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Finance – Automated Expense Classification & Reporting

Architecture Level 1

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Finance Workflow Automation System

Architecture Level 2

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Component-Level Architecture

Architecture Level 3

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Detailed Data Flow Architecture

Snapshot 1

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Snapshot 2

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Automated Expense Classification & Reporting

1. Executive Summary

The Automated Expense Classification & Reporting project delivers a fully automated financial workflow for invoice handling, featuring ingestion, OCR extraction, rule-based categorization, and report generation using Power Automate, SharePoint, and Power BI. It achieves zero manual involvement, reduces processing time by 80%, handles 500+ invoices/month, and was completed in 8 weeks from September 25 to November 19, 2025, improving accuracy, compliance, and efficiency for finance teams.

2. Architecture Overview

The architecture employs a cloud-based pipeline:

Ingestion: Invoice triggers in Power Automate initiate the workflow.

Extraction: OCR extraction via AI Builder identifies key data points from documents.

Storage & Logic: Categorization logic is applied before updating SharePoint for storage and metadata management.

Analytics: Power BI refreshes automatically for real-time visualizations and financial reports.

This design ensures end-to-end automation (<1 min per invoice) with role-based security and full scalability.

3. Technology Stack

  • Workflows: Power Automate (Cloud Flows & Desktop)
  • AI/OCR: AI Builder (Form Processing models)
  • Data Management: SharePoint (Document Libraries & Lists)
  • Analytics: Power BI (DAX, Datasets, Scheduled Reports)
  • Ingestion: Microsoft Forms, Outlook (Email triggers)
  • Data Handling: Excel Online & Custom Expressions
  • Security: Microsoft 365 Encryption & Compliance

4. Automation Model and Features

Extraction: Captures fields like vendor, amount, and date with 98% accuracy.

Categorization: Automated conditional rules map expenses based on vendor or keywords.

Dashboards: Real-time Power BI dashboards with DAX measures for spend analysis.

Integrity: Zero manual intervention required, featuring anomaly notifications and full audit trails.

5. Data Processing

Data processing ingests invoices from sources (PDF/images), extracts via OCR, parses/standardizes to SharePoint columns, categorizes with rules, and syncs to Power BI datasets for reporting. Handles inputs like expense rules, outputs categorized data/reports, with retries for errors and scheduled refreshes; supports high-volume monthly processing with minimal latency and compliance.

6. Project Timeline (8 Weeks)

Timeline: September 25 – November 19, 2025

  • Week 1 (Discovery): Analyze processes, approve rules/requirements.
  • Weeks 2-3 (Design): Map workflows, design OCR templates/report layouts.
  • Weeks 4-6 (Development): Build automations, set up libraries/integrations.
  • Week 7 (Testing): Simulate processing, ensure UAT success.
  • Week 8 (Deployment): Roll out with monitoring, verify reports.

7. Testing & Deployment

Testing: Unit tests for individual flows; integration testing using 100+ invoice samples; UAT by the finance team verifying 98% accuracy.

Deployment: Final configuration of SharePoint libraries and AI models; published Power BI reports; includes an automated rollback to manual fallback if anomalies are detected.

8. Monitoring & Maintenance

Post-deployment monitoring utilizes Power Automate analytics to track flow performance and downtime. Maintenance involves periodic OCR model retraining to adapt to new invoice formats and quarterly compliance reviews to ensure data security and audit trail integrity.

9. Roles & Responsibilities

Methodology: Agile Sprints with Microsoft Planner tracking.

  • 🚀 Project Manager: Oversees Agile sprints, timelines, and stakeholder feedback.
  • ⚙️ Automation Specialists: Build and test Power Automate flows and AI integrations.
  • 📊 Data Analyst: Designs Power BI reports and ensures data model accuracy.
  • 💰 Finance Stakeholders: Provide business rules and validate categorization logic.