D18-F04-A03 · QUALITY & DISTRESS · SYNTHETIC DATA

Beneish M-Score

Change one synthetic accounting driver, watch eight indices and coefficient contributions recompute, and explain the result without crossing M equals the -1.78 screening cutoff.

The learning loop

1 · PredictName the direction before moving a driver.
2 · InspectFind the ratio, signal, contribution, or residual that changed.
3 · ReconcileTie the components to the raw score or model residual.
4 · BoundInterpret the screen without turning it into a finding.
Make a prediction before stepping

Base → current bridge

Scenario base
Current state
Headline delta

Keyboard: Left/Right step, Home resets, and Space plays or pauses when focus is outside a form control.

Current model output

Frozen equation

M = -4.84 + .920 DSRI + .528 GMI + .404 AQI + .892 SGI + .115 DEPI - .172 SGAI + 4.679 TATA - .327 LVGI

Component and diagnostic ledger

Changed cards are purple. Start here before interpreting the headline.

Response across 61 states

Model output across the selected accounting scenarioA deterministic synthetic sensitivity line with the current state marked.

Interpretation gate

Boundary: M equals the -1.78 screening cutoff

Visible intermediate: eight indices and coefficient contributions

Open exact point-in-time input and structured output

Input

Output


Synthetic teaching data only. A model score or residual is a historically specified screen—not an audit conclusion, rating, fraud finding, default forecast, or investment recommendation.