Banks are one of the most notable financial institutions. They necessitate the processing of customers' information and financial records which have to be digitized for better storage and retrieval. OCR- Optical Character Recognition, makes it possible for data extracted from documents and images to be digitized for further use in the future.
This piece would provide a synopsis of automating document processing in banks.
Some bank documents that require automated data extraction
- Bank statements : This is the most popular use of OCR in banks. To establish the history of customers through the monetary worth of income that flows into the account within a particular period of time, a bank statement has to be prepared immediately as demanded by the customer or the bank. OCR helps to digitize transaction history and transfer to a document almost instantaneously in the form of a document for a bank statement.
- Customer IDs and other information : Banks require OCR technology to automatically extract data from customers' ID for compliance purposes.
- Credit and Debit cards : ATMs could employ OCR technology to collect data from credit and debit cards for verification by a security system. Some banks in China also attach facial recognition alongside for security verification.
- Paper applications : Application for loans, mortgage, credit cards and others, require so many documents. Employing OCR technology in this process will make it possible for multiple bank staff to review the documents and easier for the documents to be reviewed.
- Scanning cheques: OCR technology makes it faster for cheques to be quickly scanned for payment to take place.
- Security : Banks could employ the use of OCR technology with other automated operations like NLP- Natural Language Processing to provide stronger transaction security for customers. By integrating the technologies into risk assessment and fraud detection through data extracted from paper documents, this can be made possible.
Why should banks automate their data extraction processes?
- Editable information : OCR technology makes data extracted reusable by providing it an editable format.
- Saves time: Automated data extraction, saves a lot of time rather than manually picking the documents to extract data from.
- Elimination of human errors : Processing so many paper documents could leave the end result with biased data, errors, and incomplete records. Automated data extraction helps to combat this.
- Fast payment: Automated data extraction creates a room for faster operations in payments, validation of documents, compliance and other processes.
- Centralized database: Data extracted with OCR technology can be moved to a database where the right data consumers can access it.
- Cost reduction : APIs for data extraction saves cost in the long run by providing efficiency that manual methods would have induced cost for.
- Better document format: Automated data extraction leaves documents in digitized format for storage, editing and other purposes.