Population stability index
The population stability index (PSI) is a measure of the difference between two probability distributions, often used to quantify shifts in a population or model inputs.
Financial AI in Practice
The population stability index quantifies changes between distributions of a variable or model population across time or samples.
- How it is used
- Monitors applicant-population drift in credit scoring as customer demographics or economic conditions change.
- How deep it goes
- Identifies PSI as a drift-monitoring metric but does not specify its calculation, thresholds, or response procedure.
- Examples
- Flags applicant-population shifts associated with changing customer demographics or economic conditions.
- What you can do after
- Diagnose potential population drift by using PSI to flag changes in credit applicants.
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Machine Learning System Design
The population stability index is a divergence measure that quantifies how a population's distribution differs from a reference distribution.
- How it is used
- Uses prediction drift as an early warning for possible future model-quality changes.
- How deep it goes
- Defines an operational threshold and compares PSI with Wasserstein distance, but defers final calibration to historical experimentation.
- Examples
- Illustrates monthly comparisons using growth-adjusted reference data, including a 15% increase between April 2021 and April 2022.
- What you can do after
- Operate prediction monitoring by testing PSI alerts alongside Wasserstein distance and validating thresholds against historical data.
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Related concepts
- data driftmeasures · Data drift is a change over time in the statistical distribution or characteristics of data relative to a reference distribution or set of characteristics.
- Evidently AImeasured by · Evidently AI is an open-source Python tool for evaluating, testing, monitoring, and reporting on machine-learning data, models, predictions, and behavior.
- ScorecardMonitoringused by · ScorecardMonitoring is a scorecard-monitoring component that evaluates changes in score distributions and related statistical indicators.
- Wasserstein distancealternative to · Wasserstein distance is a distance between probability distributions defined by the minimum cost of transporting probability mass between them under a specified ground distance.
- model calibrationuses · Model calibration is the assessment or adjustment of a model’s outputs, scores, or confidence so they correspond more reliably to observed outcomes or a reference standard.
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