Credit Agent

Credit Drift Detection

Detects input and model drift in decision flows before it moves approval rates or losses.

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Where it Helps

The Credit Drift Detection agent monitors input variable health and model output stability inside every decision flow. It compares current data against a configurable baseline and flags statistically significant shifts before they affect business outcomes. Alerts are severity-ranked and sourced to the specific variable or score behind them, so operators can distinguish a benign population change from real model degradation before approval rates or losses move.

Key Capabilities

Input Variable Drift

Computes PSI and KS statistics on every continuous and categorical variable in a decision flow.

Null Rate Monitoring

Tracks missing-data rate per variable and alerts when it spikes relative to baseline.

Model Output Drift

Monitors score distribution and approval or decline rate against baseline to catch shifts at the decision level.

Configurable Baselines

Clients define baseline and current windows per flow, rolling or fixed, with independent evaluation frequency.

Severity-Ranked Alerts

Every alert is tiered Warning or Alert based on configurable thresholds, so teams triage by impact.

Cardinality Drift Detection

Flags new or disappearing categories in categorical variables versus the baseline distribution.

Full Alert Context

Every alert includes the variable, metric, current and baseline values, severity, and timestamp.

How it Works

Baseline Configured

Client sets the baseline window, current window, and evaluation frequency for a decision flow.

Agent Computes Drift

On schedule, the agent calculates PSI, KS, and null-rate metrics for every input variable and model output.

Thresholds Evaluated

Each metric is checked against configurable Warning and Alert thresholds.

Operators Are Alerted

Severity-ranked alerts are surfaced with full context before degradation reaches approval rates or losses.

Popular Use Cases

Credit Underwriting Flows

Early warning when applicant population or bureau data shifts before approval rates move.

Fraud Scoring Models

Detection of upstream data changes or population shifts that could mask emerging fraud patterns.

Third-Party Data Providers

Alerts when a vendor's data feed degrades, such as a null rate spike or distribution shift.

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Related Agents

Credit Memo Creation

First-draft credit memo narratives ready for underwriter review, not underwriter rewrite.

Credit Drift Detection

Detects input and model drift in decision flows before it moves approval rates or losses.

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