AI Can Play an Essential Role in Combating UK Tax Evasion

The UK stands in the forefront of global finance. However, it also contends with the persistent issue of tax evasion. The UK tax gap in the tax year 2021 to 2022 is estimated to be £35.8 billion ($45.2 billion)—4.8% of total theoretical tax liabilities—according to the official report from the UK tax authority, updated June 22, 2023.

Tax evasion in the UK is a complex issue that drains resources from the government and undermines public trust in the tax system. Individuals and corporations exploit gaps in the existing tax infrastructure to reduce their tax liabilities. While not all tax avoidance is illegal, aggressive tax avoidance strategies that push the boundaries of legality have been a cause for concern.

With the advent of artificial intelligence revolutionizing various sectors, it’s time for the UK to embrace AI as a powerful tool to curb tax evasion.

Promise of AI

AI can play a significant role in detecting tax evasion in the UK by leveraging advanced data analytics and machine learning techniques to identify suspicious patterns and anomalies in tax-related data.

The following are some ways AI could assist in this process:

Data analysis and pattern recognition. AI can process vast amounts of financial and transactional data to identify irregularities or patterns indicative of tax evasion. This includes analyzing income, expenses, investments, and other financial records.

For example, consider a scenario where an individual taxpayer consistently reports modest income, minimal expenses, and no significant investments over several years. Traditional methods of investigation might overlook this case due to its apparent conformity with standard financial behavior. However, AI-driven analytics can delve into the intricate details of the financial data, identifying subtle patterns that deviate from the expected norms.

In this example, the AI might detect a sudden surge in reported expenses, seemingly unrelated to any visible change in the individual’s lifestyle or business operations. Through sophisticated pattern recognition, the AI system could flag this as an anomaly, prompting tax authorities to investigate further.

This illustrates how AI’s ability to process extensive financial data goes beyond human capacity, uncovering nuanced irregularities that are crucial in the fight against tax evasion.

Cross-verification of data. The introduction of Real-Time Information in the UK’s payroll system significantly enhanced the government’s ability to detect and prevent fraudulent activities, particularly those involving employers paying cash to employees to evade national insurance contributions. RTI data can be cross-verified with other financial information, such as banking records and self-assessment tax returns, to ensure consistency.

Any disparities between reported income and other financial records can raise red flags for potentially fraudulent activities.

Real-time and continuous monitoring. AI can provide real-time monitoring of financial transactions, helping authorities to respond swiftly to suspicious activities. AI systems are also able to continuously monitor tax data, financial transactions, and relevant external sources, ensuring ongoing vigilance in detecting new evasion tactics and trends.

Predictive modeling and behavioral analysis. AI can build predictive models that estimate the likelihood of tax evasion based on historical data and known evasion patterns. Tax authorities can use these models to target high-risk cases more efficiently. AI can also analyze taxpayer behavior, identifying changes in financial patterns that may indicate evasion.

Collaboration with financial institutions. AI can facilitate cooperation between tax authorities and financial institutions by identifying accounts or transactions that warrant further investigation. This can help uncover offshore accounts and other tax evasion mechanisms.

Blockchain analysis. For cryptocurrencies and blockchain transactions, AI can analyze blockchain ledgers to trace cryptocurrency flows and identify potential tax evasion or money laundering activities.

Fraud detection. AI-powered fraud detection algorithms can be adapted to identify tax fraud and evasion schemes by analyzing payment transactions, invoices, and receipts.

It’s important to note that while AI can be a powerful tool in detecting tax evasion, it should complement traditional investigative methods and adhere to privacy regulations and ethical guidelines. The implementation of AI for tax evasion detection also requires a robust data infrastructure, cybersecurity measures, and the expertise to interpret AI-generated insights effectively.

Anomaly detection. AI can be used to flag unusual transactions or discrepancies between reported income and financial activities. For example, it can identify cases where reported expenses don’t match the industry averages or where income suddenly decreases without a clear explanation.

Natural Language Processing. NLP algorithms can be used to analyze textual data, such as emails, contracts, and other documents, to detect potentially incriminating information related to tax evasion schemes or hidden assets.

Social media monitoring. AI can monitor social media platforms to identify lifestyle inconsistencies. For instance, if someone reports minimal income but flaunts a lavish lifestyle on social media, this could raise suspicions and trigger an investigation.

AI in UK Tax System

Despite the immense potential, the UK taxation system has been slow to adopt AI in its efforts to combat tax evasion. This lack of technological integration is a missed opportunity. The benefits of AI in tax enforcement are evident, not only in improved efficiency but also in leveling the playing field for honest taxpayers.

AI can also help taxpayers understand and comply with tax laws by providing real-time advice and guidance, ultimately reducing unintentional noncompliance. The introduction of AI could be seen as a commitment to fairness, transparency, and a more robust tax system.

The adoption of AI in taxation won’t be without challenges. Privacy concerns, data security, and the need for robust oversight mechanisms must be addressed. The UK government must also invest in training tax professionals and equipping them with the skills necessary to manage and interpret AI-driven insights.

Way Forward

The UK has always been at the forefront of innovation and progress. It’s time for the country to engage in the battle against tax evasion by harnessing the power of AI.

By integrating AI into the taxation system, the UK can send a strong message that it is committed to fairness, transparency, and economic integrity. This move can increase tax revenue, strengthen public trust, and make the UK a global leader in combating tax evasion. The future of taxation is digital, and it’s time for the UK to take the lead in this transformative journey.

This article does not necessarily reflect the opinion of Bloomberg Industry Group, Inc., the publisher of Bloomberg Law and Bloomberg Tax, or its owners.

Author Information

Majid Aminzare is associate professor in accounting at the University of Bradford School of Management.

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