AI-driven intelligent document processing for banking and finance

摘要

The banking and finance industry is buried in paperwork—loan applications, compliance reports, risk assessments, and fraud investigations. Manual processing and outdated automation slow operations, increase costs and expose institutions to compliance risks (Vaultedge, 2023). AI-driven Intelligent Document Processing (IDP) is changing this by automating document workflows, accelerating approvals, and enhancing fraud detection. AI-powered IDP integrates machine learning, NLP, and RPA to reduce verification times, reduce errors, and strengthen compliance monitoring. Banks using AI-driven document automation process loan approvals 70% faster, improve fraud detection rates by 50%, and lower compliance costs by 40% (Rajput et al., 2025). This paper explores real-world applications of AI in banking document processing, highlighting efficiency gains, challenges, and future potential. As financial institutions move toward self-learning AI models, IDP is set to become a critical driver of speed, accuracy, and security in banking operations. Keywords: AI-Driven Document Processing, Banking Automation, Fraud Detection, Regulatory Compliance, Machine Learning in Finance, Robotic Process Automation (RPA), Intelligent Workflow Optimization.