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ReviveCoding merged 1 commit into from
Oct 14, 2026
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Make README more concise and technically focused #1

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10 changes: 2 additions & 8 deletions README.md
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# PaymentOps Reliability AI Framework

A GitHub-clean, local-runnable financial AI reliability framework for PaymentOps-style risk routing, AML transaction behavior modeling, source-wise score calibration, review-capacity evaluation, retraining simulation, and governance-ready model validation.
A local-runnable financial AI reliability framework for PaymentOps-style risk routing, AML transaction behavior modeling, source-wise score calibration, review-capacity evaluation, retraining simulation, and governance-ready model validation.

This project uses external public/proxy CFPB and IBM AML-style datasets only. It does not use proprietary bank data, production payment logs, real customer account data, JPMC data, or regulatory certification artifacts.

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python -m pip install --upgrade pip
pip install -r requirements.txt

## GitHub-Clean Sample Run
## Local Sample Run

Run:

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- reports/score_alignment_blend_metrics.json
- reports/28_score_alignment_blend_resume_claims.md

## Resume-Safe Summary

Built a GitHub-clean PaymentOps reliability AI framework using external public/proxy CFPB and IBM AML datasets, with temporal validation, source-wise score calibration, review-capacity evaluation, operational backtesting, retraining simulation, and governance-ready reports.

Improved a combined text risk-routing baseline with source-wise isotonic score calibration and aligned routing on 523,927 rows, increasing PR-AUC by 15.0%, reducing Brier score by 76.9%, and lowering false auto-clear by 25.0% on a 130,982-row future test split.

## Author

Jinwoo Bae
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