Affiliation: Veer Narmad South Gujarat University
Abstract:
GST, one of the biggest tax reforms in India that aims to bring transparency and efficiency. The fact that GST fraud is hindering tax compliance and revenue collection remains to be a major problem. This particular paper aims to provide a solution that could improve the transparency of collection and thereby increasing the purity of GST by utilizing machine learning as a tool to manually detect those dubious taxpayers who are committing GST fraud. Within the review, methodology includes a survey of 50 respondents who both claimed to be tax professionals and shared background as software engineer that were used to gather insights on how fraud is being committed and what challenges are being faced regarding it. We conducted a survey in order to gather raw data about classical habits of fraud detection and related existing approaches. To facilitate analytics of transaction data to detect patterns indicative of fraud, we used machine learning approaches. To uncover deception attempts, various algorithms precautions were taken such as, supervised algorithms as decision trees and random forests mars to clustering methods. Historical transactional log records augmented by surveys provided empirical work. The findings show that in performance than in the detection of deceptive activities, Traditional measures are significantly outperformed by integrated predictions. Specific algorithms such as random forests also achieved high accuracy in identifying triedevasion patterns, particularly with fraudulent invoices or when transactions where not declared by individuals. Furthermore, the findings highlighted the importance of the use of new detection systems and the frequent updating of such systems within tax administration. Backed up with findings above, it can be said that machine learning is also very much useful in the field of GST fraud detection thus enhancing the effectiveness of operations. Utilizing these technologies within frameworks focused on tax compliance should be more beneficial for all, ensuring better prevention of fraud and abuse and maximization of revenues for
governments as well as business.
Keywords: Fraud Detection,GST Fraud,Machine Learning,Tax Compliance
Vol & Issue: VOL.1, ISSUE No.1, january 2025