Profiling Companies with Internal Control Material Weaknesses Using the Data Mining Decision Tree Model

The Sarbanes-Oxley Act of 2002 requires management of publicly traded companies to assess their company’s internal control material weakness (MW) and to provide an internal control report as part of their periodic report to stockholders and regulators. The Public Company Accounting Oversight Board Auditing Standard 2 requires external auditors to issue an opinion on the effectiveness of their clients’ internal control. Even though the Act helped improve the quality and transparency of financial reports, a major concern has been expressed by many publicly traded companies about the increasing audit fees charged by external auditors. In this paper, we provide evidence that data mining can be used as a powerful tool to recognize and profile companies with material weaknesses in internal control. The decision tree model, in particular, reveals decision rules that can be used for auditors to assess whether a company under audit is more likely to fall into the class of MW companies or the class of non-MW companies. This type of information will help auditors not only enhance the effectiveness the audit but also reduce the cost of the audit.