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features
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support

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Description

Anticipate issues before they arise by utilizing an Azure AI anomaly detection service. This service allows for the seamless integration of time-series anomaly detection features into applications, enabling users to quickly pinpoint problems. The AI Anomaly Detector processes various types of time-series data and intelligently chooses the most effective anomaly detection algorithm tailored to your specific dataset, ensuring superior accuracy. It can identify sudden spikes, drops, deviations from established patterns, and changes in trends using both univariate and multivariate APIs. Users can personalize the service to recognize different levels of anomalies based on their needs. The anomaly detection service can be deployed flexibly, whether in the cloud or at the intelligent edge. With a robust inference engine, the service evaluates your time-series dataset and automatically determines the ideal detection algorithm, enhancing accuracy for your unique context. This automatic detection process removes the necessity for labeled training data, enabling you to save valuable time and concentrate on addressing issues promptly as they arise. By leveraging advanced technology, organizations can enhance their operational efficiency and maintain a proactive approach to problem-solving.

Description

All types of frauds can be addressed with one solution. Subex Fraud Management is a 25-year-old domain expertise that provides 360 degree fraud protection across digital service by leveraging advanced machine intelligence and signaling intelligence. This solution combines a traditional rule engine with advanced AI/machine learning capabilities to increase coverage across all services and minimize fraud run time in the network. It also includes real-time blocking capabilities. The Subex Fraud Management solution's core is a hybrid rule engine. It covers detection techniques such as expressions, thresholds, and trends. Rule engine comprises of a combination of threshold rules, geographic rules, pattern (sequential) rules, combinatorial rules, ratio/proportion-based rules, negative rules, hotlist based rules, etc. These rules allow you to monitor advanced threats in your network.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

Azure AI Metrics Advisor
Bing
CTM360
Crestwood Cloud
Microsoft Azure
Microsoft Office 2021
Rayven
groundcover

Integrations

Azure AI Metrics Advisor
Bing
CTM360
Crestwood Cloud
Microsoft Azure
Microsoft Office 2021
Rayven
groundcover

Pricing Details

No price information available.
Free Trial
Free Version

Pricing Details

No price information available.
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

Microsoft

Founded

1975

Country

United States

Website

azure.microsoft.com/en-us/products/ai-services/ai-anomaly-detector/

Vendor Details

Company Name

Subex

Founded

1992

Country

India

Website

www.subex.com/fraud-management/

Product 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

Telecom Expense Management

Billing for Data
Billing for Voice
Call Monitoring
Chargeback Tracking
Contract Negotiation
Fixed Line Compatibility
Internal Cost Allocation
Mobile Line Compatibility
Usage Reporting

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