This Financial Risk Analysis toolkit consists of three models namely: The Altman Z Score and its variants for identifying financial distress. The Ohlson O-Score for identifying financial distress. The Beneish M-Score for identifying earnings manipulation.
Altman Z Score
The Altman Z-score was formulated originally to be applied to public manufacturing companies as a scoring tool to identify corporations at risk of bankruptcy. The score is determined by a multivariate formula which has proven to be 80% to 90% reliable in predicting bankruptcy.
The original data sample consisted of 66 firms, half of which had filed for bankruptcy. A Multiple Discriminate Analysis was performed to identify which combination of ratios and factors best discriminated between firms that failed and firms that did not.
Ohlson O-Score
Ohlson O-Score (developed in 1980 by James Ohlson) is a logistic regression-based bankruptcy prediction model.
It serves as a strong alternative (and often more accurate) to the Altman Z-Score for forecasting the probability of corporate financial distress or bankruptcy within two years.
Beneish M-Score
Beneish M-Score (developed by Professor Messod Beneish in 1999) is a statistical model designed to detect earnings manipulation (financial statement fraud) rather than outright bankruptcy risk.
It identifies companies that are likely 'cooking the books' by inflating revenues, deferring expenses, or manipulating accruals.
