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What is VU Security?

We are a cybersecurity company dedicated to thwarting fraud and protecting identities in the digital realm. Our mission is to ensure that both individuals and businesses can engage in secure online interactions effortlessly as they navigate their digital transformations. We deploy a range of technologies to identify individuals by examining their distinct physiological and behavioral characteristics. Once this data is collected, our system establishes a unique pattern for each individual, which acts as a benchmark for future assessments. In addition, we perform transaction analyses of user behavior and create specialized channels aimed at fraud detection and prevention. Our methodology emphasizes the secure and swift exchange of sensitive data, utilizing an encrypted data vault as a reference point. Furthermore, we provide an extensive multi-channel fraud prevention framework that employs machine learning to create intelligent profiles, allowing us to detect potentially fraudulent activities based on user behavior patterns. This proactive stance ensures we maintain a strong defense against cyber threats, and by consistently adapting to new information, we significantly bolster our capacity to combat evolving fraud strategies. Ultimately, our commitment to innovation and vigilance positions us as a leader in the fight against cybercrime.

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.

Media

Media

Integrations Supported

Microsoft 365
PostgreSQL
SQL Server

Integrations Supported

Microsoft 365
PostgreSQL
SQL Server

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

VU Security

Date Founded

2007

Company Location

Argentina

Company Website

www.vusecurity.com/en/soluciones#prevencion

Company Facts

Organization Name

TOMIA

Date Founded

1999

Company Location

United States

Company Website

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

Categories and Features

Fraud Detection

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

Categories and Features

Fraud Detection

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

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