Using Deep Learning Algorithms for CPAs’ Going Concern Prediction

Chyan-Long Jan

doi:10.3390/info12020073

Abstract

Certified public accounts’ (CPAs) audit opinions of going concern are the important basis for evaluating whether enterprises can achieve normal operations and sustainable development. This study aims to construct going concern prediction models to help CPAs and auditors to make more effective/correct judgments on going concern opinion decisions by deep learning algorithms, and using the following methods: deep neural networks (DNN), recurrent neural network (RNN), and classification and regression tree (CART). The samples of this study are companies listed on the Taiwan Stock Exchange and the Taipei Exchange, a total of 352 companies, including 88 companies with going concern doubt and 264 normal companies (with no going concern doubt). The data from 2002 to 2019 are taken from the Taiwan Economic Journal (TEJ) Database. According to the empirical results, with the important variables selected by CART and modeling by RNN, the CART-RNN model has the highest going concern prediction accuracy (the accuracy of the test dataset is 95.28%, and the average accuracy is 93.92%).

Highlights

The Global Financial Crisis of 2008–2009, which first occurred in the United States, and influenced the whole world, devastated the global economy
10 important variables are first selected by classification and regression tree (CART), which are used for deep learning by deep neural networks (DNN) and recurrent neural network (RNN) and repeatedly trained until stable, in order to construct the best model
Based on the above design, four going concern prediction models are constructed, and the results show that CART-RNN has the highest accuracy, followed by CART-DNN, RNN, and DNN

Summary

Introduction

The Global Financial Crisis of 2008–2009, which first occurred in the United States, and influenced the whole world, devastated the global economy. Many scholars have pointed out that, one of the main reasons was that CPAs and auditors failed to fulfill their audit responsibilities and even issued false audit reports [1,2,3,4,5], and some CPAs made wrong evaluations and opinions of the going concern and sustainability of enterprises. Persakis and Iatridis [3] pointed out that audit quality was generally reduced during the global financial crisis. The problem of going concern is stakeholders’ high concern and deep care regarding the information in the audit opinions of financial statements. The failure of CPAs and auditors to raise audit opinions of going concern doubt before enterprises enter bankruptcy or financial crisis will cause great damage to certified public accountants (CPAs) and accounting firms. The going concern assumption means that an enterprise will continue in business at its current scale and status for the foreseeable future, that is, an enterprise will continue in business for at least one year after the date on the Balance Sheet (GAAP) or the date of the Statement of Financial Position (IFRSs), and will not dissolve and liquidate [7]

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Conclusion