COMPREHENSIVE SURVEY ON OPTICAL CHARACTER RECOGNITION (OCR)

Abstract

The verification and documentation of real estate transactions in the finance sector is a time-consuming and sus-ceptible to errors, traditionally involving the manual extraction of data from property documents to generate a report. The research within this paper looks into how OCR (Optical Char-acter Recognition) is applied to automate extraction, validation, and processing of key data such as property addresses for scanned documents complying with legal requirements. Data verification and intelligent error detection mechanisms through which artificial intelligence and machine learning techniques are integrated into the system ensure a certain level of accuracy and reliability in document generation. The OCR-based proposed solution reduces processing times significantly, minimizes human error, and enhances overall pro-ductivity in the legal verification workflow. This approach will optimize the creation of compliantly legal documents while automating data extraction and validation for the efficient and accurate processing of real estate transactions in the finance sector.