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Since the seminal work of Allingham and Sandmo in 1972, tax evasion has been firmly established as a complex and multifaceted global issue. This study posits that one practical approach to mitigate tax evasion in developing countries is to utilise Cressey’s (1953) fraud triangle model as a framework for analysing taxpayers’ decisions. The theory explains why individuals commit fraud, including tax evasion, through three key factors: pressure, opportunity, and rationalisation. The study used the theoretical research method (literature review) as postulated by Alm (2011) to examine and explain the tax evasion phenomenon. The findings suggest that utilising the fraud triangle model (in the context of new technology such as artificial intelligence, machine learning, data mining and deep learning) will be beneficial to policymakers. First, it will assist tax authorities in profiling taxpayers by focusing on behaviours and other factors (economic and non-economic) that influence tax evasion. Next, with this framework, tax authorities can formulate advanced risk management strategies that directly tackle the fundamental elements of the Fraud Triangle, thereby improving their efforts against tax evasion. Furthermore, it offers invaluable guidance to lawmakers and policymakers, preparing them to develop strong legislation aimed at narrowing the tax gap from aggressive tax avoidance and evasion schemes. Finally, the framework can illuminate broader economic or industry-wide circumstances that increase the overall risk of tax evasion, facilitating proactive measures before difficulties arise. Thus, integrating the fraud triangle framework into the tax administration process can improve the efficiency and effectiveness of tax authorities and contribute to fairer tax systems in developing countries.

Effective tax systems rely on tax literacy and tax compliance behaviour among taxpayers for government revenue mobilisation. However, the extant literature suggests that in sub-Saharan Africa, mobilising tax revenue to fund public services and infrastructure development to achieve the United Nations’ Millennium Development Goals (SDGs) remains a great challenge. According to the 2024 Revenue Statistics in Africa report, jointly undertaken by the African Union Commission (AUC), African Tax Administration Forum (ATAF), the OECD Centre for Tax Policy and Administration and the OECD Development Centre, the average tax-to-GDP ratio was 16% in African countries in 2022, compared to 19.3%, 21.5% and 34.0% respectively for  Asia and the Pacific, Latin America and the Caribbean, and OECD countries. Despite being recognised as a critical aspect of tax compliance, the role played by political legitimacy in taxpayer compliance behaviour remained under-explored in developing countries. This study proposes an Augmented Theory of Planned Compliance Behaviour (ATPCB) framework, based on Ajzen’s (1991) theory of planned behaviour (TPB) and both the deterrence and accommodation theories of compliance, to predict taxpayers’ compliance behaviour, especially in developing countries. The framework comprises four components: attitude, subjective norms, perceived behavioural control, and political legitimacy. The findings of this study have implications for policymakers and researchers as it will assist future research in providing a structured approach for assessing taxpayers’ compliance behaviour. Also, it will provide interested parties with a better understanding of the combined effects of individuals’ beliefs, attitudes, norms, and political legitimacy on tax compliance. Lastly, the study will assist governments in deciding the future course of action towards effective policymaking for taxation and revenue mobilisation.

Effective tax systems rely on tax literacy and tax compliance behaviour among taxpayers for government revenue mobilisation. However, the extant literature suggests that in sub-Saharan Africa, mobilising tax revenue to fund public services and infrastructure development to achieve the United Nations’ Millennium Development Goals (SDGs) remains a great challenge. According to the 2024 Revenue Statistics in Africa report, jointly undertaken by the African Union Commission (AUC), African Tax Administration Forum (ATAF), the OECD Centre for Tax Policy and Administration and the OECD Development Centre, the average tax-to-GDP ratio was 16% in African countries in 2022, compared to 19.3%, 21.5% and 34.0% respectively for  Asia and the Pacific, Latin America and the Caribbean, and OECD countries. Despite being recognised as a critical aspect of tax compliance, the role played by political legitimacy in taxpayer compliance behaviour remained under-explored in developing countries. This study proposes an Augmented Theory of Planned Compliance Behaviour (ATPCB) framework, based on Ajzen’s (1991) theory of planned behaviour (TPB) and both the deterrence and accommodation theories of compliance, to predict taxpayers’ compliance behaviour, especially in developing countries. The framework comprises four components: attitude, subjective norms, perceived behavioural control, and political legitimacy. The findings of this study have implications for policymakers and researchers as it will assist future research in providing a structured approach for assessing taxpayers’ compliance behaviour. Also, it will provide interested parties with a better understanding of the combined effects of individuals’ beliefs, attitudes, norms, and political legitimacy on tax compliance. Lastly, the study will assist governments in deciding the future course of action towards effective policymaking for taxation and revenue mobilisation.

Since the seminal work of Allingham and Sandmo in 1972, tax evasion has been firmly established as a complex and multifaceted global issue. This study posits that one practical approach to mitigate tax evasion in developing countries is to utilise Cressey’s (1953) fraud triangle model as a framework for analysing taxpayers’ decisions. The theory explains why individuals commit fraud, including tax evasion, through three key factors: pressure, opportunity, and rationalisation. The study used the theoretical research method (literature review) as postulated by Alm (2011) to examine and explain the tax evasion phenomenon. The findings suggest that utilising the fraud triangle model (in the context of new technology such as artificial intelligence, machine learning, data mining and deep learning) will be beneficial to policymakers. First, it will assist tax authorities in profiling taxpayers by focusing on behaviours and other factors (economic and non-economic) that influence tax evasion. Next, with this framework, tax authorities can formulate advanced risk management strategies that directly tackle the fundamental elements of the Fraud Triangle, thereby improving their efforts against tax evasion. Furthermore, it offers invaluable guidance to lawmakers and policymakers, preparing them to develop strong legislation aimed at narrowing the tax gap from aggressive tax avoidance and evasion schemes. Finally, the framework can illuminate broader economic or industry-wide circumstances that increase the overall risk of tax evasion, facilitating proactive measures before difficulties arise. Thus, integrating the fraud triangle framework into the tax administration process can improve the efficiency and effectiveness of tax authorities and contribute to fairer tax systems in developing countries.