point available. In these cases, the IP Risk Score allows you to evaluate the risks associated with the IP, which helps in reducing unwanted activities. Moreover, we strongly advise incorporating our device tracking functionality to improve the precision of IP risk assessments, adding another layer of protection against fraudulent actions. By leveraging these tools, businesses are empowered to enhance their defenses against various potential threats in the digital landscape, ultimately leading to a more secure online environment.

What is Frogo?

Frogo is a robust AI-driven fraud detection solution built to safeguard revenue and reduce losses for organizations operating in high-risk industries such as iGaming, payments, e-commerce, forex, banking, dating platforms, and delivery services. The platform addresses a wide variety of fraud cases, from account takeovers and internal fraud to bonus abuse, affiliate fraud, SMS-based scams, and multi-accounting. It detects anomalies by analyzing login patterns, transaction flows, promotional activity, and affiliate behavior, ensuring that fraudulent activity is intercepted before it escalates. Frogo’s hybrid approach leverages static rules, dynamic scoring, and AI predictions, allowing companies to adapt rapidly to evolving fraud tactics. Businesses can create new policies or refine existing ones with customizable scoring engines while monitoring transactions with real-time updates and alerts. Investigators gain access to enhanced analytics and case management tools, helping them pinpoint vulnerabilities and strengthen compliance workflows. The system also integrates blacklist and whitelist management, enabling precise control over user activity. For companies with unique fraud challenges, Frogo can be tailored to specific use cases, providing bespoke protection strategies. With ISO27001 certification and Swiss Approval compliance, it ensures enterprise-grade security and trust. By combining predictive technology with operational flexibility, Frogo transforms fraud prevention into a competitive advantage.

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Media

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Integrations Supported

Decisimo
PremierCashier
Sticky.io

Integrations Supported

API Availability

API Availability

Pricing Information

Pricing not provided
Free Version

Pricing Information

Pricing not provided

Supported Platforms

SaaS

Supported Platforms

SaaS

Customer Service / Support

Standard Support
Web-Based Support

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub
Online Training

Training Options

Not specified

Company Facts

Organization Name

MaxMind

Date Founded

2002

Company Location

United States

Company Website

www.maxmind.com

Company Facts

Organization Name

Frogo.ai

Date Founded

2025

Company Location

Cyprus

Company Website

frogo.ai/

Categories and Features

Fraud Detection

Access Security Management
Check Fraud Monitoring
Custom Fraud Parameters
For Banking
For Insurance Industry
Internal Fraud Monitoring
Investigator Notes
Pattern Recognition
Transaction Approval

Categories and Features

Fraud Detection

Not specified

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