The Importance of Earnings Management Detection Models to Identify Fraud： A Case From Italian Listed Firms

Markets can get the confidence of investors enhancing the quality of governance and audit systems surrounding a firm. Financial reporting is a main component of them, being the basis for information necessary to investors＇ decisions. Managers have a chance to manipulate information provided in financial statements, in order to offer a better image of a firm to its potential and effective investors. The objective of this study is to evaluate the possibility of detecting extreme cases of earnings management and to check the predictive ability of the discretionary accruals models on the event of fraudulent earnings restatement. Through the abuse of reporting incentives, a manager gives out false information that should be averted and punished by regulators in a fair market system. The authors check the efficacy of different earnings management detection models in predicting discretionary manipulations and study the correlation between the frequency of manipulation and the event of fraud.