Discovery Compliance

Discovery Compliance

Overview

Use this skill to turn statement productions into two deliverables:

• reviewable bank and credit-card index spreadsheets/CSVs
• bank and credit-card compliance matrices in markdown and Excel

Use scripts/run_matter.py as the main entry point. Keep the workflow in two phases so a paralegal can clean the extracted CSVs before matrix generation.

Main Entry Point

Phase 1: Extract For Review

python <skill-dir>\scripts\run_matter.py --phase extract --bank-folder "<bank-folder>" --credit-folder "<credit-folder>" --output-dir "<output-folder>" --bates-regex "<matter-regex>"

This creates:

• <output-folder>\bank\bank_statement_index.csv
• <output-folder>\bank\bank_statement_index.xlsx
• <output-folder>\credit\credit_card_statement_index.csv
• <output-folder>\credit\credit_card_statement_index.xlsx

Phase 2: Build Matrices After Cleanup

python <skill-dir>\scripts\run_matter.py --phase matrices --output-dir "<output-folder>" --year-start 2020 --year-end 2026

This creates:

• <output-folder>\bank_compliance_matrices.md
• <output-folder>\credit_card_compliance_matrices.md
• <output-folder>\compliance_matrices.xlsx

Convenience Mode

--phase all runs extraction and then stops with a reminder to clean the CSVs before matrix generation. It does not auto-build matrices.

Workflow Details

Extraction

Bank extraction uses:

• scripts/extract_bank_statements.py

Credit-card extraction uses:

• scripts/extract_credit_card_statements.py

Both extractors:

• walk folders recursively
• read page 1 first and page 2 only when needed
• use ocr_image.ps1 when text extraction is insufficient
• accept a matter-specific Bates regex with --bates-regex

Human Cleanup

Treat the cleaned CSVs as the source of truth for compliance matrices.

Conservative cleanup is appropriate:

• remove obvious OCR junk from Account Holder(s) Name(s)
• fill missing beginning dates when the inference is reliable usually use prior statement ending date plus one day when the same account has continuous statements if the production clearly uses month-end statements and no better source exists, first-of-month is acceptable
• normalize account numbers when the same account appears in both abbreviated and full form prefer one consistent display form within the matter, usually the folder-style short form or visible last four

Do not normalize across accounts unless the relationship is unambiguous.

Matrix Generation

Matrix generation uses:

• scripts/generate_compliance_matrices.py

The matrix builder:

• creates one account block per account label
• creates a row for every requested year
• places Bates numbers into each month touched by a statement's coverage period
• writes markdown plus a two-sheet Excel workbook

Expected Inputs

Expect the user to provide:

• a bank statement folder
• a credit-card statement folder
• an output folder
• a matter-specific Bates regex
• a year range for the matrix phase

If the user provides only one statement folder type, run only that extraction piece.

Dependencies

If imports fail, install:

python -m pip install pypdf openpyxl pymupdf pillow

These scripts rely on Windows PowerShell for OCR fallback.

Files

scripts/run_matter.py

Use as the main workflow entry point for paralegals.

scripts/extract_bank_statements.py

Use for bank-account productions.

scripts/extract_credit_card_statements.py

Use for credit-card productions.

scripts/generate_compliance_matrices.py

Use after CSV review to generate markdown and Excel matrices.

scripts/ocr_image.ps1

Use only as the OCR helper called by the Python extractors.