AI-enhanced OCR for financial document processing: Advancing recognition accuracy in modern enterprise finance

This article explores the transformative impact of Artificial Intelligence on Optical Character Recognition technologies within financial automation frameworks. Traditional OCR systems have long encountered limitations when processing diverse document formats, handwritten content, and low-quality scans, creating significant barriers to automation efficiency. The integration of deep learning algorithms and natural language processing capabilities has revolutionized these systems, enabling dynamic learning, contextual understanding, and significantly improved accuracy in extracting critical financial data. The resulting systems demonstrate remarkable adaptability across varying document types, substantially reducing manual intervention requirements while enhancing operational efficiency, cost management, and regulatory compliance. Although human oversight remains essential for complex decision-making scenarios, the synergy between AI and OCR technologies represents a pivotal advancement in financial document processing, offering organizations substantial competitive advantages through improved data integrity and streamlined workflows.

Authors

Publication Details

Journal
World Journal of Advanced Research and Reviews
Published
2025-05-17
DOI
https://doi.org/10.30574/wjarr.2025.26.2.1653
Citations
5
Primary Topic
Currency Recognition and Detection
Type
article
Field-Weighted Citation Impact
6.38
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

AI-enhanced OCR for financial document processing: Advancing recognition accuracy in modern enterprise finance

Ranadheer Reddy Charabuddi
5 citations
World Journal of Advanced Research and Reviews
Currency Recognition and Detection
6.38
article

AI-enhanced OCR for financial document processing: Advancing recognition accuracy in modern enterprise finance

Ranadheer Reddy Charabuddi
article en
5 citations

Abstract

This article explores the transformative impact of Artificial Intelligence on Optical Character Recognition technologies within financial automation frameworks. Traditional OCR systems have long encountered limitations when processing diverse document formats, handwritten content, and low-quality scans, creating significant barriers to automation efficiency. The integration of deep learning algorithms and natural language processing capabilities has revolutionized these systems, enabling dynamic learning, contextual understanding, and significantly improved accuracy in extracting critical financial data. The resulting systems demonstrate remarkable adaptability across varying document types, substantially reducing manual intervention requirements while enhancing operational efficiency, cost management, and regulatory compliance. Although human oversight remains essential for complex decision-making scenarios, the synergy between AI and OCR technologies represents a pivotal advancement in financial document processing, offering organizations substantial competitive advantages through improved data integrity and streamlined workflows.

World Journal of Advanced Research and ReviewsVol. 26(2)
Openalex Percentile: Top 3%
Currency Recognition and Detection
6.38
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

AI-enhanced OCR for financial document processing: Advancing recognition accuracy in modern enterprise finance — Ranadheer Reddy Charabuddi · World Journal of Advanced Research and Reviews (2025) | TGRS Research Map | TGRS