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What is Subex Fraud Management?

A comprehensive solution exists to combat various forms of fraud. With 25 years of expertise, Subex Fraud Management offers all-encompassing protection for digital services by utilizing cutting-edge machine intelligence and signaling intelligence. This innovative solution merges a conventional rule engine with sophisticated AI and machine learning capabilities to enhance coverage across a wide range of services while reducing the time fraud can operate within the network. Additionally, it features mechanisms for real-time blocking of fraudulent activities. At the heart of the Subex Fraud Management solution lies a hybrid rule engine, which implements detection techniques that include expressions, thresholds, and trends. The rule engine incorporates a diverse array of rules, including threshold, geographic, sequential pattern, combinatorial, ratio/proportion-based, negative, and hotlist-based rules, among others. These various rules empower organizations to effectively monitor and respond to advanced threats that may arise in their networks, ensuring a proactive approach to fraud management.

What is Splunk IT Service Intelligence?

Protect business service-level agreements by employing dashboards that facilitate the observation of service health, alert troubleshooting, and root cause analysis. Improve mean time to resolution (MTTR) with real-time event correlation, automated incident prioritization, and smooth integrations with IT service management (ITSM) and orchestration tools. Utilize sophisticated analytics, such as anomaly detection, adaptive thresholding, and predictive health scoring, to monitor key performance indicators (KPIs) and proactively prevent potential issues up to 30 minutes in advance. Monitor performance in relation to business operations through pre-built dashboards that not only illustrate service health but also create visual connections to their foundational infrastructure. Conduct side-by-side evaluations of various services while associating metrics over time to effectively identify root causes. Harness machine learning algorithms paired with historical service health data to accurately predict future incidents. Implement adaptive thresholding and anomaly detection methods that automatically adjust rules based on previously recorded behaviors, ensuring alerts remain pertinent and prompt. This ongoing monitoring and adjustment of thresholds can greatly enhance operational efficiency. Moreover, fostering a culture of continuous improvement will allow teams to respond swiftly to emerging challenges and drive better overall service delivery.

Media

Media

Integrations Supported

Integrations Supported

AXYVOR
BlueCat Gateway
CloudApper iPaaS
CloudFabrix
Evolven
SAP Store
Splunk User Behavior Analytics
The Galileo Suite

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
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars

Company Facts

Organization Name

Subex

Date Founded

1992

Company Location

India

Company Website

www.subex.com/fraud-management/

Company Facts

Organization Name

Cisco

Date Founded

1984

Company Location

United States

Company Website

www.splunk.com/en_us/products/it-service-intelligence.html

Categories and Features

Anomaly Detection

Not specified

Fraud Detection

Not specified

Categories and Features

AIOps

Not specified

Anomaly Detection

Not specified

IT Alerting

Not specified

IT Service

Not specified

Log Monitoring

Not specified

Root Cause Analysis

Not specified

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