Paper Title
Generative AI for Financial Services

Abstract
Generative Artificial Intelligence (Gen AI) is rapidly transforming the financial services sector, evolving from limited pilot experiments into enterprise-scale deployments across payments, risk management, compliance, and customer engagement. By 2026, financial institutions have increasingly embedded large language models, multimodal systems, and AI agents to accelerate decision-making, automate operational workflows, and deliver personalized customer experiences. This shift is driven by significant advances in long-context models, layout-aware document processing, and retrieval-augmented generation capabilities that now enable banks to analyze entire loan portfolios, regulatory filings, and client histories with unprecedented accuracy and scale. As adoption intensifies, industry leaders often referred to as Frontier Firms are reporting returns on AI investments up to three times higher than slower adopters, reflecting the competitive advantage of re-architecting core processes to be human-led and AI-operated. Meanwhile, up to 91% of financial services companies are actively deploying AI for fraud detection, underwriting, portfolio optimization, and enhanced customer engagement, underscoring widespread industry momentum. This article explores the state of Gen AI in financial services, its key applications, enabling technologies, and the strategic pathways institutions must adopt to scale responsibly while meeting rigorous regulatory expectations. The landscape marks a definitive turning point ushering in a new era of “unconstrained banking,” where generative AI dissolves long-standing limitations in capacity, efficiency, and innovation. Keywords - Generative AI (Gen AI), Financial Services, Large Language Models (LLMs), Multimodal AI, Long-Context Models, Layout-Aware Document Processing, Retrieval-Augmented Generation (RAG), Knowledge Banks (KBs), AI Agents (Agentic AI), Fraud Detection, AML/KYC Automation, Risk Management & Modeling, Regulatory Compliance & Reporting, Auditability & Traceability, Model Risk & Hallucinations, Third-Party/Vendor Risk, Responsible AI Governance, Unconstrained Banking, Frontier Firms, Enterprise-Scale AI Deployment