Alternative data intelligence for credit decisioning

Overview

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World-class local demonstration stack

From client data intake to committee-grade documentation, deployment, and ongoing monitoring

This build is designed to show a complete, intuitive, and defensible credit decisioning workflow. The platform surfaces what was done, why it matters, what was excluded, why the champion was selected, how PDs were calibrated, and how the deployed package will be monitored.

Mounted business folders
Active project snapshot
Latest champion snapshot
What this build now enforces
Input data folder

Select a file to review schema, missingness, leakage watchlists, and project mapping candidates.

Dataset summary
Top missing fields
Leakage watchlist
Dataset sample preview
Active project mapping and feature controls
Active leakage exclusions
Blend the system suggestions with your own judgment. Hard-locked outcome fields remain excluded.
0 selected
Use Ctrl + click to add or remove fields from the editable leakage list.
System suggestions and hard-locked leakage
Suggested candidates can be removed from the editable list. Hard-locked fields remain excluded for governance safety.
Suggested leakage candidates
Hard-locked leakage fields
Additional feature exclusions
Use this to remove features you do not want to enter model training.
0 selected
Tip: use Ctrl + click to select multiple features.
Protected keep list
Use this for features you want the funnel to preserve where possible.
0 selected
Protected features still cannot bypass leakage, identifier, or hard-rule exclusions.
What the platform will do with your controls
Matured rows over time
Bad rate over time
Top missing fields
Segment and maturity breakdown
Feature EDA explorer
Choose a candidate feature to view stability, risk ranking, missingness, and univariate IV/Gini over time.
1. Stability over time
2. Risk ranking over time
3. Missing rate over time
4. Univariate IV and Gini over time
Feature funnel and modelling logic
Champion rule
Key exclusions, correlation pruning, and VIF control
Benchmark and challenger comparison
Run model factory

This step trains the benchmark and challengers, applies the champion-selection logic, fits the governance calibration layer, builds the deployment package, generates documentation, and writes monitoring/UAT artifacts into your folders.

Latest model comparison
Champion rationale
Final selected features
OOT AUC and KS by model
Raw versus calibrated PD on OOT buckets
Champion rationale and approval view
Documentation outputs
Top drivers and final feature set
Rank-order and calibration tables
Deployment package
UAT reconciliation
Sample scoring request
Scoring response
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Weekly average score
Weekly average PD
Weekly decision mix
Weekly score percentiles
Weekly feature PSI for champion features
Champion feature monitoring explorer
The monitoring explorer reuses the same 4-panel logic as Feature EDA, but only for features used in the latest champion model.
1. Champion feature stability
2. Champion feature risk ranking
3. Champion feature missingness
4. Champion feature IV and Gini
Monitoring exports