Shipping Carrier Rate Reconciliation
Detects shipping rate variances by reconciling carrier invoices against Bill of Lading weight and accessorial charges, flagging overbilling patterns automatically.
The Problem
Major shipping carriers systematically overbill by hiding surcharges, inflating dimensional weights, and applying duplicate fees. Monthly audits catch 3-8% billing variance, but manual reconciliation of 5,000+ invoices against Bills of Lading is operationally impossible, leaving companies to absorb hundreds of thousands in overages yearly. FedEx and UPS deliberately obscure charge structures to make discovery hard; systematic overbilling detection is the only path to refund recovery and carrier leverage in contract renegotiations.
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Logic Core
- 01Match invoice weight against Bill of Lading
- 02Detect fuel surcharge, detention, dimensional weight abuse
- 03Flag refund-eligible variances with trend analysis
Recommended Tech Stack
Implementation Blueprint
1. Deploy AWS Textract to OCR and extract tables from carrier invoice PDFs
2. Build a PostgreSQL schema linking invoices to Bills of Lading (BOLs) by shipment ID
3. Implement a 3-layer variance detection: weight matching, accessorial anomalies, trend analysis
4. Automate 'Dispute Ready' PDF reports with trend charts and refund recommendations
5. Track monthly overbilling patterns per carrier to build negotiation leverage
AI Starter Prompts
Write a Python function using AWS Textract to extract line items from FedEx/UPS invoice PDFs with 95%+ accuracy
Design a PostgreSQL schema for joining invoices to BOLs with support for multi-leg shipments and accessorial charges
Build a ReportLab-based PDF generator that produces carrier dispute letters with trend charts and refund amounts
Source Reference
https://github.com/datumfoundry/datum-foundry-vault/tree/main/mvp-carrier-rate-reconciliationEnjoyed this blueprint?
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