Leveraging AI to Combat Tax Fraud in Uganda.
By Lynnet Kiggundu
Much as tax fraud remains a significant challenge in many developing countries such as Uganda, this article indicates that such challenges shall not live forever to undermine public trust and deprive the government of essential revenue needed for infrastructure, healthcare, and education.
With the current innovations in machine learning systems that are able to learn from big data, many AI tools are now able to perform tasks with minimal human interaction. The same can be written about tax administration, where AI has been applied in some economies to detect fraud and enforce tax compliance.
Therefore, because of the increased adoption of Artificial Intelligence (AI) tools in business operations and public administration, it is noteworthy for URA to leverage the potential of AI innovations to offer a transformative solution to detect fraudulent activities, enhance tax compliance, and optimize revenue collection processes.
Below, are the ways through which AI can be used in combating tax fraud;
- Enhancing Fraud Detection: AI-powered systems can analyse vast amounts of financial data to identify patterns and anomalies indicative of tax fraud. For instance, machine learning algorithms can flag sudden drops in reported income, excessive deductions, or unusual offshore transactions, prompting further investigation by tax authorities. In developed economies, AI algorithms have been instrumental in identifying high-risk taxpayers by comparing income, accounts, and electronic payments with tax filings.
- Predictive Analytics for Proactive Measures: AI enables tax authorities to employ predictive analytics, assessing historical data to forecast potential fraud risks. By evaluating factors such as prior noncompliance history and industry-specific fraud trends, AI can assign risk scores to tax returns, allowing authorities to prioritize audits and allocate resources more effectively.
- Real-Time Monitoring and Blockchain Analysis: With URA’s (specifically the Tax Investigation Department) desire to venture into taxation of digital assets, AI can facilitate real-time monitoring of transactions, enabling immediate detection of suspicious activities and reducing the chances of successful fraud. Additionally, AI-driven blockchain forensics assist in tracing illegal transactions, identifying suspicious crypto activities, and uncovering unreported income hidden in digital assets.
Conclusion: AI offers a promising avenue for developing economies such as Uganda to combat tax fraud, enhance compliance, and optimize revenue collection. By investing in AI technologies, data infrastructure, and capacity building, these countries can strengthen their tax systems, ensuring sustainable development and improved public services.
Considering the sensitive nature of the data managed by the Uganda Revenue Authority (URA) in its daily operations, the organization should develop and tailor its own AI system.
This approach would not only mitigate risks associated with data breaches and privacy violations but also enhance staff confidence by providing them with a familiar and secure technological environment.
