In an era where algorithms decide who gets a mortgage and how markets move, the intersection of finance and artificial intelligence is the most critical frontier in the global economy. Algorithms and Accountability tackles the urgent question of how we ensure these powerful digital tools remain fair, safe, and transparent. Whether you are a banking professional, a fintech developer, or a consumer concerned about digital bias, this book provides an essential roadmap for navigating the high-stakes world of automated money. You will go beyond the headlines to uncover the actual machinery behind modern banking. Discover how fairness is mathematically tested in credit scoring, how privacy laws constrain the data appetite of machine learning, and why even the smartest models can hallucinate or discriminate. From the control rooms where governance frameworks are built to the front lines of fraud detection, this guide reveals exactly how institutions are striving to keep humans in the loop of algorithmic decision-making. Written with the accessible storytelling flair of The Everyman's Finance Series, this book strips away complex jargon to deliver practical, actionable insights. It favors relatable analogies over dense equations, making sophisticated concepts like model risk management and generative AI ethics understandable for everyone. This is your definitive guide to understanding the invisible code that controls the world's wealth.