Using Financial Statement Data To Identify Factors Associated With Fraudulent Financial Reporting

Abstract

Based on stepwise-logistic models, this study finds that financial leverage, capital turnover, asset composition and firm size are significant factors associated with fraudulent financial reporting Prediction results suggest that these models outperform a nae strategy of classifying all firms as nonfraud firms for all levels of relative costs of type I and type II errors. The models also correctly identify a large percentage of fraud firms and misclassify a relatively small percentage of nonfraud firms when realistic relative error costs are assumed.