Frogo Reviews & Ratings

Frogo

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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 TOMIA?

To effectively manage financial risks and safeguard their reputations, it is essential for operators to address fraud in real-time, particularly in relation to roaming and international calls. Although many telecom providers have set up various preventative measures against fraud, the advent of new technologies reveals further weaknesses that require attention. The integration of defenses against these emerging threats is often a gradual process, causing operators to shift from conventional offline methods to leveraging network enforcement capabilities that can immediately stop fraudulent calls in progress. Systems based on Call Detail Records (CDRs), which depend on successful call logs, tend to neglect failed call attempts, which confines their effectiveness to a more reactive approach. Consequently, there is a growing urgency for operators to take proactive steps to tackle fraudulent activities throughout every phase of the calling process. For example, by monitoring the volume of call attempts made to known black-listed numbers, operators can effectively identify and intercept PBX hacked devices, as fraudsters often cycle through numerous numbers before achieving a successful connection. Additionally, this forward-thinking strategy allows for the detection of behavioral patterns that may signal larger fraud operations, thereby bolstering overall security measures. As fraud continues to evolve, the need for innovative solutions becomes increasingly vital for the telecommunications industry.

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

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Integrations Supported

Additional information not provided

API Availability

API Availability

Pricing Information

Pricing not provided

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
On-Site Training

Training Options

Not specified

Company Facts

Organization Name

TOMIA

Date Founded

1999

Company Location

United States

Company Website

tomiaglobal.com/real-time-anti-fraud-raf

Company Facts

Organization Name

Frogo.ai

Date Founded

2025

Company Location

Cyprus

Company Website

frogo.ai/

Categories and Features

Fraud Detection

Not specified

Categories and Features

Fraud Detection

Not specified

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