Financial statements fraud identifiers

Contemporary research among fraud professionals indicates that organizations lose 5% of revenues from every year which makes the in this area and derivation detection models very important. The purpose article is to develop a new accounting tool will help companies investors prompt prevention can finally result preservation financial stability as well more efficient capital allocation. In context main objective test significance some statements positions’ relations has not been used previous using dataset SEC AAERs presented included Bao et al.’s combine them with existing ones consequently statement model. Another consists presenting most significant contemporary field comparing their quality ROC analysis. Research results were generated by SMOTE algorithm logistic regression analysis on 146,045 cases for period 1982 2014 point out five independent variables al. model comprised change free cash flow, percentage soft assets, sale common preferred stock, sales, receivables shows sufficient level discriminant power 67% under curve. derived could be starting preventing losses company stakeholders face.