Nigeria: AI And Tax: Nigeria

Technology continues to gain ground globally and affect businesses and governments alike. Nigeria, like many other countries was not sufficiently poised for the changes the digital economy brought to taxation and only tried to recover from an eroded tax base by relying on the BEPS Action Plans. Beyond the digital economy, Artificial Intelligence (AI) is quickly being imprinted in several facets of the economy with predictions that it would contribute US$15.7 trillion to the global economy by 2030¹ . Internationally, the major themes in discussions surrounding AI and tax include the effect of utilising robots, labour market size, reduced income taxes, reduced public funds for social welfare systems, introduction of robot taxes² , introduction of energy taxes³ , improved tax administration in combating tax evasion and tax fraud⁴ , the legality of automated decisions⁵ and data privacy among others. It is imperative that Nigerian tax administrations, both federal and states, consider what the threats and opportunities in tax are and join the conversations to ensure they do not get left behind.

Intersections between AI and Tax

In considering AI in tax, analyses are usually from the perspective of its effect on national revenue and its potential for improved administrations. Firstly, considering national revenue, the employment of AI by governments and businesses alike reduces reliance on human employees previously trained for such roles. The result beyond its impact on the size of the labour market is a shrinking of the personal income tax base and revenues previously available to governments for social welfare services. To combat this, more developed economies have made suggestions for the introduction of robot taxes and creating new tax types.⁶ In Nigeria, the informal economy reportedly accounts for 57.7% of the GDP.⁷ By implication, the nation already grapples with a very small tax base. On the flip side of the small tax base is the lack of accountability by government officials for taxes collected resulting in taxpayer apathy and tax evasion. Consequently, any policies aimed at introducing robot taxes or other taxes would not be welcome. With the current imbalance between Nigerians who earn and Nigerians who actually get taxed, new taxes are certain to result in greater inequalities among citizens.

Another subject crucial in the relationship between AI and tax is the increased efficiency in tax administrations. The Norwegian Tax Authority deploys data analysis for case selection for investigations and the Belgian Government deploys AI for finding fraud patterns. AI is also deployed by several national tax authorities across the globe. The OECD notes that advanced analytics offer potential to developing countries to modernise their tax systems by utilising data beyond recording and storing.⁸ While the inland revenue services in Nigeria may house more data in their archives than they are aware of, irregular data handling may affect the reliability of such data. Further, the existing data irrespective, the inland revenue services and other public offices in the country, suffer severe data limitation issues. ⁹ If these challenges are surmounted, accessing and exploiting the right kind of data, training personnel and investing in machine learning would prepare the inland revenue service for leveraging AI to improve administration of taxes. Practical benefits would include saving time, reducing risks of errors and manipulations, tax case predictions, checking correctness of declared data, identifying hidden relationships, promoting equal treatment for similar taxes, and curbing tax evasion. In addition to aiding monitoring and compliance, AI in tax will also help multinationals satisfy government demands for accurate tax reporting thus improving the development of government regulation.¹⁰ As machine learning will be cost intensive¹¹, the government will need to undertake a cost-benefit analysis. These considerations nonetheless, it is important the country is not left behind in utilising AI in tax administration. Currently, the Federal Inland Revenue Service utilises technology through its TaxPro Max platform. Although it is reported to have increased collections within the first year of its deployment¹², user experience has not been without hitches. To avoid these hitches with AI, much work must go into properly classifying taxpayers and businesses and curating the content to avoid counterproductive results. Also key to AI's influence on tax is the role of data. AI rides on the wheels of data and the rules governing data must be adhered to in the use of AI. Any reliance on AI for automated decision-making by tax administrations must satisfy the demands of privacy, fairness, transparency and accountability. The Nigerian Data Privacy Regulation 2019 (Regulation) regulates the use of data and the rights of data subjects. Accordingly, the inland revenue services must adhere to the provisions of the Regulation in processing data, especially with regard to automated decision-making.

In terms of whether a labour-intensive economy should embrace AI or adopt a protectionist approach, it is noted that in Egypt, it was finally agreed that embracing AI was not optional.¹³ Therefore, Nigeria should equally not only embrace AI as it is currently doing¹⁴, but also take the wheels in determining what direction AI should take in key sectors such as taxation. If wielded correctly, investments made in AI for tax administration would work in the overall interests of the economy.

Conclusion

The digital economy served as a preview of how countries can have their tax base eroded if blinded to the potential of technology in business. As AI is already utilised in businesses local and international, it is imperative that the government examines what the effects will be both in terms of taxes collected and administration of taxes. It is hoped that Nigeria will make the needed investment in training personnel and machine learning to ensure it is well-poised to take advantage of the innovations of AI in taxation.

Footnotes

1. Anand S. Rao and Gerard Verweij Sizing the Pricehttps://www.pwc.com/gx/en/issues/analytics/assets/pwc-ai-analysis-sizing-the-prize-report.pdf accessed 23 May 2023.

2. Alessia Fidelangeli and Federico Galli Artificial Intelligence and Tax Law: Perspectives and Challenges (2021)https://ceridap.eu/artificial-intelligence-and-tax-law-perspective-and-challenges/?Ing=en accessed 5 July 2022.

3. Michaela Georgina Lexer and Luisa Scarcella Artificial Intelligence and Labor Markets. A critical Analysis of Solution Models from a Tax Law and Social Security Law Perspective https://ssrn.com/abstract=4014798 accessed 28 February 2023.

4. Aleksandra Bal Black-Box Models as a Tool to Fight VAT Fraud (2022)https://link.springer.com/chapter/10.1007/978-94-6265-523-2_12 accessed 12 March
2023.

5. Isak Mendoza and Lee A. Bygrave The Right Not to be Subject to Automated Decisions Based on Profiling (2017) https://link.springer.com/chapter/10.1007/978-3-319-64955-9_4 accessed 12 March 2023.

6. Lexer and Scarcella (n3).

7. https://www.worldeconomics.com/Informal-Economy/Nigeria.aspx accessed 23 May 2023.

8. Advanced Analytics for Better Tax Administration: Putting Data to Work (OECD Publishing 2016) 6.

9. Wilson R.S. Prichard Taxation, Responsiveness and Accountability in Sub-Saharan Africa 2010 https://citeseerx.ist.psu.edu/document repid=rep1&type=pdf&doi+18b0189596c828f9 c502ecabc814bfe5a2353691 accessed 11 March 2023.

10. Zhuowen Huang Discussion on the development of AI on taxation American Journal of Industrial and Business Management 2018 8, 1817-1824 Scientific Research Publishing https://doi.org/10.4236/ajibm.2018.88123 accessed 4 March 2023.

11. Artificial Intelligence-Entering the World of Tax https://www2.deloitte.com/ro/en/pages/tax/articles/artificial-intelligence-in-tax.html accessed 2 March 2023.

12. Joseph Chibueze TaxPro Max: The game changer in tax administration in Nigeria https://guardian.ng/business-services/money/taxpro-max-the-game-changer-in-tax-administration-in-nigeria/ accessed 24 May 2023.

13. Sally Radwan and Samar Sobeih Egypt's AI strategy is more about development than AI https://oecd.ai/en/wonk/egypt-ai-strategy accessed 24 May 2023.

14. Nigeria has established of the National Centre for AI and Robotics (NCAIR) and is working on a National Artificial Intelligence Policy. Fom Gyem: Analysing Nigeria's National Artificial Intelligence Policy https://guardian.ng/technology/tech/analysing-nigerias-national-artificial-intelligence-policy/ accessed 31 May 2023.

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