Automated Revenue Leakage Detection System

Augustus Chukwu

Completed work

AI Automation

Financial Consultant

Business Workflow Automation

N8N

Python

Supabase

E-Commerce

Automated Revenue Leakage Detection System for Marketplace Platforms

PROJECT OVERVIEW

Built a comprehensive revenue validation system that automatically detects and flags missing commission charges, pricing errors, and discount abuse in real-time for marketplace platforms. The system monitors 100% of transactions and identifies revenue leakage that billing systems miss, typically recovering $10,000-50,000+ in the first 30 days.

THE CHALLENGE

Marketplace platforms face a critical but invisible problem: they're losing 5-15% of their revenue without knowing it.

The issues are systematic:

Missing Commissions - Webhook failures, logic errors, or system glitches result in zero commission being charged when sellers receive payment. Each occurrence directly impacts bottom line.

Incorrect Commission Rates - Sellers remain on legacy pricing tiers after rate updates, or wrong rates are applied based on product category. The revenue gap compounds with every transaction.

Discount Code Abuse - Expired promotional codes remain active in the system, usage limits aren't enforced, or minimum purchase requirements are bypassed.

Underpriced Transactions - Products/services listed below minimum pricing thresholds generate insufficient commission revenue.

Free Trial Conversion Failures - Payment method failures or system errors result in users maintaining free access indefinitely.

The core problem: Billing systems (Stripe, Chargebee, etc.) charge exactly what they're told to charge. They don't validate whether that amount is correct based on your business rules.

Manual audits only catch 10-20% of transactions and detection delays of 2-3 months make recovery difficult.

THE SOLUTION

Designed and implemented a real-time validation layer that operates between your transaction system and billing platform, automatically validating every transaction against your pricing rules and business logic.

System Architecture:

5 Automated Workflows:

Transaction Monitor - Webhook receiver that captures every marketplace transaction and stores it in a centralized database

Transaction Validator - Validates actual commission charged vs. expected commission based on dynamic pricing rules, checks minimum pricing enforcement, detects calculation errors

Discount Validator - Verifies discount code validity (expiration, usage limits), validates minimum purchase requirements, confirms correct discount calculations

Daily Reporter - Aggregates findings by severity level (Critical/High/Medium), calculates total daily leakage amount, sends executive summary to finance team

Recovery Manager - Auto-assigns findings to team members using round-robin distribution, tracks recovery status and success rates

n8n workflow

Key Features:

✓ Real-time validation (catches issues within 24 hours)

✓ Severity-based prioritization (Critical > High > Medium)

✓ Automatic team assignment for recovery

✓ Comprehensive audit trail

✓ Daily executive reporting

✓ Multi-category pricing rule support

✓ Flexible discount validation logic

TECHNICAL APPROACH

Stack Selection:

n8n for workflow automation (visual workflows, easy maintenance)

Supabase for PostgreSQL database (real-time APIs, scalability)

Python for complex validation logic (precision in financial calculations)

Slack for alerting and notifications

Database Design:

pricing_rules - Category-based commission structure with version control

discount_rules - Promotional code definitions with usage tracking

transactions - Complete transaction history with leakage flags

leakage_findings - Detected issues with severity classification

daily_leakage_summary - Aggregated metrics for reporting

Key Technical Decisions:

Batch Processing Over Real-Time - After testing both approaches, implemented daily batch validation. Provides 99% of the value with significantly reduced complexity and improved reliability.

Python for Validation Logic - Complex commission calculations and edge case handling require precision. Python's decimal handling and readability made it the right choice.

Severity-Based Workflow - Not all leakage is equal. Critical issues (missing $1,000 commission) trigger immediate alerts, while medium issues (underpricing by $5) batch into daily reports.

Idempotent Workflow Design - All workflows handle re-runs gracefully, preventing duplicate findings and ensuring data consistency.

n8n python code node

MEASURABLE RESULTS

Test Implementation Results:

Scenario 1: Service Marketplace ($3M GMV)

Leakage detected: $47,000 (first 30 days)

Annual projected recovery: $240,000+

Primary issues: Missing commission (40%), Wrong rates (35%)

Detection time: Same day vs. 3 months manual audit

Scenario 2: E-commerce Platform ($8M GMV)

Leakage detected: $18,000 (first 30 days)

Annual projected recovery: $95,000+

Primary issues: Expired discounts (55%), Underpricing (30%)

Scenario 3: Rental Marketplace ($5M GMV)

Leakage detected: $31,000 (first 30 days)

Annual projected recovery: $165,000+

Primary issues: Free trial abuse (60%), Wrong rates (25%)

Operational Impact:

Before System:

Manual audits: 40 hours/month

Transaction coverage: 10-20%

Detection delay: 2-3 months

Recovery rate: 60%

After System:

Manual work: 2 hours/month (reviewing flagged items only)

Transaction coverage: 100%

Detection delay: <24 hours

Recovery rate: 85%

ROI Calculation:

Average first-month recovery: $30,000

Annual value: $150,000-250,000

System cost: $600/year (infrastructure)

Development time: 72 hours (now reusable)

ROI: 25,000%+

TECHNICAL IMPLEMENTATION DETAILS

Integration Points:

Webhook receivers for real-time transaction capture

REST API connections to Supabase

Slack Webhook API for notifications

Extensible to connect with Stripe, QuickBooks, payment processors

Validation Logic:

For each transaction:
  → Fetch applicable pricing rules (category + product type)
  → Calculate expected commission
  → Compare actual vs. expected (with 0.5% tolerance for rounding)
  → If variance detected:
    - Calculate leakage amount
    - Assign severity level
    - Create finding record
    - Trigger appropriate alert

Scalability:

Handles 10,000+ transactions per day

Database indexed for sub-second query performance

Workflows designed for horizontal scaling

Archive strategy for historical data

Maintenance:

Visual n8n workflows (non-developers can understand)

Comprehensive logging for debugging

Self-healing error handling

Automated health checks

DELIVERABLES

✓ 5 production-ready n8n workflow JSONs

✓ Complete Supabase database schema

✓ Sample data and test suite

✓ Full technical documentation (40+ pages)

✓ Installation and setup guide

✓ Troubleshooting manual

✓ SQL query library for analysis

✓ Postman collection for API testing

✓ Example webhook payloads

Open Source Release:

GitHub repository with MIT license

3,200-word technical article on dev.to

Community support via GitHub Issues

TECHNOLOGIES USED

Automation: n8n (workflow orchestration)

Database: Supabase (PostgreSQL with REST APIs)

Backend Logic: Python 3.9+ (financial calculations)

Alerting: Slack API

Version Control: Git/GitHub

Documentation: Markdown, Mermaid diagrams

IDEAL CLIENT PROFILE

This solution is perfect for:

Marketplace Platforms processing $500K+ monthly GMV who:

Charge commission or take-rate on transactions

Have multiple pricing tiers or categories

Offer promotional discounts

Run free trial programs

Need to ensure billing accuracy at scale

Typical Use Cases:

Service marketplaces (freelancing, consulting)

E-commerce platforms (multi-vendor)

Rental marketplaces (equipment, space, vehicles)

Gig economy platforms

SaaS marketplaces

BUSINESS VALUE PROPOSITION

For CFOs/Finance Leaders:

Recover 5-15% of revenue currently being lost

Real-time visibility into billing accuracy

Reduced audit overhead (98% time savings)

Executive dashboard for daily monitoring

Compliance and audit trail

For Technical Leaders:

Production-ready system in 2-4 hours

No vendor lock-in (open source stack)

Easy to customize for specific business rules

Scales with transaction volume

Low maintenance overhead

For Operations:

Automated finding assignment

Clear recovery workflows

Performance tracking by team member

Historical analysis capabilities

PROJECT TIMELINE

Phase 1: Research & Design (8 hours)

Marketplace leakage pattern analysis

Architecture design

Database schema design

Workflow blueprint creation

Phase 2: Core Development (40 hours)

Transaction monitoring workflow

Validation engine development

Discount validation logic

Database setup and optimization

Phase 3: Reporting & Recovery (16 hours)

Daily reporter workflow

Recovery manager workflow

Slack integration

Alert system configuration

Phase 4: Testing & Documentation (8 hours)

Test suite creation

Edge case validation

Documentation writing

Demo video production

Total: 72 hours (can be compressed to 40 hours for experienced implementations)

AVAILABLE FOR SIMILAR PROJECTS

I specialize in building custom financial automation solutions for growth companies facing expensive, manual operational challenges.

My Approach:

Understand the specific pain point and financial impact

Design a system that solves the root cause (not just symptoms)

Build using proven, scalable technology

Deliver with comprehensive documentation

Provide ongoing support and optimization

Other Financial Automation Solutions I Build:

Multi-processor payment reconciliation

Cash flow forecasting engines

Failed payment recovery systems

Commission calculation automation

Chargeback defense systems

Fraud detection workflows

Why Work With Me:

I run my own fintech company (real production experience)

Every system I build is battle-tested with real money

I focus on measurable ROI, not just "automation"

Transparent pricing and timeline estimates

Full documentation and knowledge transfer

PROJECT LINKS

📦 GitHub Repository: https://github.com/Etherlabs-dev/marketplace-leak-detector

📝 Technical Deep-Dive: https://dev.to/etherlabsdev/i-built-a-revenue-leakage-detector-that-saves-marketplaces-up-to-50kyear-open-source-4cgo

📧 Contact: ethercess@proton.me

🗓️ Book a Call: My calendar link

PRICING FOR CUSTOM IMPLEMENTATION

Option 1: Self-Implementation Support ($1,500)

2 hours of implementation consultation

Customization guidance for your business rules

30 days of Slack support

Code review of your setup

Option 2: Full Custom Implementation ($3,000-8,500)

Complete setup for your marketplace

Custom validation logic for your pricing structure

Integration with your existing systems

Team training (2 sessions)

90 days of support

Option 3: Build New Financial Automation (Starting at $3,500)

Discovery session to identify pain points

Custom system design

Full development and testing

Documentation and training

Ongoing support options

Interested in discussing your marketplace's revenue leakage?

Book a free 30-minute consultation to discuss your specific situation and see if this solution is right for you.

🗓️ Book a Call: My calendar link

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Completed work

Posted Dec 9, 2025

Developed a system to detect and recover revenue leakage for marketplace platforms.

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Timeline

Nov 1, 2025 - Nov 7, 2025