Payables-Discrepancy-Automation

This project automates the reconciliation of billing and payables data, highlighting mismatches and exporting the results to a structured Excel file. Built for operational efficiency, it’s especially useful when auditing large datasets across multiple sources.

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##Features

• Uploads billing, payables, and member reference data
• Calculates discrepancies between expected and actual payouts
• Highlights off-balance transactions
• Produces an Excel report with formatting and summary analysis
• Built to run smoothly in Google Colab or locally as a .py script

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Requirements

• Python 3.7+
• pandas, openpyxl, xlsxwriter

To install dependencies:

pip install pandas openpyxl xlsxwriter

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##Files

File	Description
Payables_Reconciliation.py	Main Python script with full reconciliation logic
sample_billing.csv	Sample billing transactions
sample_payables.csv	Sample payables from the system
sample_members.csv	Sample member-product reference table

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##How to Use (Colab or Local)

1. Run the script
2. Choose report type: weekly or monthly
3. Upload the 3 required CSVs when prompted:
   • Billing
   • Payables
   • Member reference file
4. Receive a formatted Excel file with:
   • Billing File
   • Off-Balances
   • Full Analysis

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##Notes

• Thresholds:
  • Weekly: ±$0.20
  • Monthly: ±$1.00
• The logic assumes grouped totals by Member ID and Product ID
• This is a generalized version of a real-world automation and uses dummy data only

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##Why This Project? This automation was built to reduce manual reconciliation time, flag mismatches across disparate files, and generate audit-ready reports with minimal effort. It's especially useful in operations or financial workflows where transaction validation is critical.

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##Author Built by tamtural as part of an automation portfolio project. LinkedIn: Tamarl Christie

Feel free to reach out with questions!