EVALUATING THE EFFECTIVENESS OF END TO END INTELLIGENT DOCUMENT UNDERSTANDING SYSTEMS IN FINANCIAL SERVICES
Keywords:
Intelligent Document Understanding, OCR, Natural Language Processing, Financial Services, Information ExtractionSynopsis
Purpose: The paper assesses how end to end intelligent document understanding (IDU) systems can transform document centric workflows in financial services by automating extraction, understanding, and processing of unstructured documents. Design/methodology/approach: We propose an integrated framework combining OCR, NLP, and layout analysis, and empirically evaluate key performance metrics for document extraction. Findings: Intelligent systems dramatically improve extraction accuracy, reduce processing time, and enhance compliance. Practical implications: Financial institutions can achieve significant operational savings and reduce human errors through adoption of end to end IDU workflows. Originality/value: This work synthesizes insights from classic information extraction research and modern financial automation trends to clarify documented benefits and challenges.
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