It’s all about understanding the content and process
Understanding the documents is extremely valuable when setting up a successful AI OCR (Optical Character Recognition) solution. OCR technology is used to extract text and information from images or scanned documents, and its effectiveness depends on understanding the quality and relevance of the documents being processed. Here’s why understanding the documents is crucial:
- Document Variability: Documents can vary widely in terms of layout, fonts, languages, and formatting. Understanding the types of documents you will be processing helps in customizing the OCR system to handle these variations effectively.
- Preprocessing: Knowing the documents allows you to perform preprocessing tasks such as image enhancement, noise reduction, and deskewing, which can significantly improve OCR accuracy. Different document types may require different preprocessing steps.
- Language and Script Recognition: If your documents contain multiple languages or scripts, understanding the document content helps in configuring the OCR to recognize and process each language correctly.
- Layout Analysis: Understanding the document structure and layout enables the OCR system to identify headers, footers, tables, and other structural elements. This is crucial for preserving the document’s semantic meaning during OCR.
- Field Extraction: In the case of accounts payable (AP) automation, you do not need to extract text from the entire document but only specific fields or regions (e.g., extracting customer names, dates and amounts from invoices). Understanding the document layout helps in defining these regions for extraction.
- Error Handling: Recognizing common errors or variations in the documents allows you to implement error handling mechanisms, such as verifying extracted data against predefined patterns or rules.
- Training and Tuning: Training and fine-tuning the OCR model often require labeled data for supervised learning. Understanding the documents helps in creating training datasets that reflect the real-world variations present in your document collection. This is a crucial step often skipped when implementing packaged OCR software.
- Post-Processing: After OCR, you may need to perform post-processing tasks, such as data validation, or entity recognition. Knowing the context of the documents aids in designing effective post-processing routines.
- Performance Metrics: Understanding the documents helps in setting realistic performance metrics for your OCR solution. Different types of documents may have varying levels of difficulty, and you need to assess OCR accuracy accordingly.
- Scalability and Maintenance: Knowing the document types and potential future changes in document formats allows you to design a scalable and maintainable AI assisted OCR solution. You can plan for updates and improvements based on your understanding of the documents.
Over the years many companies have been disappointed when the promises of OCR have failed to deliver a return-on-investment. This often occurs because accuracy rates are too low, outputting bad data that can result in vendors being paid the wrong amount or worse yet the wrong vendors being paid! Add these to the high costs of post processing clean up and it is not hard to see why ROIs are not being achieved. However, the technology is not the problem, it is the process.
For a successful AI assisted OCR program to deliver an acceptable ROI it is critical that the first step be a thorough examination of the target documents, process, and expected results. Utilizing “real-world” documents (not random test documents), a series of tests can provide data on expected results giving decision makers the information needed to determine if the investment will provide the ROI needed. In summary, understanding the documents and process you’re working with is fundamental to the success of your AI OCR solution. With AI assisted technology, the tools are place, the question is can it deliver the saving to justify the investment? Do your due diligence before committing to a solution and choose a solution provider that will help you do your research and understand your documents. Let your solution partner help you to tailor the AI assisted OCR system to the specific needs of your document collection, resulting in higher accuracy and efficiency in text extraction and data processing.
Contact ICG Consulting today to start a conversation on how ICG’s AI assisted data capture solutions can deliver immediate value to your financial back-office. ICG will assist you in testing your documents and determining what results you might expect. You can also request a demo of one our data capture or comprehensive cloud-hosted AP automation solutions and see for yourself how your company can take advantage of the power of AI. For a quick view of ICG’s solutions view this short video.