CASE STUDY

Intelligent Invoice Automation

for a UK-Based Finance & Accounts KPO

How Zero Drag Automations delivered a 20X productivity increase by replacing manual data entry with custom-trained OCR and intelligent document processing.

KEY RESULTS

Productivity Increase

Reduction in Manual Effort

Person for approvals

0%+

Data Accuracy

Client Overview

Our client is a UK-based Knowledge Process Outsourcing (KPO) firm specialising in finance and accounting services. They manage accounts payable processing for multiple end-clients across diverse industries, handling thousands of supplier invoices each month.

Their core operation relied heavily on manual data entry, with a team of operators keying in invoice details line by line into the accounting system. As invoice volumes grew and client expectations tightened, this approach was becoming a bottleneck that threatened both accuracy and scalability.

CHALLENGE & SOLUTION

The Challenge

Large volume of invoices processed manually by multiple data-entry staff
Every supplier invoice followed a different format and layout
Varying tax codes, line-item structures, and currency conventions across invoices
High error rates and slow turnaround times due to manual handling
Off-the-shelf OCR tools failed due to the diversity of invoice formats

The Solution

Developed an in-house trained OCR model tailored to financial documents
Built custom parsing logic for each unique invoice format encountered
Automated extraction of key fields: vendor details, line items, tax codes, totals
Implemented an approval workflow where data is auto-populated for human review
Continuous model improvement as new invoice formats are introduced

How It Works

OUR APPROACH

Discovery & Audit We began by conducting an in-depth audit of the existing invoice processing workflow. This involved cataloguing the variety of invoice formats received, understanding the tax code structures, and mapping the end-to-end data flow from invoice receipt through to ledger posting.

Custom OCR Training Rather than relying on generic OCR software, we developed and trained an in-house OCR model specifically tuned for financial documents. The model was trained on real-world invoice samples from the client’s operations, allowing it to recognise and extract vendor names, addresses, line items, quantities, unit prices, tax codes, and totals with high accuracy.

Format-Specific Parsing Since every supplier’s invoice followed a different layout, we wrote custom parsing and mapping logic for each format. This ensured that regardless of how a supplier structured their invoice, the system could reliably extract the correct data and map it to the appropriate fields in the accounting software.

Approval Workflow We designed a streamlined approval interface where the auto-populated invoice data is presented to a single approver for review. The approver can verify, correct, or approve entries in seconds rather than minutes, dramatically reducing the human effort required.

Continuous Improvement As new supplier formats are encountered, our team adds custom parsing rules to the system. The OCR model continues to improve over time, learning from corrections and new data to increase accuracy further.

RESULTS & IMPACT

The automation transformed the client’s invoice processing operation:

Metric	Outcome
Content	20X increase in throughput — the same volume of invoices is now handled with a fraction of the previous effort
Staffing	Reduced from a full data-entry team to a single approver for the entire invoice workflow
Accuracy	Near-elimination of manual keying errors; data is extracted and validated programmatically
Turnaround	Invoice processing time reduced from hours to minutes per batch
Scalability	System handles growing invoice volumes without additional headcount
Cost Savings	Significant reduction in operational costs by replacing repetitive manual labour with automation

“Zero Drag Automations completely transformed how we handle invoices. What used to take an entire team now runs with one person reviewing auto-populated data. The accuracy and speed gains have been remarkable.”

— Operations Director, UK Finance & Accounts KPO