The telecommunications industry in Nigeria has witnessed significant growth over the past two decades, providing millions of subscribers with access to voice and data services. Despite these advancements, network-related challenges such as call drops, call setup failures, network congestion, poor signal coverage, and switching errors continue to affect service quality. These challenges often result in unsuccessful calls for which subscribers may still be charged, leading to customer dissatisfaction, increased complaints, and reduced confidence in telecommunication service providers. This study focuses on the Design and Implementation of an AI-Based Automated Call Charge Reversal System for Unsuccessful Calls in Telecommunication Networks in Nigeria. The proposed system utilizes Artificial Intelligence (AI) and Machine Learning (ML) techniques to monitor, analyze, and classify call transactions in real time. By examining Call Detail Records (CDRs), network performance indicators, and subscriber billing data, the AI model identifies unsuccessful calls and automatically initiates charge reversals where appropriate. The system is designed to distinguish between network-induced call failures and user-initiated call terminations, thereby ensuring accurate refund decisions and minimizing fraudulent claims. It integrates seamlessly with existing telecommunications billing infrastructures, enabling automatic reimbursement of wrongly deducted call charges without requiring manual intervention. The implementation employs a centralized database for managing subscriber records, call logs, and refund transactions, while an administrative dashboard provides real-time monitoring and reporting capabilities. The proposed solution is expected to improve billing transparency, enhance customer satisfaction, reduce complaint handling costs, and strengthen regulatory compliance within the Nigerian telecommunications sector. Furthermore, the adoption of AI-driven automation will contribute to increased operational efficiency and improved service quality among network operators. The study concludes that the integration of Artificial Intelligence into telecom billing systems offers a practical and scalable approach to addressing the persistent challenge of erroneous call charges in Nigeria’s telecommunications industry.

Keywords: Artificial Intelligence (AI), Machine Learning, Telecommunications, Call Charge Reversal, Unsuccessful Calls, Billing System, Nigeria, Customer Satisfaction, Call Detail Records (CDRs), Network Quality of Service (QoS)..