Author Login IJIRT Partner Network (IPN) Login

Role of Artificial Intelligence in Income Tax Fraud Detection

  • Unique Paper ID: 173925
  • Volume: 11
  • Issue: 10
  • PageNo: 1927-1936
  • Abstract:
  • Income tax fraud is a significant threat to tax authorities across the globe, resulting in massive revenue loss and compromising the integrity of tax systems. Conventional detection methods, including manual audit and rule-based systems, are time-consuming, labor-intensive, and ever less suitable in identifying sophisticated patterns of fraudulent activities. As tax evasion schemes become more advanced, artificial intelligence (AI) has been a game-changing force in fraud detection. This study analyzes the application of AI in identifying income tax fraud, considering its advantages, disadvantages, and practical implications. AI platforms apply machine learning techniques and predictive analytics to scrutinize vast amounts of taxpayer data, identifying abnormalities and suspicious patterns better than traditional approaches. Supervised learning models like decision trees and neural networks learn from past instances of fraud cases to classify a transaction, while unsupervised learning models like clustering and anomaly detection detect fraud patterns underlying instances where there is no labeled dataset. These solutions improve the accuracy of fraud detection, minimize false positives, and provide real-time risk assessment, thus facilitating greater tax compliance and revenue collection. In spite of these advantages, AI-based tax fraud detection has numerous challenges facing it. Among the major issues are privacy of data issues, algorithmic biases that can lead to discriminatory targeting, cost of computation, and inadequate regulatory demands on AI-driven tax audit processes. To address these limitations, this research suggests a hybrid model merging the strengths of AI capability with human oversight to ensure efficiency as well as ethical values in detecting fraud. Besides, the study explores emerging technologies such as the use of blockchain and privacy-enhancing technologies to improve the potency of AI in detecting tax fraud even more. The study reveals that AI-powered fraud detection significantly enhances audit precision, reduces the workload, and complements proactive anti-fraud tactics. However, successful deployment requires ethical AI frameworks, more stringent data governance regulations, and regulation to ensure transparency and accountability. This paper adds to the existing literature on AI use in financial fraud detection, enabling tax authorities and policymakers to understand how to best capitalize on AI adoption. Governments can create a more efficient, transparent, and fraud-resistance tax system that benefits both taxpayers and authorities by harnessing the power of AI.
Download article email to a friend

Cite This Article

  • ISSN: 2349-6002
  • Volume: 11
  • Issue: 10
  • PageNo: 1927-1936

Role of Artificial Intelligence in Income Tax Fraud Detection

Related Articles

19 Apr, 2025

Tech Meets Tradition: Exploring Online Emergence in Wedding Services

Read More
Impact Factor
8.01 (Year 2024)
UGC Approved
Journal no 47859

Join Our IPN

IJIRT Partner Network

Submit your research paper and those of your network (friends, colleagues, or peers) through your IPN account, and receive 800 INR for each paper that gets published.

Join Now

Latest Publication

Archive

View More

Recent Conferences

NCSEM 2024

National Conference on Sustainable Engineering and Management - 2024 Last Date: 15th March 2024

Submit inquiry