OPTIMIZING FINANCIAL OPERATIONS: ENHANCING EFFICIENCY IN DISBURSEMENT, BUDGET MANAGEMENT, COLLECTION, GENERAL LEDGER, AND ACCOUNTS PAYABLE/RECEIVABLE THROUGH AI DRIVEN SERVICE MANAGEMENT SYSTEM

Abstract

In today’s dynamic financial environment, organizations are increasingly adopting advanced technologies to streamline operations. The optimization of financial processes such as disbursement, budget management, collection, general ledger, and accounts payable/receivable is essential to maintaining a competitive edge. The implementation of AI-driven service management systems allows companies to achieve greater efficiency, minimize errors, and increase profitability by transforming traditional financial operations into more intelligent and responsive processes. This project aims to develop and implement an AI-powered service management system that enhances critical financial functions. The study focuses on identifying specific AI solutions applicable to disbursement, budgeting, collection, general ledger, and accounts payable/receivable. It also examines the benefits of these technologies in improving accuracy, reducing costs, and enabling data-driven decision-making. The system is designed to replace conventional methods with scalable, predictive, and automated financial processes. The system demonstrated measurable improvements in financial operations, including reduced processing times, lower error rates, and decreased operational costs. Forecasting accuracy improved significantly through predictive analytics, enabling more responsive budget adjustments and resource allocation. Additionally, the system optimized collection and dispute resolution processes, resulting in stronger stakeholder relationships and more stable cash flows. The integration of an AI-based service management system presents a transformative approach to financial operations. By automating repetitive tasks, enhancing data accuracy, and delivering predictive insights, the system supports smarter decision-making across financial functions. While successful implementation requires strategic planning and robust data integration, the potential benefits in terms of operational efficiency and cost reduction reinforce AI’s critical role in modern financial management. Future research may further explore implementation challenges and industry-specific customization strategies.