SZodixStudyAcademic Library
ShelvesOpen access
Study · an open academic library·Metadata from OpenAlex (CC0)·Shelves·OpenAlex metadata, de-duplicated
The Effects of Beneish’s M-Score Model and Financial Ratio Analyis on Fraudulent Financial Statement Indications
8 references·0 citing·31 second hop
The Effects of Beneish’s M-Score Model and Financial Ratio Analyis on Fraudulent Financial Statement Indications (2023)The Effects of Beneish’s M-Score Model an…Financial statement analysis (2019)Financial statement analysisEvaluasi Keakuratan Model Beneish M-Score Sebagai Alat Deteksi Kecurangan Laporan Keuangan (Kasus Perusahaan Pada Otoritas Jasa Keuangan di Indonesia) (2019)Evaluasi Keakuratan Model Ben…Predicting fraudulent financial reporting using artificial neural network (2017)Predicting fraudulent financi…Using Beneish model to detect corporate financial statement fraud in Greece (2016)Using Beneish model to detect…Detecting fraudulent financial reporting using financial ratio (2016)Detecting fraudulent financia…Financial ratios between fraudulent and non-fraudulent firms: Evidence from Tehran Stock Exchange (2015)Financial ratios between frau…Application of Beneish M-Score Models and Data Mining to Detect Financial Fraud (2015)Application of Beneish M-Scor…Accountability in Financial Reporting: Detecting Fraudulent Firms (2014)Accountability in Financial R…FINANCIAL RATIOS, DISCRIMINANT ANALYSIS AND THE PREDICTION OF CORPORATE BANKRUPTCY (1968)The Financial and Market Effects of the SEC's Accounting and Auditing Enforcement Releases (1991)An Empirical Analysis of the Relation between the Board of Director Composition and Financial Statement Fraud (1997)An Analysis of Fraudulent Financial Reporting Using the Fraud Diamond Theory Perspective: An Empirical Study on the Manufacturing Sector Companies Listed on the Borsa Istanbul (2020)Is the fraud diamond perspective valid in Kenya? (2020)The Detection of Earnings Manipulation (1999)Relationship between Financial Ratio and Financial Statement Fraud Risk Moderated by Auditor Quality (2019)DETECTION OF FRAUD INDICATIONS IN FINANCIAL STATEMENTS USING FINANCIAL SHENANIGANS (2020)Scoring the financial distress and the financial statement fraud of Garuda Indonesia with «DDCC» as the financial solutions (2021)Detecting false financial statements using published data: some evidence from Greece (2002)Manajemen Laba: Ukuran Perusahaan, Kepemilikan Manajerial dan Kompensasi Bonus (2019)The Influence of Corporate Governance on the Mitigation of Fraudulent Financial Reporting (2020)Using the Beneish M-score model: Evidence from non-financial companies listed on the Warsaw Stock Exchange (2020)An Index of Factorial Simplicity (1974)Causes and Consequences of Earnings Manipulation: An Analysis of Firms Subject to Enforcement Actions by the SEC* (1996)The risk of financial fraud: a management perspective (2020)Forensic accounting tools for fraud deterrence: a qualitative approach (2022)Predicting financial distress in TSX-listed firms using machine learning algorithms (2024)Detecting GAAP violation: implications for assessing earnings management among firms with extreme financial performance (1997)Bankruptcy Risk Prediction in Ensuring the Sustainable Operation of Agriculture Companies (2021)Creative Accounting Determinants and Financial Reporting Quality: Systematic Literature Review (2022)Forecasting with artificial neural networks: (1998)Audit committee, board of director characteristics, and earnings management (2002)Artificial intelligence and big data: ontological and communicative perspectives in multi-sectoral scenarios of modern businesses (2022)Artificial intelligence and machine learning in finance: A bibliometric review (2022)Earnings management: a three-decade analysis and future prospects (2023)Accounting Methods and Differential Stock Market Response to the Announcement of Earnings (1993)Predicting returns with financial ratios (2004)How does working capital management affect the profitability of Spanish SMEs? (2011)The Fraud Diamond: Considering the Four Elements of Fraud (2004)The New Fraud Triangle Model (2012)
this work references cited by second hop

References

  • 2015Application of Beneish M-Score Models and Data Mining to Detect Financial Fraud154 cited
  • 2017Predicting fraudulent financial reporting using artificial neural network109 cited
  • 2016Using Beneish model to detect corporate financial statement fraud in Greece103 cited
  • 2014Accountability in Financial Reporting: Detecting Fraudulent Firms98 cited
  • 2016Detecting fraudulent financial reporting using financial ratio95 cited
  • 2015Financial ratios between fraudulent and non-fraudulent firms: Evidence from Tehran Stock Exchange61 cited
  • 2019Financial statement analysis37 cited
  • 2019Evaluasi Keakuratan Model Beneish M-Score Sebagai Alat Deteksi Kecurangan Laporan Keuangan (Kasus Perusahaan Pada Otoritas Jasa Keuangan di Indonesia)12 cited

Cited by

No citing works inside the corpus for this window.

Only edges whose both ends are imported exist here. Widen the year window, or show the whole map. Back to the work