Leveraging Generative AI and OCR for Automating Loan Document Processing in Fintech

The digitization of loan document processing has become increasingly crucial in the financial technology (Fintech) sector. Traditional approaches relying on manual or rule-based systems struggle with low-quality scans, diverse document formats, and fraud detection. This paper explores the integration of Generative Artificial Intelligence (GenAI) and Optical Character Recognition (OCR) technologies for automating loan document workflows. Key challenges addressed include handling noisy or low-quality input, identifying fraudulent documents, and leveraging advanced technologies such as deep learning, transformer-based models, and anomaly detection techniques. The proposed framework aims to streamline data extraction, improve accuracy, and ensure robust fraud detection while maintaining scalability and efficiency.

Authors

Publication Details

Journal
International Journal of Global Innovations and Solutions (IJGIS)
Published
2024-12-25
DOI
https://doi.org/10.21428/e90189c8.1436e7da
Primary Topic
FinTech, Crowdfunding, Digital Finance
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Leveraging Generative AI and OCR for Automating Loan Document Processing in Fintech

Jitender Jain, Medha Gupta
International Journal of Global Innovations and Solutions (IJGIS)
FinTech, Crowdfunding, Digital Finance
article

Leveraging Generative AI and OCR for Automating Loan Document Processing in Fintech

Jitender Jain, Medha Gupta
article en

Abstract

The digitization of loan document processing has become increasingly crucial in the financial technology (Fintech) sector. Traditional approaches relying on manual or rule-based systems struggle with low-quality scans, diverse document formats, and fraud detection. This paper explores the integration of Generative Artificial Intelligence (GenAI) and Optical Character Recognition (OCR) technologies for automating loan document workflows. Key challenges addressed include handling noisy or low-quality input, identifying fraudulent documents, and leveraging advanced technologies such as deep learning, transformer-based models, and anomaly detection techniques. The proposed framework aims to streamline data extraction, improve accuracy, and ensure robust fraud detection while maintaining scalability and efficiency.

International Journal of Global Innovations and Solutions (IJGIS)
Openalex Percentile: Top 62%
FinTech, Crowdfunding, Digital Finance
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.