Optical Character Recognition (OCR) and Banking
Optical Character Recognition (OCR)
Literally, OCR stands for Optical Character Recognition. It is a widespread technology to recognize text inside images, such as scanned documents and photos. OCR technology is used to convert virtually any kind of image containing written text (typed, handwritten, or printed) into machine-readable text data.
As financial entities that possess PII and sensitive data, banks and financial firms are subject to compliance regulations and evaluation by auditors. Consequently, firms need to efficiently and securely preserve financial records and archive documents. Manually sifting through thousands of paper documents to retrieve specific information is time-consuming and costly, and so is the storage of paper documents. According to research done by PricewaterhouseCoopers, it costs an organization $20 on average to file a single document, roughly $120 to manually search for a misfiled document, and $220 to recreate a lost document.
The time and labor spent trying to find certain content throughout a plethora of documents is time that could otherwise be allocated toward a firm’s core workflow. OCR technology leverages image processing to reliably convert scanned documents from images into searchable PDF files, allowing for specific information retrieval with keyword search. Accordingly, banks and financial organizations are able to save on physical storage units costs and modernize by standardizing paper to digital document conversion.
This use case can be handled with different engines offered by different providers on the market. To help companies discover and test these different engines, we have developed Eden AI, which provides a single, simple access to all these engines: