In today’s data-driven world, financial institutions regularly deal with a hefty amount of customer information that requires automated solutions. Companies manually enter this information in their databases, which can be very time-consuming. This leads them to face the consequences of inconvenience and financial losses. Businesses need an advanced method of document verification that digitizes the data capturing and extraction processes. OCR financial services are an efficient way of digitizing the data extraction process and streamlining business operations.
What is Optical Character Recognition (OCR)?
Optical Character Recognition (OCR) is a technology that converts a text-based image into a machine-readable digital format that can be edited and formatted. It is crucial in verifying official documents because it uses machine learning and artificial intelligence technologies to recognize complex data patterns of financial records. OCR technology in the banking sector is convenient as it quickly converts physical documents into electronic format by allowing them to modify the data in real-time. It will enable businesses to save these financial files on their databases, ensuring they can access all documents.
How Does OCR Technology Improve Digital Banking?
Optical character recognition in banking is crucial as it digitizes text-based documents, which makes managing and retrieving critical information easier. It can improve the account onboarding, document verification, and loan application process while reducing the human errors associated with manual data entry processes. Financial industries can digitally extract information from financial statements, such as invoices, contracts, and receipts. It automatically scans the document and creates its digital template quickly. OCR services in financial institutions are operated in the following way:
- Image Collection
The first step in the OCR verification process is to capture the images of the customer’s legitimate documents. These documents are converted into digital data after getting scanned by automated machines. Using the OCR technology, businesses can easily analyze scanned documents and verify the customer’s authenticity.
- Pre-Processing of Documents
Before the documents are processed, they are transformed into digital images. In this step, the OCR uses technology to make the scanned document as accurate as possible and remove any friction and delays. The image is analyzed in a black and white representation. Optical character recognition uses technology that identifies the white areas of the document as the background and the black areas as the text.
- Text Recognition
OCR recognizes the text using automated techniques of matching patterns and feature extraction. The pattern recognition technique compares the individual words with a similar recorded word in the database by matching their typeface and dimensions. Whereas, the feature extraction identifies the words in terms of enclosed loops, line intersections, and line orientation. It uses these features to find the closest word available in the database.
- Post-Processing
After recognizing the text using pattern recognition and feature extraction techniques, the OCR technology converts the text data into a digital file. All the errors made during the data extraction process are removed to increase the data accuracy rate. It enables machine learning and AI technology to cross-match and verify the data with available word templates.
OCR Use Cases Across Industries
Businesses optimize the OCR technology to automate their operational tasks. OCR services are used to streamline the operations of the following sectors:
- Banking: The banking sector incorporates OCR technology to authenticate paperwork used for financial transactions, loan documents, and check deposits. Verifying these financial documents can combat the risk of document forgery and improve transaction security.
- Healthcare: The healthcare industry can use the OCR services to analyze patient medical records and insurance payments. It helps them reduce manual data entry work and streamline their daily workflow.
- Retail: The retail sector can use it to retrieve data from invoices, payment bills, purchase orders, and packing lists.
Why Should Businesses Adopt OCR Services?
- Use of Automated Services
Businesses should use OCR services because they use AI and machine learning (ML) technologies to automate data entry processes. This protects businesses from consequences of errors associated with manual entry. Doing this ensures the document accuracy and enhances its scalability and efficiency. OCR protects the information from fraud, document alteration and terrorist financing.
- Provides Excessive Storage
OCR secures the document information in cloud storage because it can retain it for a long time. It can store a hefty amount of data in its database, protecting the information from misplacement, theft, and forgery.
- Enhance Work Productivity
Optical character recognition allows businesses to extract data digitally without hiring a workforce for this task. The employees can use this time to focus on urgent tasks that are much more tedious, hence improving their work productivity.
Final Words
OCR financial services are crucial for financial institutions as they make data extraction easier. They detect data with great accuracy due to the use of artificial intelligence and machine learning algorithms. It improves employee’s work productivity, which enhances the overall company reputation and provides operational efficiency. Several industries, such as banking, healthcare, and retail sectors, are using OCR services to streamline their operations.