Can AI-Powered OCR Recognize Handwriting?

Optical character recognition (OCR) for handwriting: something once considered impossible to achieve, and now it’s here. But what is it, how does it compare to traditional OCR – and how does it actually work? Let’s explore each of these in turn.

What Is Handwriting OCR?

Handwriting OCR is the process of automatically extracting handwritten text from paper, scans and other low-quality digital documents. Some OCR applications will then convert scanned handwritten notes into digital text. In other words, it takes your notes from pen to print to digital data.

While the definition of handwriting OCR is relatively straightforward, the process itself? Not so much. To really understand the impact of OCR technology, let’s take a look at the differences between traditional OCR, the kind of OCR that can read handwriting and then how artifial intelligence (AI) is changing the game.

Traditional OCR

Before handwriting OCR, there was traditional OCR (optical character recognition). This is what helped shape the meaning behind the phrase optical character/text recognition.

• Optical: relating to sight.
• Character: printed or written symbols, letters or numbers.
• Recognition: identifying something from previous encounters.

Traditional OCR is all about technology that has “studied” fonts and symbols enough to be able to identify almost all variations of machine-printed texts. But therein lies the limitations of traditional OCR: while it’s great when you want to extract text from scanned paper, it can’t read handwriting. There is simply too much variety for it to try accurately processing documents.

The challenges of traditional OCR

For a while, traditional OCR was all we had. So, organizations had to take a few shortcuts to make up for its limitations and get the work done.

Traditional text OCR could handle the easy stuff – about 80 percent of document workflows. For the more complicated stuff (like scanning handwritten documents), humans had to intervene and perform manual data entry, which took a considerable amount of time and effort. While 20 percent of manual data entry is better than 100 percent, this two-tiered capture system – OCR versus humans – was burdensome and created three major challenges:

• Accuracy: mistyping and exception handling.
• Resources: difficult to source talent willing and able to manually extract handwriting.
• Security: the transfer from machine to human back to the machine created concern, especially because the people using the technology were in tightly regulated industries with sensitive information, like financial services, government and healthcare.

For years, organizations simply accepted that this was the extent of OCR’s capabilities. An effective handwriting recognition software seemed impossible. Eventually, people stopped looking for it, resigning themselves to dealing with a two-tiered capture system.

Is there a software to decipher handwriting?

There are many tools for deciphering and converting your handwriting that utilize OCR, but finding one that also includes AI is less common.

Intelligent document processing (IDP) solutions such as SS&C | Blue Prism® Decipher IDP allow you to customize form templates to validate, format and organize data entering your systems, then validate it to ensure it’s correct. And it’s all done with an easy-to-use, low-code user interface (UI) so you don’t need to be a tech expert to get it working.

Is There an AI That Can Read Handwriting?

In fact, there is! Some organizations are even looking at how they can use generative AI for document extraction and processing. Generative AI uses a large language model (LLM) and machine learning to comprehend and generate natural language among other things. Organizations are finding more uses for their AI models while maintaining governance through enterprise AI-level guardrails to ensure accuracy and compliance.

In the example of a contract agreement, a user can ask the gen AI to highlight specific keywords from the document or summarize certain clauses. They can specify the responses they want, extract and format data, and even review it.

As this technology evolves, it will continue to improve and have more business use cases where AI acts as a digital assistant to people. It could even help read historical documents and record crucial data that we thought we’d lost. 

Handwriting OCR Applications

Any business burdened with massive amounts of information arriving on paper and under constant pressure to “do more with less” can benefit from handwriting OCR. Paperwork processing – a necessary evil for many organizations – is one such example. Processing is common for insurance and healthcare organizations. It’s painful because it often steals away time and resources for manual data entry. Handwriting OCR allows them to reallocate resources by turning pen to print. That is, digital print.

Here are a few more areas where it can help:

• Insurance
• Claims Automation
• Business reply cards
• Underwriting analytics
• Patient enrollment
  
• Prescription preauthorization

Beyond automating the processing workflows, handwriting OCR also provides a level of data access that produces better analytics and decision-making. Before this type of OCR, teams were just processing paper to get the job done. Now, they can process paper and make the job better.

How Does Handwriting OCR Work?

Handwriting OCR achieves what traditional OCR never could in its ability to convert handwriting to text easily. But getting to the point where you can scan text files involved a lot more than just creating “better software.” Here’s how it works:

Artificial intelligence, machine learning and computer vision engines

If your business or organization needs a handwriting OCR solution, do your homework. Not every provider does it the same way and there are a lot out there. Words like “AI” and “machine learning” are tossed around a lot. But few can back it up with explanations of how their technology works. Finally, when it comes to numbers around accuracy and performance, look for only the most transparent vendors.

Think of OCR scanner applications like Adobe Scan, which is a downloadable app for your mobile device where you can select an image-to-text option to turn handwritten documents into PDFs. Of course, then you need to open the PDF on Adobe Acrobat and use the edit PDF tool to convert handwritten notes into editable text, which you must manually edit. When searching for the right OCR software, consider how you would like to apply it specifically to your business.

Technology

• Is their IDP solution AI-powered or is it just a well-marketed, human data entry and machine hybrid? Can it directly convert handwritten notes to text?
• What level of intelligence do their OCR algorithms have?
• Can they explain the math behind their solution? What kind of ML models do they employ?

Accuracy

• Can they accurately recognize handwriting? Can they provide an accurate number (e.g., 95%, 99%, etc.)?
• Can they provide accurate numbers for every process they perform and every document they read and extract?

Experience

• Are they a fresh startup or have they been doing it for years?
• Why are they in the OCR game? SS&C | Blue Prism® Document Automation got started doing crowd data entry. This is what gave us the largest human-verified dataset (1 billion+ fields) in the industry.

Ease of use

• What are their OCR features? Do they offer a cloud-based SaaS solution, or must you host it onsite?
• How soon before you can start using the product? Many providers take about 6 months to a year to achieve high-level accuracy. Our Document Automation offers it on Day 1.
• How much training is required? If it’s an AI-powered platform, will you need ML expertise on staff? Or will the provider handle everything (like we do)?

Business case

• Do they have experience solving real business issues with their technology?
• Have they imbued their technology with lessons learned from that experience?