Invoice Capture: Benefits, Use Cases, & Top Vendors in 2024

Invoice capture is rapidly transforming how organizations process supplier invoices. By automatically extracting key data from invoices, this technology eliminates slow and error-prone manual data entry, delivering major efficiency gains and cost savings.

This comprehensive guide will explore:

  • The basics of invoice capture and how it works
  • Cost saving and productivity benefits
  • Top use cases by industry
  • Leading solutions comparison
  • Implementation best practices
  • The future outlook for invoice automation

Let‘s dive in!

What is Invoice Capture & How Does it Work?

Invoice capture, also called invoice data extraction or invoice OCR, is the use of AI technologies to automatically identify and extract relevant data from paper and digital invoices.

It enables hands-free processing and approvals by removing the need for humans to manually enter invoice header data prior to posting the transaction in enterprise resource planning (ERP) platforms or accounts payable systems.

Invoice capture works by combining:

  • Optical character recognition (OCR) – Converts scanned or printed document images into machine-readable text data.
  • Natural language processing (NLP) – Enables software to understand free-form human language and grammar.
  • Machine learning – Algorithms detect patterns and relationships in large datasets to continuously improve over time.

By leveraging these technologies, invoice capture solutions are trained on millions of sample invoices to identify common fields and data patterns. This allows the software to automatically locate and extract important invoice header details such as:

  • Supplier name
  • Invoice number
  • Date
  • Purchase order number
  • Line item descriptions
  • Quantities
  • Unit prices
  • Tax amounts
  • Total amount due
  • Bank details

And more.

Advanced systems can even detect tables and recurring structures in the documents to pull out line item data correctly.

OCR technology reading text

Invoice capture utilizes OCR to convert printed or scanned documents into digital data

This extracted data can then be exported into back-office systems like ERPs or accounting platforms, eliminating the need for manual data entry.

As the solution processes more invoices, machine learning allows the algorithms to become more accurate over time. Human users can also provide feedback on errors which further improves the AI.

This enables highly automated invoice processing at scale.

The Benefits of Invoice Automation

Transitioning to automated invoice capture provides significant benefits:

1. Dramatically Lower Processing Costs

Manually entering data from invoices is hugely expensive and time-consuming. It requires teams of accounts payable (AP) staff and data entry clerks devoted to the task.

Research shows:

  • AP processing costs organizations an average of $17 per invoice involving manual steps (IBM).
  • 70% of AP costs are related to manually processing invoices (McKinsey).

Invoice automation reduces the manual processing labor required by 50-70%, delivering significant cost savings.

2. Faster Processing & Approvals

Manually processing invoices is extremely slow, taking AP staff 2-4 minutes per document on average (Ardent Partners).

Automated data extraction by AI is up to 4X faster, with turnaround times reduced from weeks to just hours or days (AWS).

This prevents late fees, improves supplier relationships, and gives real-time visibility into payables.

3. Increased Accuracy

Human data entry results in errors up to 5% of the time (ABBYY), leading to incorrect payments, compliance issues, and wasted time resolving mistakes.

Automated invoice capture has an accuracy rate of over 98%, delivering near perfect results.

4. Enhanced Control & Visibility

With faster access to invoice data, organizations gain increased visibility into accounts payable. This allows for proactive tracking of spending patterns, cash flow optimization, and dynamic forecasting.

Automated workflows and approvals also provide control and auditability over the entire procurement-to-payment process.

5. Reduced Compliance Risk

Accurate data extraction minimizes the risks associated with financial compliance for taxes, regulatory reporting, and internal policies. Invoice anomalies get flagged earlier.

In summary, leading companies are realizing 50-80% cost reductions in AP processing while simultaneously improving efficiency, accuracy, and financial control.

Top Use Cases by Industry

Invoice automation provides value across many different sectors and use cases:

Manufacturing

Manufacturers receive high volumes of supplier and subcontractor invoices with complex billing structures. Intelligent data capture optimizes their procure-to-pay cycle.

Results:

  • Global manufacturer Cummins reduced invoice processing by 80% using AI extraction (AWS Case Study)

Financial Services & Insurance

Banks, insurance firms, and other financial institutions have large volumes of customer invoices and paperwork. Automating the capture and extraction of this data accelerates operations.

Results:

  • Brazilian bank Banco Santander saw a 90% drop in invoice processing time with AI (ABBYY Case Study)

Healthcare

Hospitals and health systems receive high volumes of patient invoices and insurance claim forms. Invoice automation enables frictionless revenue cycle management.

Results:

  • When AI invoice capture was implemented at a major hospital, time spent on manual data entry reduced by 25 hours per week (Hyperscience Case Study)

Retail & Ecommerce

Retailers have large volumes of purchase orders and supplier invoices. Intelligent automation optimizes their procure-to-pay processes.

Results:

  • UK retailer New Look achieved 99% accuracy in invoice data extraction with AI (Rossum Case Study)

Construction

Construction firms receive high volumes of vendor invoices for materials, equipment rentals, and subcontractor services on job sites. Automation provides major AP efficiencies.

Results:

As these examples demonstrate, organizations across industries stand to benefit tremendously from automated invoice capture.

How Invoice Automation Solutions Compare

Many vendors now provide AI-powered invoice capture and data extraction solutions. Here we‘ll compare some of the top options:

Solution Description Pricing Model Strengths Limitations
Rossum AI specifically built for structured data extraction from invoices Volume-based pricing Specialized AI delivers high accuracy for invoices; great for mid-market Limited to invoice documents
Amazon Textract Cloud API for document text and data extraction Pay per page pricing Leverages Amazon‘s advanced ML cloud capabilities Can have inconsistent output formats
ABBYY FlexiCapture On-premise and cloud data capture platform Perpetual license or subscription Mature product with strong learning capabilities Higher complexity to configure
Hyperscience Intelligent document processing for structured data extraction Enterprise pricing End-to-end automation beyond just data extraction Requires involvement of their professional services
UiPath Accounts Payable Automation platform with integrated invoice OCR Per user subscription pricing Tight integration between data capture and downstream RPA bots Focused on the UiPath ecosystem
Parascript InvoiceXpress Self-learning invoice capture solution Subscription pricing Flexible deployment options including on-premise Better suited for high-volume enterprise use cases
Docufree Intelligent document processing tailored for AP Monthly subscription Affordable for SMBs Less advanced machine learning capabilities
AgileDark Open source document data extraction Free community version Avoid vendor lock-in with open source Requires technical resources to implement

This comparison highlights key differences between solutions when it comes to the underlying technology, pricing models, strengths, and limitations.

Selecting the right product depends on your invoice volumes, use cases, budget, and more. Evaluating solutions specifically using a sample of your own documents is recommended to test accuracy.

On-Premise vs SaaS Considerations

Invoice capture solutions are available both as on-premise software as well as cloud-based SaaS models:

On-Premise

  • Installed directly on company infrastructure
  • Requires internal IT resources to maintain
  • Better supports customization
  • Keeps data behind company firewall

SaaS

  • Hosted on vendor cloud infrastructure
  • Lower implementation effort
  • Subscription-based pricing
  • Easier scaling
  • Accessible from anywhere

Companies with higher security or customization needs may prefer on-premise options. But SaaS models are easier to adopt, especially for smaller businesses or those wanting quicker time to value.

Hybrid deployment options are also available, such as:

  • On-premise software with cloud-based ML training
  • Private cloud models

Driving Successful Implementation

Here are best practices to roll out invoice automation for maximum results:

Clean Up Invoice Process First

Standardize formats and label positions before deploying extraction tools. This improves accuracy.

Implement Data Validation Checks

Configure automated multi-step verification of extracted data before invoice posting. Flag outliers for review.

Start Small, Then Scale

Run controlled pilots on targeted invoice groups before expanding to all suppliers and spend categories.

Refine The AI with Ongoing Training

Leverage human-in-the-loop to keep improving algorithm accuracy through continuous feedback.

Integrate With Procurement Systems

Link new invoices back to original purchase orders and supplier master data for greater context.

Monitor Performance Metrics

Track KPIs like accuracy rate, exceptions, processing cost per invoice and cycle times to quantify benefits.

Get Stakeholder Buy-In

Educate IT, AP, Procurement and other teams early on to build institutional knowledge around automation.

Emerging Trends and the Future of Invoice Capture

Invoice automation is an area seeing rapid innovation, with AI and machine learning models continuously evolving. Key trends to watch:

  • Wider document support beyond invoices, including purchase orders, remittances, checks, ID cards and more
  • Integration of extraction tools into core enterprise platforms like SAP, Oracle, Workday
  • Rise of self-learning models needing less and less training over time
  • Industry-specific solutions tailored for construction, manufacturing, healthcare verticals
  • End-to-end procure-to-pay platforms integrating capture capabilities natively
  • Adoption of cloud and SaaS delivery models providing scalability

As these trends progress, invoice automation will become an indispensable component of modern digital finance operations.

Conclusion

Invoice capture provides a high-ROI way to eliminate manual invoice processing, accelerating cycle times while reducing costs up to 80%.

By leveraging AI-driven data extraction, organizations can unlock new levels of efficiency and visibility across their procure-to-pay processes. This in turn provides strategic benefits, freeing up employees from repetitive tasks to focus on more value-added analysis.

Leading solutions like Rossum, Amazon Textract, Parascript, and ABBYY FlexiCapture make invoice automation accessible for organizations of all sizes. When combined with digital workflows, advanced capture capabilities open the door to true touchless invoice processing.

This guide provided a comprehensive look at everything business leaders need to successfully adopt invoice automation, from understanding the technology, to comparing top vendors, to implementing for maximum impact.

Is your organization looking to modernize finance operations? Now is the time to leverage intelligent document capture and join the leaders automating their order-to-cash processes. Reach out to discuss how we can help you launch your first extraction project and demonstrate bottom-line results.