Challenges in auditing fair value measurement and accounting estimates
Babajide Oyewo, Ebuka Emebinah, Romeo Savage
Abstract
Babajide Oyewo, Ebuka Emebinah, Romeo Savage
Abstract
Purpose Following the issuance of International Financial Reporting Standard 13 on fair value measurement (which became operational from January 2013), this study aims to investigate post-implementation challenges in the audit of fair value measurement and accounting estimates in the Nigerian context. Design/methodology/approach Data-collection was through a structured-questionnaire administered on 400 auditors from diverse backgrounds in terms of audit firm size, international affiliation and global presence. Findings Empirical data obtained from 277 auditors were analysed using descriptive statistics, factor analysis, one-way ANOVA, cluster analysis, independent samplet-test and one-way multivariate analysis of co-variance. It was observed that the two highest-ranking and most-prevalent challenges of auditing fair value measurement and accounting estimates are the tendency for managers to manipulate earnings owing to the inability of auditor to effectively test fair value estimates; and the difficulty in testing unobservable inputs due to the application of assumptions and judgement in arriving at estimates by preparers of financial reports. Originality/value While there is no significant difference in the perception of auditors on the audit challenges associated with fair value measurement and accounting estimates, there is a significant difference in the magnitude of audit challenges faced in verifying fair value measurements and accounting estimates across industry sectors. Concerned stakeholders (including but not limited to accounting regulators, auditing standard setters, audit firms, researchers) are importuned to come up with robust and pragmatic measures to curtain these challenges, as the inability of auditors to rigorously verify fair value estimates may jeopardize the very essence of fair value measurement which is to elevate financial reporting quality.
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Purpose Following the issuance of International Financial Reporting Standard 13 on fair value measurement (which became operational from January 2013), this study aims to investigate post-implementation challenges in the audit of fair value measurement and accounting estimates in the Nigerian context. Design/methodology/approach Data-collection was through a structured-questionnaire administered on 400 auditors from diverse backgrounds in terms of audit firm size, international affiliation and global presence. Findings Empirical data obtained from 277 auditors were analysed using descriptive statistics, factor analysis, one-way ANOVA, cluster analysis, independent samplet-test and one-way multivariate analysis of co-variance. It was observed that the two highest-ranking and most-prevalent challenges of auditing fair value measurement and accounting estimates are the tendency for managers to manipulate earnings owing to the inability of auditor to effectively test fair value estimates; and the difficulty in testing unobservable inputs due to the application of assumptions and judgement in arriving at estimates by preparers of financial reports. Originality/value While there is no significant difference in the perception of auditors on the audit challenges associated with fair value measurement and accounting estimates, there is a significant difference in the magnitude of audit challenges faced in verifying fair value measurements and accounting estimates across industry sectors. Concerned stakeholders (including but not limited to accounting regulators, auditing standard setters, audit firms, researchers) are importuned to come up with robust and pragmatic measures to curtain these challenges, as the inability of auditors to rigorously verify fair value estimates may jeopardize the very essence of fair value measurement which is to elevate financial reporting quality.
Key concepts: Accounting, Audit, Fair value, Context (archaeology), Business, Variance (accounting), Judgement, Actuarial science