Article
A SECURE OCR-BASED TEXT ANALYTICS FRAMEWORK FOR AUTOMATED UNDERSTANDING OF BANKING AND FINANCIAL DOCUMENTS
A Secure OCR-Based Text Analytics Framework for Automated Understanding of Banking and Financial Documents presents an intelligent system designed to digitize, analyze, and securely process complex financial records. The framework integrates advanced Optical Character Recognition (OCR) with natural language processing and machine learning techniques to extract, classify, and interpret key information from banking documents such as invoices, statements, and loan forms. A secure architecture is incorporated to ensure data privacy, integrity, and compliance with regulatory standards through encryption and controlled access mechanisms. The system improves document processing speed, reduces manual errors, and enhances decision-making by providing structured, searchable insights from unstructured financial text. Experimental evaluation demonstrates high accuracy in text extraction and semantic understanding across diverse document formats. This framework supports scalable deployment in financial institutions, enabling efficient automation and secure handling of sensitive information while optimizing operational workflows and customer service.
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