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Product Overview

UmbrellaFraud is designed with a multi-tiered architecture. The core components include the Transaction Analyzer, which processes incoming transaction data; the Rule Engine, which applies predefined fraud rules; the Anomaly Detector, which identifies unusual patterns; and the Alert Manager, which generates and manages alerts. These components communicate via internal messaging queues, ensuring asynchronous and reliable communication.

REST APIs facilitate integration with external systems, using endpoints like `/transactions` for data input and `/alerts` for output. Data is persisted in DB2, while configuration parameters and logs are stored in VSAM datasets. 0, with RBAC controlling access to resources.

Network requirements include specific ports for DB2 and the administrative interface. The `DISPLAY-FRAUD-RULES` command shows current rules, while `MODIFY-FRAUD-RULE` allows changes. Competing products like FraudGuard and Sentinel lack UmbrellaFraud's tight integration with the Hogan mainframe environment, offering a less streamlined architecture for Hogan users.

Frequently Asked Questions

What is UmbrellaFraud?

UmbrellaFraud is a mainframe-based fraud detection system designed for banking applications running on z/OS. It leverages the Hogan application infrastructure to monitor transactions and identify potentially fraudulent activities in real-time.

How does UmbrellaFraud work?

UmbrellaFraud integrates with existing banking systems through APIs and data feeds. It analyzes transaction data, customer data, and other relevant information to detect patterns indicative of fraud. When suspicious activity is detected, alerts are generated and sent to fraud analysts for further investigation.

What types of fraud can UmbrellaFraud detect?

UmbrellaFraud supports real-time fraud detection, rule-based fraud detection, and anomaly detection. It can identify various types of fraud, including credit card fraud, wire transfer fraud, and account takeover fraud.

What techniques does UmbrellaFraud use for fraud detection?

UmbrellaFraud uses a combination of techniques, including statistical analysis, machine learning, and rule-based logic, to identify fraudulent activity. It continuously learns from new data to improve its accuracy and effectiveness.

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