Corporate Failure Prediction Tools: A Comprehensive Analysis of Altman Z-Score and Argenti A-Score Models in Financial Distress Assessment

Prof. Aliyu IDRIS   Haruna DZUGWAHI; PhD

doi:10.56201/wjfir.v8.no5.2024.pg167.178

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Corporate Failure Prediction Tools: A Comprehensive Analysis of Altman Z-Score and Argenti A-Score Models in Financial Distress Assessment

Prof. Aliyu IDRIS Haruna DZUGWAHI, PhD

Abstract

Corporate Failure Prediction Tools are sophisticated analytical frameworks designed to assess and forecast the probability of financial distress and bankruptcy. These tools provide critical insights for investors, creditors, and financial analysts by evaluating a company's potential risk of economic collapse. The study examines two prominent models: the Altman Z- Score and Argenti A-Score methodologies. The Altman Z-Score, developed in 1968, utilises multiple discriminant analyses to evaluate five key financial ratios, categorising companies into safe, grey, and distress zones. The Argenti A-Score complements this approach by incorporating subjective managerial assessments and examining organisational defects, potential mistakes, and early warning symptoms. These prediction tools offer a comprehensive approach to understanding corporate financial health by integrating quantitative financial metrics and qualitative organisational indicators. The research underscores the importance of dynamic, multi-dimensional analysis in predicting and mitigating potential corporate failures.

Keywords

Corporate Failure PredictionFinancial Risk AssessmentBankruptcy Modeling

References

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Corporate Failure Prediction Tools: A Comprehensive Analysis of Altman Z-Score and Argenti A-Score Models in Financial Distress Assessment

Abstract

Keywords

References

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