What is Optical Character Recognition (OCR)?

The presence of Know Your Customer (KYC) and anti-money laundering (AML) requirements has forced companies in the banking and finance service industries to dedicate significant resources to due diligence. Under the fear of severe penalties, banks must examine the risk characteristics of prospective clients and get sufficient verification. This is where Optical Character Recognition (OCR) technology comes in to help.

What is Optical Character Recognition (OCR)?

OCR is the process of converting an image of a text into a machine-readable text format. When you scan a form or a receipt, for example, your computer stores the scan as an image file. You cannot modify, search, or count the words in the image file using a text editor. You may, however, utilize OCR to transform the image into a text document, with the contents saved as text data.

How Does OCR Work?

OCR enables organizations to scan and recognize identity documents, especially when AI algorithms are used. It can, for example, detect complicated ID papers despite changes in format and structure.

The OCR software works in the following steps:

Image collection

A scanner scans documents and transforms them into binary data. The scanned image is analyzed by OCR software, which recognizes the light portions as the background and the dark areas as text.

Preprocessing

To prepare the picture for reading, the OCR program first cleans it and eliminates mistakes. Here are some of its cleaning methods:

• Deskewing or tilting the scanned paper slightly to correct alignment difficulties that may have arisen during the scan.
• Despeckling or eradicating digital picture spots, as well as smoothing the borders of text images
• Cleaning up the image's boxes and lines.
• Script detection for multi-language OCR technology

Recognition of text

Pattern matching and feature extraction are the two primary types of OCR algorithms or software processes that an OCR program utilizes for text recognition.

• Pattern Matching

Pattern matching works by comparing a character picture, known as a glyph, to another similarly stored glyph. Pattern recognition is only possible if the stored glyph has the same font and scale as the input glyph. This approach works effectively with scanned images of papers typed in a known font.

• Feature extraction

Feature extraction decomposes or breaks down glyphs into characteristics like lines, closed loops, line direction, and line junctions. It then employs these characteristics to locate the best match or nearest neighbor among its many stored glyphs.

Postprocessing

The technology turns the extracted text data into a digital file after analysis. Some OCR systems are capable of producing annotated PDF files that include both the before and after versions of the scanned material.

Why is OCR Important?

Business procedures include the use of paper forms, invoices, scanned legal documents, and printed contracts. These vast amounts of documentation require a significant amount of time and space to keep and handle. While paperless document management is the way to go, scanning a document into an image poses challenges. The procedure requires manual assistance and might be time-consuming and inefficient.

Furthermore, digitizing this document material generates picture files that include the text contained inside them. Image text cannot be handled by word processing software in the same way that text documents can. The problem is solved by OCR technology, which converts text pictures into text data that can be processed by other business software. The data may then be used for analytics, simplifying operations, automating procedures, and boosting productivity.

Advantages of Using OCR for KYC Verification

The fundamental advantage of optical character recognition technology is that it simplifies data entry by allowing for simple text searches, modification, and storage. OCR enables individuals and businesses to keep data on their PCs, laptops, and other devices, guaranteeing that all paperwork is always available.

OCR enables organizations to scan and recognize identification papers, especially when AI algorithms are used. It can, for example, detect complicated ID papers despite changes in format and structure. Utilizing OCR to extract data from ID documents reduces human error and other safety hazards, helping to ensure proper AML/KYC compliance.

The following are some of the advantages of using OCR technology:

• Speed: In comparison to the time-consuming and exhausting manual techniques of document verification that were previously utilized by businesses, OCR-based document verification is far faster and less demanding for enterprises. Many clients are said to quit organizations that require them to go through lengthy verification processes. OCR technology, on the other hand, reduces these risks for organizations by automating the data extraction process.
• Reduce expenses: Businesses may manage their operations with fewer employees as OCR technology decreases the need for manual effort. With fewer employees working on document verification for consumers, the organization may considerably reduce expenditures. The staff may also be employed for other critical duties.
• Storage: Businesses confront more than just the problem of collecting and processing customer information. They must also store and secure their clients' personal information.OCR also improves data management by eliminating the need for paper documents. The data is saved digitally and may be preserved safely for as long as the company wishes.
• Searchability: OCR gives the organization entire control over its information by transforming extracted data into searchable forms such as.doc ,.rtf ,.txt, or pdf.
• Automate content processing and document routing
• Secure and centralize data (no fires, break-ins, or documents lost in the back vaults)
• Improve service by ensuring personnel has the most up-to-date and correct information.

OCR Limitations in KYC

Although OCR is a low-cost addition to the KYC process, it has some limitations:

• Data privacy. Some OCR services employ cloud-based storage systems, which may be in violation of the General Data Protection Regulation (GDPR) and other data privacy laws.
• Capturing conditions. Camera angles, distortions, and illumination may all have an impact on the quality of OCR output.

Businesses should consider the compliance of these instruments when selecting an OCR service provider.

Choosing the Best OCR Service for KYC

Businesses may consider the requirements listed below for proper OCR when selecting the best OCR solution for KYC:

1. Integration of a mobile/web camera. Different types of SDK for ID scanning can minimize drop-offs and enhance conversion rates during client onboarding.
2. Technology that is ideal for every shooting or scanning situation. In natural shooting settings with bad illumination, AI-based OCR can function well.
3. The number of alphabets supported. OCR should be taught to recognize alphabets such as Cyrillic, Latin, Greek, Georgian, Armenian, Japanese, Korean, and Chinese.
4. GDPR and other data privacy legislation compliance OCR should enable safe data storage in accordance with GDPR, CPRA, CCPA, and other data protection requirements.

Businesses should integrate OCR technology with their AML and data protection compliance programs to get the full benefits of OCR technology.