Salīdzināt metodes

	Kredīta novērtēšana (rezultātu kartes, WoE/IV)	Altmana Z-rezultāts: Korporatīvās maksātnespējas prognozēšana
Nozare	Finanses	Finanses
Saime	Regression model	Regression model
Izcelsmes gads	1997	1968
Autors	Hand & Henley; Thomas, Edelman & Crook	Edward Altman
Tips	Supervised binary classification model	Multiple discriminant analysis scoring model
Pirmavots	Hand, D. J., & Henley, W. E. (1997). Statistical classification methods in consumer credit scoring: a review. Journal of the Royal Statistical Society: Series A, 160(3), 523–541.	Altman, E. I. (1968). Financial ratios, discriminant analysis and the prediction of corporate bankruptcy. The Journal of Finance, 23(4), 589–609.
Citi nosaukumi	Credit Scorecard, Application Scoring, Behavioural Scoring, Kredi Skorlama	Altman's Z-Score Model, Multiple Discriminant Analysis Bankruptcy Model, Z-Score Financial Distress Model, Altman Z-Skoru
Saistītās	3	3
Kopsavilkums	Credit scoring is a statistical technique that estimates the probability that a borrower will default on a financial obligation. Using Weight of Evidence (WoE) binning, Information Value (IV) variable selection, and logistic regression, it converts raw applicant data into a single integer score. Formalized by Hand and Henley (1997) and elaborated by Thomas, Edelman, and Crook, the scorecard framework has become the regulatory standard for retail credit risk assessment in banking, lending, and insurance.	The Altman Z-Score is a linear discriminant model developed by Edward I. Altman in 1968 to predict corporate bankruptcy using five accounting-based financial ratios. Derived through multiple discriminant analysis on a matched sample of 66 US manufacturing firms, the model combines liquidity, profitability, leverage, solvency, and activity ratios into a single composite score that classifies firms as financially sound, distressed, or in a grey zone.