
OCR Vs. ICR: The Key Differences that Businesses Need to Know

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Financial institutions need to have reliable and efficient data management. With such a system, these businesses can easily organise all customer-relevant information, thus, being able to provide better services. Efficient data management also impacts other sectors and practices, such as ameliorating the more comprehensive identity verification journey.
Many companies are using technologies that provide scanned images of documents. These images lack all the metadata, such as names, dates, and invoice amounts, within the document. These details are then added manually, which consumes a lot of precious time, thus, affecting productivity and customer service. But with the emergence of OCR and ICR technologies, financial firms are now becoming more efficient in servicing customers. However, before a firm invests in implementing these technologies, it’s pertinent to understand how they work and how best they can implement them in their existing data management ecosystem.Â
Optical Character Recognition (OCR) technology was introduced in 1931 when it was used to create a text-to-telegraph device. OCR converts documents into electronic files. The optical character recognition technology works by scanning text images and then translating them into encoded text.Â
Intelligent Character Recognition (ICR) emerged in the 1990s as a more intelligent version of OCR. ICR is a specific type of OCR that translates different fonts, including handwritten texts. It is used for retrieving type documents that can be categorised and searched. Meanwhile, ICR is used for recognising handwritten texts that are more complicated for OCR to manage. Apart from this, ICR is a self-learning technology; it can recognise new patterns of handwriting and can also improve data capturing from scanned documents.Â
Although OCR and ICR technologies have been around for decades, firms still rely on humans for data entry which can result in data errors. According to research from Gartner, companies spend billions of dollars on rekeying data because of a lack of benchmarks that can measure accuracy-effort trade-offs.Â
Thus, businesses aren’t aware of what benefits they can enjoy by implementing ICR and OCR technologies. Here are a few benefits of both these technologies:
When deciding to implement OCR and ICR, it is critical to keep in mind the needs of your business. Businesses must precisely know why they want to use these technologies and what benefits they will get out of them.Â
You can only see the benefits of OCR and ICR materialise when you train them using high-quality data. The reason for using a high-quality data set is that handwritten texts are complicated. Therefore, to get the best possible results, development teams must train OCR and ICR models using deep learning algorithms and computer-vision engines alongside a high-quality data set.
OCR and ICR capabilities can be truly enhanced by incorporating an AI solution. As AI models can process and analyse vast amounts of data, this can help both models to work efficiently.
Images with unreadable texts can distort the output of both OCR and ICR. Therefore, ensure that you use high-quality legible text. Moreover, you can employ image normalisation techniques, such as applying filters, reducing blur, and properly aligning the document.
Shufti Pro’s OCR solution leverages AI, machine learning algorithms, and computer vision to extract data even from the most poor quality images and illegible texts. Business owners can streamline their operations and increase productivity with our OCR solution.
Here’s why our OCR scanner is for you:
Still confused about whether to invest in ICR or OCR technology?