Telecom — Customer Interaction Fraud Detection Pipeline

Overview

The purpose of this DAG is to detect fraudulent activities within customer interactions in the telecom sector. It utilizes data sourced from Customer Relationship Management (CRM) systems and historical interaction logs. The ingestion pipeline begins with data extraction from these sources, ensuring comprehensive coverage of customer interactions. Following data ingestion, advanced fraud detection models are applied to analyze patterns and identify anomalies indicative of fraud. Quality control

The purpose of this DAG is to detect fraudulent activities within customer interactions in the telecom sector. It utilizes data sourced from Customer Relationship Management (CRM) systems and historical interaction logs. The ingestion pipeline begins with data extraction from these sources, ensuring comprehensive coverage of customer interactions. Following data ingestion, advanced fraud detection models are applied to analyze patterns and identify anomalies indicative of fraud. Quality control mechanisms are integrated to reduce false positive rates, ensuring that legitimate customer interactions are not flagged erroneously. Upon detection of potential fraud, alerts are generated to facilitate rapid response and mitigation actions by the customer service team. Monitoring key performance indicators (KPIs) such as detection accuracy, response time to alerts, and the rate of false positives provides insights into the system's effectiveness. This DAG not only enhances the security of customer interactions but also builds customer trust and satisfaction, ultimately leading to improved business outcomes in the telecom industry.

Part of the AI Assistants & Contact Center solution for the Telecom industry.

Use cases

• Increased detection of fraudulent activities
• Enhanced customer trust and satisfaction
• Reduced operational costs from false alerts
• Faster response times to potential fraud
• Improved compliance with regulatory standards