Tax evasion risk management using a Hybrid Unsupervised Outlier Detection method

Savić, Miloš; Atanasijević, Jasna; Jakovetić, Dušan; Krejić, Nataša

doi:10.1016/j.eswa.2021.116409

Cited by 21 publications

(13 citation statements)

References 19 publications

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“…In order to combat tax evasion, it is important to measure the relevant indicators of tax evasion, the risks of tax evasion, and the profiles of tax evaders at risk, and to engage in mechanisms to monitor compliance and behavioral indicators (Savic´ et al, 2022). In a pivotal report on managing and improving tax compliance, the OECD (2004) encourages the use of public opinion-based surveys and research to measure compliance indicators such as taxpayers' attitudes, awareness, perception, risk preferences, tax morale, social norms and intention to comply.…”

Section: Active Monitoring Of Compliance Indicatorsmentioning

confidence: 99%

Taxes and social instability: How large corporations and wealthy taxpayers hide taxable money?

Lompo,

Ouoba

2024

EAL

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<p><span lang="EN-US" style="font-size: 12pt; font-family: verdana, geneva, sans-serif; color: black;">Non-compliance with tax obligations, particularly by wealthy taxpayers and large corporations, continues to represent a source of social injustice that fuels social instability, especially in developing countries. Understanding the strategies of tax evasion and avoidance is of critical importance. This article highlights five main strategies used by large corporations and wealthy taxpayers to avoid taxes, including tax havens, the underground economy, aggressive tax optimization, alternative financial markets, and crypto currencies. We also propose several actions to tackle global tax non-compliance, including prevention, peer reporting, active monitoring of compliance indicators and inter- national cooperation. These actions can be combined to achieve optimal results in reducing tax evasion and avoidance.</span></p>

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Section: Active Monitoring Of Compliance Indicatorsmentioning

confidence: 99%

Taxes and social instability: How large corporations and wealthy taxpayers hide taxable money?

Lompo,

Ouoba

2024

EAL

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“…Specifically, it was associated with Principal Component Analysis (PCA) [20] and Singular Value Decomposition (SVD) [21], as dimensionality reduction techniques, in order to determine the relevant fraud indicators and learn a fraud scale to rank Brazilian taxpayers based on the risk they represent for the tax administration. In [22], unsupervised and supervised machine learning techniques were coupled to detect taxpayers' suspicious behavior. In particular, two unsupervised learning techniques were adopted to discover clusters of business entities that exhibit similar tax-related behavior.…”

Section: Related Workmentioning

confidence: 99%

“…One should note that the latter approach can be generalized to recognize fraud patterns for other types of taxes. A Hybrid Unsupervised Outlier Detection (HUNOD) model was presented in [22] to mine risky tax behaviors. In particular, user knowledge was fed into a combination of representational learning and clustering to detect outliers in personal income tax data.…”

Section: Related Workmentioning

confidence: 99%

Simultaneous Classification and Regression for Zakat Under-Reporting Detection

Ismail

Alsadhan

2023

Applied Sciences

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Tax revenue represents an essential budget source for most countries around the world. Accordingly, the modernization of relevant technological infrastructure has become a key factor of tax administration strategy for improving tax collection efficiency. In particular, the fiscal consolidation of the Kingdom of Saudi Arabia has been supported by considerable development in tax policy and administration, aimed at raising more taxes from non-oil activities. In fact, non-Saudi investors are liable for income tax in Saudi Arabia. On the other hand, Saudi citizen investors (and citizens of the GCC countries) are liable for Zakat, an Islamic assessment. Typically, taxpayers are in charge of preparing and accurately reporting their Zakat declaration. This allows tax authorities to overview and audit their business activities. However, despite administration efforts to increase taxpayer compliance, considerable revenue remains at under-reporting risk. In this paper, we introduce a novel intelligent approach to support tax authority efforts in detecting under-reporting among Zakat payer declarations. In particular, the proposed solution aims at improving detection accuracy and determining the fraud cases that correspond to a higher revenue at risk. Specifically, we formulate Zakat under-reporting detection as a supervised machine learning task through the design of a deep neural network that performs simultaneous classification and regression tasks. In particular, the proposed network contains an input layer, five hidden layers, and two output layers for classification and regression. Zakat declarations are mapped into the predefined “under-reporting” or “actual declaration” classes. Moreover, the revenue at risk caused by the predicted fraud cases is learned by the designed model. This allows the proposed approach to prioritize the auditing of specific Zakat payers based on the corresponding predicted revenue at risk. A real dataset including 51,919 Zakat declarations was used to validate and assess the designed model. Further, the Synthetic Minority Oversampling Technique (SMOTE) boosted the proposed model performance in terms of classification and prioritization.

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“…Supervision is the process of observing the implementation of all organizational activities to ensure that all work being carried out goes according to the established plan. Meanwhile, in terms of public administration, supervision is defined as an activity process that compares what is carried out, carried out, or carried out with what is desired, planned, or ordered (Savić et al, 2022).…”

Section: Tax Controlmentioning

confidence: 99%

The Effectiveness of Tax Audit as a Self Assessment System Supervision Measures and Tax Revenue Support (Study at the Large Tax Office 4)

Wahyudin

2022

ijtc

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The level of formal taxpayer compliance is still not satisfactory if it is associated with the self-assessment system because there are still quite high gaps. For this reason, it is necessary to carry out a tax audit as a supervisory measure. Through the audit, it is hoped that it will increase the awareness of taxpayers to fulfil their tax obligations and increase tax revenues. This study uses a descriptive qualitative approach with the type of case study. The author uses a target approach, a source approach and a process approach to analyse the effectiveness of tax audits as an act of supervising the self-assessment system and supporting tax revenue. The results of the study indicate that the tax audit is quite effective as an act of monitoring the self-assessment system. This is evidenced by a change in the behaviour of the taxpayers who have been audited. However, it is not effective enough to support tax revenue. The inhibiting factors include the amount of data that must be processed and analysed, facilities and infrastructure with limited capabilities. Efforts have been made to provide infrastructure, especially computers, which can process and analyse large amounts of data quickly, optimize data from internal parties and anticipate field inspections using zoom and being more selective.

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Tax evasion risk management using a Hybrid Unsupervised Outlier Detection method

Cited by 21 publications

References 19 publications

Taxes and social instability: How large corporations and wealthy taxpayers hide taxable money?

Taxes and social instability: How large corporations and wealthy taxpayers hide taxable money?

Simultaneous Classification and Regression for Zakat Under-Reporting Detection

The Effectiveness of Tax Audit as a Self Assessment System Supervision Measures and Tax Revenue Support (Study at the Large Tax Office 4)

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