VAULTX
Akash Rajendran
Department of CSE
College of Engineering Kidangoor
Kottayam, Kerala, India
akashrajendran835@gmail.com
Jebin Joseph
Department of CSE
College of Engineering Kidangoor
Kottayam, Kerala, India
jebinjoseph8421@gmail.com
Christo V Rajesh
Department of CSE
College of Engineering Kidangoor
Kottayam, Kerala, India
christorajesh0@gmail.com
Sam Sebastian
Department of CSE
College of Engineering Kidangoor
Kottayam, Kerala, India
samsebastian916@gmail.com
Harikrishnan P T
Department of CSE
College of Engineering Kidangoor
Kottayam, Kerala, India
harikrishnan135790@gmail.com
Tinimol Andrews
Department of CSE
College of Engineering Kidangoor
Kottayam, Kerala, India
tinimolandrews@gmail.com
Abstract— The rapid digitalization of financial and administrative processes has led to a significant increase in the volume of documents such as bills, warranties, insurance policies, receipts, and invoices. Recent research has explored the application of Artificial Intelligence (AI), Machine Learning (ML), Optical Character Recognition (OCR), and Natural Language Processing (NLP) to automate document processing, information extraction, and decision support in financial and industrial do mains. Existing studies investigate predictive modeling for warranty analysis, AI-assisted warranty claim handling, intelligent document management systems, deep learning–based financial document classification, and OCR-based receipt digitization. Other works focus on secure cloud storage mechanisms, encryption techniques, privacy and ethical challenges associated with AI powered financial systems. This literature review presents a comprehensive analysis of ten representative studies, highlighting their methodologies, key contributions, and limitations. The review reveals that while significant progress has been made in individual areas such as document extraction, analytics, security, and privacy, existing solutions lack a unified, user-centric approach that integrates automated multi-source document ingestion, intelligent extraction, predictive reminders, and secure storage within a single framework.
