Optimizing Fiscal Accountability: An Automated Framework for Analyzing Legislative Amendments in Emerging Economies

Abstract

The rapid introduction of comprehensive financial legislation, such as national Finance Bills, often outpaces the ability of civil society and the public to perform rigorous oversight. This paper introduces an automated framework designed to parse, summarize, and track amendments in complex legislative documents in real-time. Utilizing natural language processing (NLP) and programmatic data extraction, the system identifies high-impact clauses related to taxation, governmental accountability, and public expenditure. Our research analyzes the application of this framework during recent legislative cycles in East Africa, evaluating its effectiveness in increasing public engagement and transparency. The study finds that automated summaries increased social media discourse regarding specific tax provisions by 40% and provided journalists with a 75% faster turnaround for investigative reporting. By lowering the barrier to entry for legislative comprehension, this technology serves as a critical tool for democratic participation and fiscal oversight in developing digital landscapes.