Overview

The financial industry is entering a defining transformation, driven by the convergence of artificial intelligence, generative AI, and autonomous agentic systems. What began as incremental automation rules, spreadsheets, and dashboards has rapidly evolved into learning systems capable of reasoning, summarizing, simulating, and even taking multi-step actions. This book, AI, Generative AI, and Agentic AI for Finance: A Practical, Hands-on Approach Using Python, is written to guide practitioners through this new era with clarity and pragmatism. It bridges foundational financial analytics with modern AI techniques, showing how market data, risk metrics, customer behavior, and portfolio views can be understood, modeled, and acted upon through a unified workflow. Designed for analysts, data scientists, risk managers, developers, and finance professionals, this book intentionally blends concepts, intuition, and implementation. Each chapter builds toward practical capabilities: descriptive and risk analytics, credit scoring, fraud detection, portfolio reasoning, generative reporting, and ultimately agentic systems that can plan and execute financial tasks. With Python as the working medium and synthetic data to ensure safe experimentation, readers progress from fundamentals to hands-on mini-projects and capstone agents. The goal is simple yet ambitious: to equip you with the tools, mental models, and practical steps to build the next generation of AI-enhanced financial systems responsibly, effectively, and creatively.

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