Last Updated on September 6, 2023 by ScreenPush
Online identity verification is as important for digital businesses as security infrastructure is for physical businesses. Technology is evolving with every passing moment and so are criminal strategies along with it. Whether they are social media conglomerates, e-commerce businesses, or financial institutions, no one is safe from online economic crimes. Thus, these organizations risk being non-compliant with KYC and AML rules if any criminal is onboarded as a legitimate customer. Moreover, online scams not only target businesses but also the identities of their customers. Therefore, online identity theft and account takeovers also jeopardize the customer base of these businesses.
OCR technology is utilized by identity verification systems for the extraction of data like name, dob, address, gender, etc. from the provided documents.
What is an OCR Software?
Optical Character Recognition OCR Technology is used to recognize and extract textual data from pictures or scanned documents. Whether the text is in handwritten, printed, or typed form, this technology will extract that information. Moreover, it turns the recognized information into machine-readable text.
In the online identity verification process, optical character recognition services are used to extract data from the documents provided by the customer. Among other things, the extracted data may include name, DOB, address, government-issued ID card number, etc.
How Does OCR Technology Work for ID Verification?
OCR is a major tool for online identity verification systems. Trained in ML and AI models, it provides maximum accuracy of data extraction results. The procedure of data recognition and extraction performed by OCR is as follows:
- First and foremost, the user either uploads a picture of a government-issued identity card or shows it to the webcam.
- The ID verification system takes a screenshot of the shown ID document.
- Then, OCR software using AI and ML technology extracts the textual data from the scanned document or the image.
- The IDV system shows the extracted data to the user through an information form.
- In any case of missing or wrongly extracted information, the user can edit the information form before confirming its submission. The editing access is given for the reason that the user has the right to their correct identity.
Few Shortcomings of OCR Technology
OCR is prone to certain limitations which are outlined below:
- When the users take pictures, they are not always aligned in a way for OCR to do its magic. So, OCR must have an image rectification feature to correctly recognize the information incorporated in the image.
- OCR usually converts the images with colored backgrounds to black and white photos. In colored images, text may appear blurry to the OCR software thus it can produce incorrect results sometimes.
- Although artificial intelligence and machine learning technology are used to ensure the accuracy of data extraction, if the picture is not clear or has a certain glare to it, then OCR may become prone to some mistakes.
- Nowadays, most mobile phone cameras can take high-quality pictures. However, in the case of webcams, the resolution of pictures taken is significantly lower and creates a problem for OCR. It becomes difficult for OCR to correctly structure and extract the data. Furthermore, recognizing the correct identity subtype from a mammoth of ID subtypes also becomes an uphill task.
So, How does OCR Justify its Place in IDV Systems?
The accuracy of results for most identity verification solutions out there is above 90%. If OCR is not used in ID verification, there are not many proper alternatives to replace that. This technology uses machine learning for data recognition and extraction. So, it is safe to say that AI and ML will only enhance in the future, providing even more accuracy of results. Currently, it would not be wrong to say that OCR services are holding their own pretty well in the IDV space.
Moreover, the pros of using optical character recognition for online ID verification are described below:
- It saves time by scanning loads of data in no time, resulting in an increase in customers onboarded.
- When customers bypass the hassle of manual verification, it automatically raises their satisfaction level. So, enhanced user experience results in customer retention.
- Businesses don’t need a translator to verify multi-language documents. Optical character recognition (OCR) is fully capable of doing it and in return saves your time and cost.