Artificial Intelligence in Financial Auditing: Innovating Traditional Practices for Enhanced Accuracy
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Abstract
Artificial intelligence (AI) has revolutionized financial transaction auditing by replacing traditional approaches with an innovative approach that strives to increase the auditing process's efficiency and delicacy. This article's goal is to look into how artificial intelligence technologies like data analytics, machine literacy, and natural language processing are being used to implement fiscal auditing systems. In addition to expediting inspection cycles, artificial intelligence also improves the reliability of financial statements. It accomplishes this by offering prophetic perceptivity, automating repetitive tasks, and spotting irregularities. The research looks at some artificial intelligence (AI) tools that are currently in use in auditing, including automated data analysis platforms and fraud detection algorithms, and evaluates the effect that these tools have on inspection quality. It also discusses the challenges associated with the abandonment of artificial intelligence, including the requirement for data security organizations and nonsupervisory fabrics. This article's goal is to clarify how artificial intelligence is changing the auditing landscape and making it a more thorough and accurate method of financial control. Ethnographic data and case studies are used to achieve this. The results raise the prospect that auditing procedures may someday be rewritten using artificial intelligence, setting new benchmarks for delicacy and effectiveness in the industry.