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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 Group-IB Fraud Protection?

Join the ranks of over 500 million users who have embraced Group-IB's Fraud Protection solution, leveraging cutting-edge fraud intelligence, device fingerprinting, and behavioral analysis to effectively thwart complex digital fraud. Protect your business from a wide array of fraud attempts with innovative detection capabilities that are state-of-the-art. Streamline your threat response processes to reduce the repercussions of fraud while implementing proactive strategies to avert future issues. Boost customer satisfaction and cultivate trust by ensuring secure and seamless interactions that focus on enhancing the user experience. Utilize automated defense systems to effectively respond to AI-driven attack tactics. Traditional fraud detection methods often prioritize identifying anomalies, which can inadvertently result in a surge of false positives that misclassify legitimate user activities as suspicious, ultimately causing inconvenience to authentic users and squandering valuable resources. In contrast, Group-IB's Fraud Protection takes a more nuanced approach by prioritizing user authentication before entering the fraud detection phase, guaranteeing a more fluid and dependable experience for all users involved. This distinctive strategy not only fortifies security but also promotes a more positive relationship between consumers and businesses, ultimately leading to better overall outcomes. By investing in this advanced fraud protection, organizations can ensure a significant reduction in fraud-related losses and enhance their operational efficiency.

Media

Media

Integrations Supported

Integrations Supported

Group-IB Unified Risk Platform

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

Standard Support
Web-Based Support

Training Options

Documentation Hub
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

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

Group-IB

Date Founded

2003

Company Location

United States

Company Website

www.group-ib.com/products/fraud-protection/

Categories and Features

Fraud Detection

Not specified

Categories and Features

Fraud Detection

Not specified

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