How deeply does Financial AI in Practice cover KS?

Defines KS as a cumulative-distribution separation measure but does not detail a calculation procedure.

KS

As explained in Financial AI in Practice

The maximum difference between two cumulative distributions, often used to measure how well a model separates groups.

The Kolmogorov–Smirnov (KS) statistic measures the maximum difference between two cumulative distributions. In credit scoring, it indicates how cleanly a model separates good (nondefault) borrowers from bad (default) borrowers. section 4.4.1 section 1.4.2

Use KS alongside related credit-risk metrics, while keeping their roles distinct:

KS measures separation between good and bad borrowers. section 4.4.1
AUC measures predictive ranking power; PSI flags data drift as applicant populations or economic conditions change. section 4.4.1

How Financial AI in Practice covers it

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Related concepts

probability distributionmeasures · A probability distribution is a mathematical specification assigning probabilities to the possible values or outcomes of a random variable, with total probability one.
credit scoringmeasures · Credit scoring is the assessment or estimation of a person’s or organization’s creditworthiness to inform credit-related decisions.
credit risk modelmeasures · A credit risk model estimates the likelihood or consequences of credit-related outcomes, such as default or repayment failure, using information about a borrower.
scorecardmeasures · A predictive model that assigns points to input characteristics to estimate an outcome.

This explainer was generated by Manning's knowledge graph from the text of Financial AI in Practice. The section links point to the parts of the book it draws on.