Sustainable Financial Innovation
Sustainable Financial Innovation

Author: Karen Wendt

Publisher: CRC Press

Published: 2018-12-12

Total Pages: 213

ISBN-13: 1351652265

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Innovations and consequently future-fitness must form new models and address existing hurdles and new forms of collaborations. They must enable faster innovation cycles and "intelligence mining" by combining open and closed source systems, organic communities, open space techniques and cross-fertilization. Innovations must apply to and integrate incubation and acceleration networks. This book explores new concepts for future-fitness with five capitals: financial, ecological, social/cultural, human/personal, and manufactured/technological. It offers a new integral framework bringing researchers and business leaders together in one volume.

Morningstar Funds 500
Morningstar Funds 500

Author: Morningstar Inc.

Publisher: Wiley

Published: 2008-02-08

Total Pages: 614

ISBN-13: 9780470121290

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In this completely new reference guide, you’ll find the best information and independent opinion available on 500 of the largest and most popular mutual funds—the very funds you likely own. Morningstar’s Fund Reports are the industry standard and are trusted by financial professionals nationwide. And now, you get this exclusive and valuable guidance all year long, with access to fifty free fund reports during any time in 2008. Choose from 2,000 funds.

Bank 4.0
Bank 4.0

Author: Brett King

Publisher: John Wiley & Sons

Published: 2018-12-17

Total Pages: 359

ISBN-13: 1119506506

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Winner of best book by a foreign author (2019) at the Business Book of the Year Award organised by PwC Russia The future of banking is already here — are you ready? Bank 4.0 explores the radical transformation already taking place in banking, and follows it to its logical conclusion. What will banking look like in 30 years? 50 years? The world’s best banks have been forced to adapt to changing consumer behaviors; regulators are rethinking friction, licensing and regulation; Fintech start-ups and tech giants are redefining how banking fits in the daily life of consumers. To survive, banks are having to develop new capabilities, new jobs and new skills. The future of banking is not just about new thinking around value stores, payment and credit utility — it's embedded in voice-based smart assistants like Alexa and Siri and soon smart glasses which will guide you on daily spending and money decisions. The coming Bank 4.0 era is one where either your bank is embedded in your world via tech, or it no longer exists. In this final volume in Brett King's BANK series, we explore the future of banks amidst the evolution of technology and discover a revolution already at work. From re-engineered banking systems, to selfie-pay and self-driving cars, Bank 4.0 proves that we're not on Wall Street anymore. Bank 4.0 will help you: Understand the historical precedents that flag a fundamental rethinking in banking Discover low-friction, technology experiences that undermine the products we sell today Think through the evolution of identity, value and assets as cash and cards become obsolete Learn how Fintech and tech "disruptors" are using behaviour, psychology and technology to reshape the economics of banking Examine the ways in which blockchain, A.I., augmented reality and other leading-edge tech are the real building blocks of the future of banking systems If you look at individual technologies or startups disrupting the space, you might miss the biggest signposts to the future and you might also miss that most of we've learned about banking the last 700 years just isn't useful. When the biggest bank in the world isn't any of the names you'd expect, when branch networks are a burden not an asset, and when advice is the domain of Artificial Intelligence, we may very well have to start from scratch. Bank 4.0 takes you to a world where banking will be instant, smart and ubiquitous, and where you'll have to adapt faster than ever before just to survive. Welcome to the future.

Corporate Social Responsibility
Corporate Social Responsibility

Author: Andrew Crane

Publisher: Routledge

Published: 2014

Total Pages: 630

ISBN-13: 1000021238

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As a relatively young subject matter, corporate social responsibility has unsurprisingly developed and evolved in numerous ways since the first edition of this textbook was published. Retaining the features which made the first edition a top selling text in the field, the new edition continues to be the only textbook available which provides a ready-made, enhanced course pack for CSR classes. Authoritative editor introductions provide accessible entry points to the subjects covered - an approach which is particularly suited to advanced undergraduate and postgraduate teaching that emphasises a research-led approach. New case studies are integrated throughout the text to enable students to think and analyze the subject from every angle. The entire textbook reflects the global nature of CSR as a discipline and further pedagogical features include chapter learning outcomes; study questions; ‘challenges for practice’ boxes and additional ‘further reading’ features at the end of each chapter. This highly rated textbook now also benefits from a regularly updated companion website which features a brand new 'CSR Case Club' presenting students and lecturers with further case suggestions with which to enhance learning; lecture slides; updates from the popular Crane and Matten blog, links to further reading and career sites, YouTube clips and suggested answers to study questions. An Ivey CaseMate has also been created for this book at https://www.iveycases.com/CaseMateBookDetail.aspx?id=335.

Neural Networks and Deep Learning
Neural Networks and Deep Learning

Author: Charu C. Aggarwal

Publisher: Springer

Published: 2018-08-25

Total Pages: 512

ISBN-13: 3319944630

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This book covers both classical and modern models in deep learning. The primary focus is on the theory and algorithms of deep learning. The theory and algorithms of neural networks are particularly important for understanding important concepts, so that one can understand the important design concepts of neural architectures in different applications. Why do neural networks work? When do they work better than off-the-shelf machine-learning models? When is depth useful? Why is training neural networks so hard? What are the pitfalls? The book is also rich in discussing different applications in order to give the practitioner a flavor of how neural architectures are designed for different types of problems. Applications associated with many different areas like recommender systems, machine translation, image captioning, image classification, reinforcement-learning based gaming, and text analytics are covered. The chapters of this book span three categories: The basics of neural networks: Many traditional machine learning models can be understood as special cases of neural networks. An emphasis is placed in the first two chapters on understanding the relationship between traditional machine learning and neural networks. Support vector machines, linear/logistic regression, singular value decomposition, matrix factorization, and recommender systems are shown to be special cases of neural networks. These methods are studied together with recent feature engineering methods like word2vec. Fundamentals of neural networks: A detailed discussion of training and regularization is provided in Chapters 3 and 4. Chapters 5 and 6 present radial-basis function (RBF) networks and restricted Boltzmann machines. Advanced topics in neural networks: Chapters 7 and 8 discuss recurrent neural networks and convolutional neural networks. Several advanced topics like deep reinforcement learning, neural Turing machines, Kohonen self-organizing maps, and generative adversarial networks are introduced in Chapters 9 and 10. The book is written for graduate students, researchers, and practitioners. Numerous exercises are available along with a solution manual to aid in classroom teaching. Where possible, an application-centric view is highlighted in order to provide an understanding of the practical uses of each class of techniques.