AI Driven Investment Banking (AI-Powered Business Function Series)

Who this is for: Investment banking professionals who already know the workflows and want practical ways to layer AI into their day-to-day without learning to code. You are looking for faster sourcing, sharper diligence, better valuations, cleaner execution, and tighter risk control. You want real tools and repeatable playbooks, not hype. You have more data than time, fragmented sources, inconsistent models, and manual processes that slow deals and expose risk. You need clear guidance on where AI adds measurable value, how to pilot tools safely, and how to move from proofs of concept to production. How this book helps: It focuses only on how AI tools, techniques, and workflows enhance what you already do, with conversational, practical explanations and visuals to make adoption straightforward. What you will get, at a glance Deal intelligence that flags targets, comparables, and red flags in minutes using NLP and knowledge graphs. Due diligence accelerators that extract clauses, obligations, and risks from long documents with review-ready summaries. Valuation upgrades with feature-engineered, interpretable models that complement DCFs and comps, not replace them. Execution and trading optimizations that learn from intraday microstructure to reduce slippage and improve fill quality. Credit and portfolio risk dashboards that surface early warnings and scenario outcomes for quick action. Compliance and AML intelligence that triages alerts and improves investigator productivity with auditable reasoning. Deployment patterns, team roles, and ROI methods that make pilots stick inside a regulated IB environment. Across the chapters, you will see concrete workflows built around widely used platforms such as Bloomberg Terminal AI, Kensho, AlphaSense, FactSet AI, Refinitiv Eikon AI, Alteryx, Tableau, Power BI, and low-code options. Every method is explained in plain language and mapped to where it fits in the deal lifecycle. You will also find short, realistic use cases that show time saved, risk reduced, and decision quality improved, along with clear notes on regulatory and model limitations. The writing is direct and practical, avoiding filler, and the visuals are easy to follow.