Risk-Based Audits in a Behavioural Model

Hashimzade, N.; Myles, G.

doi:10.1177/1091142115602062

Risk-Based Audits in a Behavioural Model

Hashimzade, N.; Myles, G.

Authors

N. Hashimzade

G. Myles

Abstract

The tools of predictive analytics are widely used in the analysis of large data sets to predict future patterns in the system. In particular, predictive analytics is used to estimate risk of engaging in certain behavior. Risk-based audits are used by revenue services to target potentially noncompliant taxpayers, but the results of predictive analytics serve predominantly only as a guide rather than a rule. “Auditor judgment” retains an important role in selecting audit targets. This article assesses the effectiveness of using predictive analytics in a model of the compliance decision that incorporates several components from behavioral economics: subjective beliefs about audit probabilities, a social custom reward from honest tax payment, and a degree of risk aversion that increases with age. Simulation analysis shows that predictive analytics are successful in raising compliance and that the resulting pattern of audits is very close to being a cutoff rule.

Citation

Hashimzade, N., & Myles, G. (2017). Risk-Based Audits in a Behavioural Model. Public Finance Review, 45(1), 140-165. https://doi.org/10.1177/1091142115602062

Journal Article Type	Article
Acceptance Date	Jul 9, 2015
Online Publication Date	Sep 1, 2015
Publication Date	Jan 1, 2017
Deposit Date	Jul 13, 2015
Publicly Available Date	Jul 20, 2015
Journal	Public Finance Review
Print ISSN	1091-1421
Electronic ISSN	1552-7530
Publisher	SAGE Publications
Peer Reviewed	Peer Reviewed
Volume	45
Issue	1
Pages	140-165
DOI	https://doi.org/10.1177/1091142115602062
Keywords	Tax compliance, Audits, Behavioral.
Public URL	https://durham-repository.worktribe.com/output/1425385

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Copyright Statement
Hashimzade, N. and Myles, G. (2017) 'Risk-based audits in a behavioural model.', Public finance review., 45 (1). pp. 140-165. Copyright © 2015 The Author(s). Reprinted by permission of SAGE Publications.