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Introduction:

Tax evasion is a widespread issue that involves individuals and businesses failing to pay the correct amount of taxes owed to the government. It has a significant impact on the economy, leading to reduced government revenue and an unequal distribution of the tax burden among citizens. Detecting potential tax evasion patterns is crucial in order to combat this issue effectively.

This thesis aims to explore various methods and techniques that can be used to detect potential tax evasion patterns. By analyzing data, identifying red flags, and implementing advanced technologies such as data mining and machine learning, tax authorities can improve their ability to detect and prevent tax evasion.

Table of Contents:

1.1 Introduction
1.2 Background of Study
1.3 Problem Statement
1.4 Objective of Study
1.5 Limitation of Study
1.6 Scope of Study
1.7 Significance of Study
1.8 Structure of the Thesis
1.9 Definition of Terms

Chapter Two: Literature Review
– Overview of tax evasion
– Previous studies on tax evasion detection
– Methods and techniques for detecting tax evasion patterns
– Role of technology in tax evasion detection
– Challenges and limitations in detecting tax evasion

Chapter Three: Research Methodology
– Research design
– Data collection methods
– Data analysis techniques
– Sampling methods
– Ethical considerations
– Validity and reliability of data
– Limitations of research methodology
– Case study analysis

Chapter Four: Discussion of Findings
– Analysis of data
– Identification of potential tax evasion patterns
– Comparison of different detection methods
– Recommendations for tax authorities
– Implications for policy and practice
– Future research directions

Chapter Five: Conclusion and Summary
– Summary of key findings
– Conclusions drawn from the study
– Implications for tax authorities and policymakers
– Recommendations for future research
– Final thoughts on detecting potential tax evasion patterns

Thesis Overview:

Detection of potential tax evasion patterns is a critical issue that requires careful analysis and investigation. This thesis aims to explore various methods and techniques that can be used to detect tax evasion effectively. By conducting a comprehensive literature review, analyzing data, and implementing advanced technologies, tax authorities can improve their ability to detect and prevent tax evasion.

The research methodology chapter will outline the design of the study, data collection methods, analysis techniques, and ethical considerations. By utilizing a case study approach, this thesis will provide valuable insights into the detection of potential tax evasion patterns.

The discussion of findings chapter will analyze the data collected, identify potential tax evasion patterns, compare different detection methods, and provide recommendations for tax authorities. The conclusion and summary chapter will summarize key findings, draw conclusions from the study, and offer recommendations for future research in this area.

Overall, this thesis will contribute to the existing literature on tax evasion detection and provide valuable insights for tax authorities, policymakers, and researchers in combating tax evasion effectively.

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