خرید و دانلود نسخه کامل کتاب AI for Finance: A Practical Guide to Building, Governing, and Deploying AI in Financial Institutions (AI in Finance Series)

Finance is where AI delivers its greatest upside — and its most unforgiving failures.In finance, mistakes are not academic. Models move money, allocate credit, trigger trades, and shape customer outcomes. Poor decisions don’t just reduce accuracy — they create regulatory exposure, reputational damage, and systemic risk. Yet many AI initiatives still die as fragile pilots, trapped between innovation teams and risk committees.AI for Finance is written for finance leaders, risk professionals, and technical practitioners who must deploy AI in environments where accountability is non-negotiable. It provides a clear, regulator-ready path from experimentation to durable, governed capability.This is not a quant textbook or a vendor-driven overview. It is an execution-focused playbook for building, validating, governing, and operating AI across the financial value chain — from credit and fraud to trading, FP&A, treasury, and insurance.INCLUDED IN THIS BOOKThe 3-Year Strategic Roadmap: A phased execution plan from cleanup and governance to agentic autonomy, ensuring your AI capability survives beyond the pilot phase.15+ Proprietary Frameworks: High-stakes decision models including the P.C.A. Loop, the S.O.L.D. vendor framework, and the H.E.A.T. fraud detection method.25+ Financial-Grade GenAI Prompts: Ready-to-use prompts for controllers, risk managers, and analysts to audit variances, draft adverse action letters, and stress-test investment theses.The Regulatory-Ready Governance Toolkit: Templates aligned with SR 11-7 and the EU AI Act, including Model Definition Documents, validation reports, and traceability matrices.Critical Flight-Safety Checklists: Go/no-go deployment protocols, pre-mortem workshops, kill-switch drills, and rigorous vendor due diligence.The ROI & Performance Catalog: Financial metrics that matter, from Precision at Top-K for fraud to Sharpe Ratio for trading and incremental lift for marketing.Real-World Case Studies: Deep-dive autopsies of success and failure, including the Zestimate collapse, the Knight Capital flash crash, and modern implementations across credit, AML, and insurance.WHAT’S INSIDE THIS BOOKPart I: The New Financial IntelligenceA practical mental model for AI in finance, the realities of non-stationary data, and the complementary roles of supervised learning, unsupervised discovery, and generative synthesis.Part II: Building & Governing the MachineFrom build-versus-buy decisions to industrial-grade MLOps, kill-switches, and modernized model risk management that satisfies regulators without stalling innovation.Part III: Execution Across the Value ChainHands-on applications across credit underwriting, fraud and financial crime, trading and investment management, FP&A, treasury, and balance sheet optimization.Part IV: Safety, Security & FailureHow AI systems fail in finance, how attackers exploit them, and how to red-team, secure, and recover before small errors become market events.Part V: The Future & The RoadmapResponsible AI trade-offs, the rise of agentic systems, and a pragmatic three-year roadmap to transform finance teams from data gatherers into strategic architects.Part VI: The Practitioner’s ToolkitFill-in-the-blank governance templates, aggressive vendor checklists, and a prompt library tailored to real financial workflows.If AI is already influencing your financial decisions, this book shows you how to stay in control — and ahead.Written for CFOs, controllers, risk managers, quants, finance technologists, and regulators who demand rigor, accountability, and results — not black boxes.