Forecasting audit opinion based on multilevel perceptron neural network model using one-goal particle swarm optimisation

Abstract

Audit opinion is not necessarily absolute due to constraints inherent in any audit work, including sampling, different convincing degrees of audit evidence, accounting system and internal control characteristics, as well as inherent constraints of accounting measurement. The information contained in audit reports is used to forecast corporate bankruptcy; therefore, the auditor's opinion influences the views of users of financial statements. Financial status of a business can be assessed using financial ratios. The circumstances considered by an auditor in commenting on financial distress including financials (in particular, short-term liquidity, ability to repay and debt tolerability), and operations (profitability and ability to generate cash from operations). This study uses an integrated ANN-PSO to forecast audit opinion. The results show that ANN-PSO is more useful, because PSO algorithm can optimise hidden layers and neurons in ANN simultaneously. Finally, ANN-PSO outperforms ANN.

Auditor’s going-concern opinion prediction: the case of Slovenia

“…Criticism of audits and auditing in the aftermath of the 2007 global financial crisis gave an additional boost to such interest (Carson et al, 2013;Geiger et al, 2017;Sikka, 2009). Further, in the last decade, the availability of an array of novel methodological approaches has accelerated the development of various models, including audit models (Bahrami et al, 2020;Gepp et al, 2018;Guslawa et al, 2018;Stani si c et al, 2019;etc.). Authors used various modelling techniques to identify (classify) or predict firms with a going-concern opinion (Goo et al, 2016;Martens et al, 2008;Yeh et al, 2014).…”