{"title":"Our Recommendations","description":"","products":[{"product_id":"climate-change-managing-the-financial-risk-and-funding-the-transition","title":"Climate Change: Managing the Financial Risk and Funding the Transition","description":"\u003cp\u003e\u003cmeta charset=\"utf-8\"\u003e\u003cem\u003eClimate Change: Managing the Financial Risk and Funding the Transition\u003c\/em\u003e\u003cspan\u003e serves as a practical and accessible reference for an essential understanding of climate-related risks and opportunities in financial institutions. Editor Jing Zhang has gathered more than 30 experts from world-leading financial and consultant institutions in a four-part book that focuses on climate change as the most profound challenge our social, political and economic systems have ever faced.\u003c\/span\u003e\u003c\/p\u003e","brand":"Risk Books","offers":[{"title":"Default Title","offer_id":50099414204758,"sku":"9781782724407","price":85.0,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0904\/4433\/3398\/files\/new_cc-mtfraftt-2d-v2-411x616pixels_1.png?v=1753887333"},{"product_id":"machine-learning-origins-developments-and-implications","title":"Machine Learning: Origins, Developments and Implications","description":"\u003cstyle\u003e#html-body [data-pb-style=HB1PBAU]{justify-content:flex-start;display:flex;flex-direction:column;background-position:left top;background-size:cover;background-repeat:no-repeat;background-attachment:scroll}\u003c\/style\u003e\u003cdiv data-content-type=\"row\" data-appearance=\"contained\" data-element=\"main\"\u003e\u003cdiv data-enable-parallax=\"0\" data-parallax-speed=\"0.5\" data-background-images=\"{}\" data-background-type=\"image\" data-video-loop=\"true\" data-video-play-only-visible=\"true\" data-video-lazy-load=\"true\" data-video-fallback-src=\"\" data-element=\"inner\" data-pb-style=\"HB1PBAU\"\u003e\n\u003cdiv data-content-type=\"text\" data-appearance=\"default\" data-element=\"main\"\u003e\n\u003cp\u003eCelebrated Risk Books author Terry Benzschawel returns with his \u003cem\u003emagnum opus\u003c\/em\u003e, \u003cem\u003eMachine Learning: Origins, Developments and Implications\u003c\/em\u003e, a comprehensive exploration of the world of artificial intelligence and machine learning. This book investigates the historical roots, intricate mechanisms, and diverse applications of machine learning, offering readers a thorough understanding of its transformative impact not only on the world of finance but on the whole of society.\u003c\/p\u003e\r\n\u003cp\u003e \u003c\/p\u003e\r\n\u003cp\u003eKey Areas Explored:\u003c\/p\u003e\r\n\u003cp\u003e\u003cstrong\u003eFundamentals of Machine Learning:\u003c\/strong\u003e\u003c\/p\u003e\r\n\u003cp\u003eDelve into the core concepts of machine learning, including decision trees, neural networks, and deep learning architectures. Benzschawel provides clear explanations of theoretical concepts and complex algorithms, making them accessible to both technical and non-technical readers.\u003c\/p\u003e\r\n\u003cp\u003e \u003c\/p\u003e\r\n\u003cp\u003e\u003cstrong\u003eApplications Across Industries:\u003c\/strong\u003e\u003c\/p\u003e\r\n\u003cp\u003eExamine real-world applications of machine learning in various domains including healthcare, the military and marketing but with a particular focus on finance.\u003c\/p\u003e\r\n\u003cp\u003e \u003c\/p\u003e\r\n\u003cp\u003e\u003cstrong\u003eEthical Implications for Financial Institutions:\u003c\/strong\u003e\u003c\/p\u003e\r\n\u003cp\u003eBenzschawel discusses the ethical challenges arising from the integration of AI in decision-making processes and analyses the potential consequences of delegating decision authority to intelligent algorithms.\u003c\/p\u003e\r\n\u003cp\u003e \u003c\/p\u003e\r\n\u003cp\u003e\u003cstrong\u003eWorkforce Preparedness:\u003c\/strong\u003e\u003c\/p\u003e\r\n\u003cp\u003eHave you fostered a skilled workforce capable of harnessing AI's potential? Now is the time to begin preparing.\u003c\/p\u003e\r\n\u003cp\u003e \u003c\/p\u003e\r\n\u003cp\u003e\u003cstrong\u003ePolicy and Governance:\u003c\/strong\u003e\u003c\/p\u003e\r\n\u003cp\u003eThis book outlines strategies to ensure the responsible and transparent use of machine learning technologies.\u003c\/p\u003e\r\n\u003cp\u003e \u003c\/p\u003e\r\n\u003cp\u003e\u003cstrong\u003eInterpretability and Accountability:\u003c\/strong\u003e\u003c\/p\u003e\r\n\u003cp\u003eTransparency and interpretability in machine learning models is essential and Benzschawel discusses mechanisms to ensure accountability and mitigate biases in AI systems.\u003c\/p\u003e\n\u003c\/div\u003e\n\u003cdiv data-content-type=\"text\" data-appearance=\"default\" data-element=\"main\"\u003e\n\u003cp\u003eCelebrated Risk Books author Terry Benzschawel returns with his \u003cem\u003emagnum opus\u003c\/em\u003e, \u003cem\u003eMachine Learning: Origins, Developments and Implications\u003c\/em\u003e, a comprehensive exploration of the world of artificial intelligence and machine learning. This book investigates the historical roots, intricate mechanisms, and diverse applications of machine learning, offering readers a thorough understanding of its transformative impact not only on the world of finance but on the whole of society.\u003c\/p\u003e\r\n\u003cp\u003e \u003c\/p\u003e\r\n\u003cp\u003eKey Areas Explored:\u003c\/p\u003e\r\n\u003cp\u003e\u003cstrong\u003eFundamentals of Machine Learning:\u003c\/strong\u003e\u003c\/p\u003e\r\n\u003cp\u003eDelve into the core concepts of machine learning, including decision trees, neural networks, and deep learning architectures. Benzschawel provides clear explanations of theoretical concepts and complex algorithms, making them accessible to both technical and non-technical readers.\u003c\/p\u003e\r\n\u003cp\u003e \u003c\/p\u003e\r\n\u003cp\u003e\u003cstrong\u003eApplications Across Industries:\u003c\/strong\u003e\u003c\/p\u003e\r\n\u003cp\u003eExamine real-world applications of machine learning in various domains including healthcare, the military and marketing but with a particular focus on finance.\u003c\/p\u003e\r\n\u003cp\u003e \u003c\/p\u003e\r\n\u003cp\u003e\u003cstrong\u003eEthical Implications for Financial Institutions:\u003c\/strong\u003e\u003c\/p\u003e\r\n\u003cp\u003eBenzschawel discusses the ethical challenges arising from the integration of AI in decision-making processes and analyses the potential consequences of delegating decision authority to intelligent algorithms.\u003c\/p\u003e\r\n\u003cp\u003e \u003c\/p\u003e\r\n\u003cp\u003e\u003cstrong\u003eWorkforce Preparedness:\u003c\/strong\u003e\u003c\/p\u003e\r\n\u003cp\u003eHave you fostered a skilled workforce capable of harnessing AI's potential? Now is the time to begin preparing.\u003c\/p\u003e\r\n\u003cp\u003e \u003c\/p\u003e\r\n\u003cp\u003e\u003cstrong\u003ePolicy and Governance:\u003c\/strong\u003e\u003c\/p\u003e\r\n\u003cp\u003eThis book outlines strategies to ensure the responsible and transparent use of machine learning technologies.\u003c\/p\u003e\r\n\u003cp\u003e \u003c\/p\u003e\r\n\u003cp\u003e\u003cstrong\u003eInterpretability and Accountability:\u003c\/strong\u003e\u003c\/p\u003e\r\n\u003cp\u003eTransparency and interpretability in machine learning models is essential and Benzschawel discusses mechanisms to ensure accountability and mitigate biases in AI systems.\u003c\/p\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\u003c\/div\u003e","brand":"Risk Books","offers":[{"title":"Default Title","offer_id":50769995399510,"sku":"9781782724452","price":85.0,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0904\/4433\/3398\/files\/machine_learning_2d_crop-v2.jpg?v=1751978128"},{"product_id":"artificial-intelligence-in-finance-volume-2-reinforcement-learning-theory-and-practice","title":"Artificial Intelligence in Finance, Volume 2: Reinforcement Learning Theory and Practice","description":"\u003cstyle\u003e#html-body [data-pb-style=DORF2CK]{justify-content:flex-start;display:flex;flex-direction:column;background-position:left top;background-size:cover;background-repeat:no-repeat;background-attachment:scroll}\u003c\/style\u003e\u003cdiv data-content-type=\"row\" data-appearance=\"contained\" data-element=\"main\"\u003e\u003cdiv data-enable-parallax=\"0\" data-parallax-speed=\"0.5\" data-background-images=\"{}\" data-background-type=\"image\" data-video-loop=\"true\" data-video-play-only-visible=\"true\" data-video-lazy-load=\"true\" data-video-fallback-src=\"\" data-element=\"inner\" data-pb-style=\"DORF2CK\"\u003e\u003cdiv data-content-type=\"text\" data-appearance=\"default\" data-element=\"main\"\u003e\n\u003cp\u003eRedefine What’s Possible in Finance with Reinforcement Learning.\u003cbr\u003eIn this second volume of the Artificial Intelligence in Finance series, the authors explore how Reinforcement Learning (RL) is transforming financial modelling, strategy, and decision-making.\u003cbr\u003eAt its core, RL allows models to learn from experience, dynamically adjusting their strategies based on feedback—successes or failures—at each step. This makes RL a game-changer for tackling multi-step, interdependent financial decisions and for designing entirely new algorithms to address unstructured, high-stakes challenges.\u003cbr\u003eWhat You’ll Learn:\u003cbr\u003e• Foundations first: Markov decision processes (MDPs), optimal policy learning, and general RL frameworks.\u003cbr\u003e• Next-level techniques: Hybrid models that fuse RL with deep learning, stochastic approximation, temporal difference learning, and even large language models.\u003cbr\u003e• Real-world impact:\u003cbr\u003eo Portfolio and wealth management\u003cbr\u003eo Algorithmic trading\u003cbr\u003eo Options pricing and hedging\u003cbr\u003eo Risk management and beyond\u003cbr\u003e• State-of-the-art tools: Explore how Transformers and Graph Neural Networks handle complex financial datasets with unprecedented flexibility.\u003cbr\u003eWith a clear focus on practical application, this book blends rigorous theory with hands-on tools to help professionals and academics alike build smarter, more scalable financial systems.\u003cbr\u003eWhether you're optimizing trading strategies, managing risk, or researching future-proof AI tools, this book is your roadmap to applying RL in the real world of finance.\u003c\/p\u003e\r\n\u003cp\u003e\u003cbr\u003eWhy This Book?\u003cbr\u003e• Demystifies the power and limits of RL in finance\u003cbr\u003e• Bridges the gap between academic theory and industry application\u003cbr\u003e• Helps you build simulation-based, risk-aware, adaptive models\u003cbr\u003e• Builds on Volume 1’s foundation—but stands strong on its own\u003cbr\u003eFor strategists, quants, data scientists, and curious minds—this is essential reading.\u003cbr\u003eAI is changing finance. Reinforcement learning is leading the way.\u003c\/p\u003e\n\u003c\/div\u003e\u003c\/div\u003e\u003c\/div\u003e","brand":"Risk Books","offers":[{"title":"Default Title","offer_id":51232491143510,"sku":"9781782724544","price":145.0,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0904\/4433\/3398\/files\/rb25-ai-in-finance-vol2-2d-411x616.png?v=1751978222"},{"product_id":"model-risk-and-uncertainty-in-the-financial-world","title":"Model Risk and Uncertainty in the Financial World","description":"\u003cp class=\"MsoNormal\"\u003e\u003cb\u003e\u003cspan style=\"font-size: 12.0pt; line-height: 107%; font-family: 'Aptos Display',sans-serif; mso-ascii-theme-font: major-latin; mso-hansi-theme-font: major-latin;\"\u003eModel Risk and Uncertainty in the Financial World\u003c\/span\u003e\u003c\/b\u003e\u003cspan style=\"font-size: 12.0pt; line-height: 107%; font-family: 'Aptos Display',sans-serif; mso-ascii-theme-font: major-latin; mso-hansi-theme-font: major-latin;\"\u003e is a comprehensive work that addresses the art and science of building and managing financial models with an appreciation of the risks and uncertainties that lie within.\u003cspan style=\"mso-spacerun: yes;\"\u003e  \u003c\/span\u003eSoulellis and Ghose highlight how financial models can be laden with uncertainty, prone to failure, and capable of sparking crises when their risks are ignored. \u003c\/span\u003e\u003cspan style=\"font-size: 12.0pt; line-height: 107%; font-family: 'Aptos Display',sans-serif; mso-ascii-theme-font: major-latin; mso-hansi-theme-font: major-latin; mso-bidi-font-family: Calibri; color: #222222; background: white;\"\u003eThey distil foundational concepts in economics, statistics and machine learning into an intuitive accessible read for model builders and users, emphasising a useful distinction between risk and uncertainty, and the importance of managing them differently.\u003cspan style=\"mso-spacerun: yes;\"\u003e  \u003c\/span\u003e\u003c\/span\u003e\u003cspan style=\"font-size: 12.0pt; line-height: 107%; font-family: 'Aptos Display',sans-serif; mso-ascii-theme-font: major-latin; mso-hansi-theme-font: major-latin;\"\u003e\u003c\/span\u003e\u003c\/p\u003e\n\u003cp class=\"MsoNormal\"\u003e\u003cspan style=\"font-size: 12.0pt; line-height: 107%; font-family: 'Aptos Display',sans-serif; mso-ascii-theme-font: major-latin; mso-hansi-theme-font: major-latin;\"\u003eThe authors’ narrative blends history, theory, and practice to show how model risk has affected markets — from Black Monday to the global financial crisis, from COVID-19 to Silicon Valley Bank. Drawing on their deep professional experience, they guide readers through key themes: the limits of probability, the psychology of risk, specification and operations failures, and how the past informs lessons for the future. They argue that uncertainty can never be eliminated — but it can be managed through the application of various measurement and estimation methods as well as a willingness to acknowledge the unknown. \u003c\/span\u003e\u003c\/p\u003e\n\u003cp class=\"MsoNormal\"\u003e\u003cspan style=\"font-size: 12.0pt; line-height: 107%; font-family: 'Aptos Display',sans-serif; mso-ascii-theme-font: major-latin; mso-hansi-theme-font: major-latin;\"\u003eThis book equips bankers, regulators, quants, and policymakers with a sharper awareness of model risk and a toolkit for living with uncertainty. \u003ci\u003eModel Risk and Uncertainty in the Financial World\u003c\/i\u003e is essential reading for anyone who wants to understand where financial modelling has been — and where it’s going next.\u003c\/span\u003e\u003c\/p\u003e","brand":"Risk Books","offers":[{"title":"Default Title","offer_id":51417194955094,"sku":"9781782724209","price":145.0,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0904\/4433\/3398\/files\/Model-Risk-_-Uncertainty-2D-411x616-V2.png?v=1758890849"}],"url":"https:\/\/www.riskbooks.com\/collections\/our-recommendations.oembed","provider":"Risk Books","version":"1.0","type":"link"}