Data Driven Modelling And Predictive Analytics In Business And Finance
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Data Driven Modelling And Predictive Analytics In Business And Finance
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Author : Alex Khang
language : en
Publisher: CRC Press
Release Date : 2024-07-24
Data Driven Modelling And Predictive Analytics In Business And Finance written by Alex Khang and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-07-24 with Computers categories.
Data-driven and AI-aided applications are next-generation technologies that can be used to visualize and realize intelligent transactions in finance, banking, and business. These transactions will be enabled by powerful data-driven solutions, IoT technologies, AI-aided techniques, data analytics, and visualization tools. To implement these solutions, frameworks will be needed to support human control of intelligent computing and modern business systems. The power and consistency of data-driven competencies are a critical challenge, and so is developing explainable AI (XAI) to make data-driven transactions transparent. Data- Driven Modelling and Predictive Analytics in Business and Finance covers the need for intelligent business solutions and applications. Explaining how business applications use algorithms and models to bring out the desired results, the book covers: Data-driven modelling Predictive analytics Data analytics and visualization tools AI-aided applications Cybersecurity techniques Cloud computing IoT-enabled systems for developing smart financial systems This book was written for business analysts, financial analysts, scholars, researchers, academics, professionals, and students so they may be able to share and contribute new ideas, methodologies, technologies, approaches, models, frameworks, theories, and practices.
Predictive Intelligence For Data Driven Managers
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Author : Uwe Seebacher
language : en
Publisher: Springer Nature
Release Date : 2021-03-26
Predictive Intelligence For Data Driven Managers written by Uwe Seebacher and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-03-26 with Business & Economics categories.
This book describes how companies can easily and pragmatically set up and realize the path to a data-driven enterprise, especially in the marketing practice, without external support and additional investments. Using a predictive intelligence (PI) ecosystem, the book first introduces and explains the most important concepts and terminology. The PI maturity model then describes the phases in which you can build a PI ecosystem in your company. The book also demonstrates a PI self-test which helps managers identify the initial steps. In addition, a blueprint for a PI tech stack is defined for the first time, showing how IT can best support the topic. Finally, the PI competency model summarizes all elements into an action model for the company. The entire book is underpinned with practical examples, and case studies show how predictive intelligence, in the spirit of data-driven management, can be used profitably in the short, medium, and long terms.
Three Essays On Business Analytics
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Author : Yuxin Zhang (Ph. D.)
language : en
Publisher:
Release Date : 2020
Three Essays On Business Analytics written by Yuxin Zhang (Ph. D.) and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020 with categories.
In my dissertation, I propose a general research framework of MAD---Monitoring, Analyzing, and Data Informed Decision-making---for financial decision-making. I present three essays which concentrate on two consequential aspects of decision-making for financial risk management. The first two essays focus on better monitoring and analyzing the risk, and the last one focuses on better data-informed decision-making based on the observation and analysis. In the first essay, I study the modeling of joint mortality for the practice of life insurance and annuity pricing. Specifically, I develop a new mathematical model to describe the joint mortality for coupled dependent lives. This model can be used to guide the risk management strategy and the pricing policy for insurance and annuity products. It is shown that it improves the current methods for modeling financial decision-making related to dependent life structures (such as joint life insurance, last survivor annuities, and defined benefit plans for married couples). In the second essay, I study the prediction of Bitcoin price movement and the relevant implications for business analytics. I exploit Bitcoin transaction networks and link network characteristics with the Bitcoin market exchange price. Based on this linkage and the data record, I construct predictive models for Bitcoin price movement. With the innovative use of Bitcoin transaction network data, the predictive models lead to more accurate results which outperform existing models. This methodological innovation also presents new managerial insights from network perspectives. In the third essay, I focus on data-driven decision-making in contexts of the allocation of disaster relief funds. Specifically, I tackle methodological challenges in disaster management when data are extremely sparse and insufficient in the beginning of the disaster evolution, and slowly become more available and reliable as time unfolds. Here I propose an iterative learning method within the general MAD framework to estimate disaster damage losses using very limited and slowly obtained data. Results show that this iterative learning method leads to highly accurate results with fast convergence of the estimation error to a very low level. The framework and results of this essay can be further used for disaster management and resource allocation in various scenarios
Synergy Of Ai And Fintech In The Digital Gig Economy
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Author : Alex Khang
language : en
Publisher: CRC Press
Release Date : 2024-09-30
Synergy Of Ai And Fintech In The Digital Gig Economy written by Alex Khang and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-09-30 with Computers categories.
The convergence of Artificial Intelligence (AI) and Financial Technology (Fintech) has ushered in a new era of innovation in the finance ecosystem, particularly within the context of the digital gig economy. This emerging trend has created a unique set of challenges and opportunities, which AI and Fintech are poised to address. This book explores how the convergence of these cutting-edge technologies is reshaping the financial landscape, especially related to the way people work and earn in the gig economy, and examines the rise of the digital gig economy and its impact on the traditional workforce. Synergy of AI and Fintech in the Digital Gig Economy presents the key advancements in AI and Fintech, how they are disrupting traditional financial systems, and how AI-powered tools and platforms are streamlining financial processes, enhancing decision-making, and providing personalized services to individuals and businesses. The book explores how the synergy of AI and Fintech is advancing financial inclusion and looks at how these technologies are providing previously underserved populations with access to financial services and empowering them to participate in the global economy. Highlights include how AI and Fintech are revolutionizing risk assessment and management in the financial sector and discuss the use of advanced algorithms to detect fraud, assess creditworthiness, and mitigate financial risk more effectively. The book also addresses the regulatory challenges and ethical considerations arising from the integration of AI and Fintech and discusses the need for responsible AI and data privacy to ensure sustainable development. Insights, case studies, and practical examples provided in the book show how AI and Fintech are driving transformative changes and represent an area of significant interest and importance in the realm of finance and technology. Written for students, scholars, lecturers, researchers, scientists, experts, specialists, and engineers, this book represents an area of significant interest and importance in the realm of finance and technology. Real-world examples and contributions from industry experts give readers a comprehensive understanding of this hot trending topic.
Modeling Techniques In Predictive Analytics
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Author : Thomas W. Miller
language : en
Publisher: FT Press
Release Date : 2013-08-23
Modeling Techniques In Predictive Analytics written by Thomas W. Miller and has been published by FT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-08-23 with Business & Economics categories.
Today, successful firms compete and win based on analytics. Modeling Techniques in Predictive Analytics brings together all the concepts, techniques, and R code you need to excel in any role involving analytics. Thomas W. Miller’s unique balanced approach combines business context and quantitative tools, appealing to managers, analysts, programmers, and students alike. Miller addresses multiple business challenges and business cases, including segmentation, brand positioning, product choice modeling, pricing research, finance, sports, text analytics, sentiment analysis, and social network analysis. He illuminates the use of cross-sectional data, time series, spatial, and even spatio-temporal data. For each problem, Miller explains why the problem matters, what data is relevant, how to explore your data once you’ve identified it, and then how to successfully model that data. You’ll learn how to model data conceptually, with words and figures; and then how to model it with realistic R programs that deliver actionable insights and knowledge. Miller walks you through model construction, explanatory variable subset selection, and validation, demonstrating best practices for improving out-of-sample predictive performance. He employs data visualization and statistical graphics in exploring data, presenting models, and evaluating performance. All example code is presented in R, today’s #1 system for applied statistics, statistical research, and predictive modeling; code is set apart from other text so it’s easy to find for those who want it (and easy to skip for those who don’t).
Financial Data Analytics With Machine Learning Optimization And Statistics
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Author : Yongzhao Chen
language : en
Publisher: Wiley
Release Date : 2023-06-06
Financial Data Analytics With Machine Learning Optimization And Statistics written by Yongzhao Chen and has been published by Wiley this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-06-06 with Business & Economics categories.
An essential introduction to data analytics and Machine Learning techniques in the business sector In Financial Data Analytics with Machine Learning, Optimization and Statistics, a team consisting of a distinguished applied mathematician and statistician, experienced actuarial professionals and working data analysts delivers an expertly balanced combination of traditional financial statistics, effective machine learning tools, and mathematics. The book focuses on contemporary techniques used for data analytics in the financial sector and the insurance industry with an emphasis on mathematical understanding and statistical principles and connects them with common and practical financial problems. Each chapter is equipped with derivations and proofs—especially of key results—and includes several realistic examples which stem from common financial contexts. The computer algorithms in the book are implemented using Python and R, two of the most widely used programming languages for applied science and in academia and industry, so that readers can implement the relevant models and use the programs themselves. The book begins with a brief introduction to basic sampling theory and the fundamentals of simulation techniques, followed by a comparison between R and Python. It then discusses statistical diagnosis for financial security data and introduces some common tools in financial forensics such as Benford's Law, Zipf's Law, and anomaly detection. The statistical estimation and Expectation-Maximization (EM) & Majorization-Minimization (MM) algorithms are also covered. The book next focuses on univariate and multivariate dynamic volatility and correlation forecasting, and emphasis is placed on the celebrated Kelly's formula, followed by a brief introduction to quantitative risk management and dependence modelling for extremal events. A practical topic on numerical finance for traditional option pricing and Greek computations immediately follows as well as other important topics in financial data-driven aspects, such as Principal Component Analysis (PCA) and recommender systems with their applications, as well as advanced regression learners such as kernel regression and logistic regression, with discussions on model assessment methods such as simple Receiver Operating Characteristic (ROC) curves and Area Under Curve (AUC) for typical classification problems. The book then moves on to other commonly used machine learning tools like linear classifiers such as perceptrons and their generalization, the multilayered counterpart (MLP), Support Vector Machines (SVM), as well as Classification and Regression Trees (CART) and Random Forests. Subsequent chapters focus on linear Bayesian learning, including well-received credibility theory in actuarial science and functional kernel regression, and non-linear Bayesian learning, such as the Naïve Bayes classifier and the Comonotone-Independence Bayesian Classifier (CIBer) recently independently developed by the authors and used successfully in InsurTech. After an in-depth discussion on cluster analyses such as K-means clustering and its inversion, the K-nearest neighbor (KNN) method, the book concludes by introducing some useful deep neural networks for FinTech, like the potential use of the Long-Short Term Memory model (LSTM) for stock price prediction. This book can help readers become well-equipped with the following skills: To evaluate financial and insurance data quality, and use the distilled knowledge obtained from the data after applying data analytic tools to make timely financial decisions To apply effective data dimension reduction tools to enhance supervised learning To describe and select suitable data analytic tools as introduced above for a given dataset depending upon classification or regression prediction purpose The book covers the competencies tested by several professional examinations, such as the Predictive Analytics Exam offered by the Society of Actuaries, and the Institute and Faculty of Actuaries' Actuarial Statistics Exam. Besides being an indispensable resource for senior undergraduate and graduate students taking courses in financial engineering, statistics, quantitative finance, risk management, actuarial science, data science, and mathematics for AI, Financial Data Analytics with Machine Learning, Optimization and Statistics also belongs in the libraries of aspiring and practicing quantitative analysts working in commercial and investment banking.
Revolutionizing The Ai Digital Landscape
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Author : Alex Khang
language : en
Publisher: CRC Press
Release Date : 2024-06-07
Revolutionizing The Ai Digital Landscape written by Alex Khang and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-06-07 with Business & Economics categories.
This book investigates the growing influence of artificial intelligence in the marketing sphere, providing insights into how AI can be harnessed for developing more effective and efficient marketing strategies. In addition, the book will also offer a comprehensive overview of the various digital marketing tools available to entrepreneurs, discussing their features, benefits, and potential drawbacks. This will help entrepreneurs make well-informed decisions when selecting the tools most suited to their needs and objectives. It is designed to help entrepreneurs develop and implement successful strategies, leveraging the latest tools and technologies to achieve their business goals. As the digital landscape continues to evolve rapidly, this book aims to serve as a valuable resource for entrepreneurs looking to stay ahead of the curve and capitalize on new opportunities. The book's scope encompasses a wide range of topics, including customer experience, content marketing, AI strategy, and digital marketing tools.
Applied Predictive Analytics
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Author : Dean Abbott
language : en
Publisher: John Wiley & Sons
Release Date : 2014-03-31
Applied Predictive Analytics written by Dean Abbott and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-03-31 with Computers categories.
Learn the art and science of predictive analytics — techniques that get results Predictive analytics is what translates big data into meaningful, usable business information. Written by a leading expert in the field, this guide examines the science of the underlying algorithms as well as the principles and best practices that govern the art of predictive analytics. It clearly explains the theory behind predictive analytics, teaches the methods, principles, and techniques for conducting predictive analytics projects, and offers tips and tricks that are essential for successful predictive modeling. Hands-on examples and case studies are included. The ability to successfully apply predictive analytics enables businesses to effectively interpret big data; essential for competition today This guide teaches not only the principles of predictive analytics, but also how to apply them to achieve real, pragmatic solutions Explains methods, principles, and techniques for conducting predictive analytics projects from start to finish Illustrates each technique with hands-on examples and includes as series of in-depth case studies that apply predictive analytics to common business scenarios A companion website provides all the data sets used to generate the examples as well as a free trial version of software Applied Predictive Analytics arms data and business analysts and business managers with the tools they need to interpret and capitalize on big data.
Predictive Business Analytics
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Author : Lawrence Maisel
language : en
Publisher: John Wiley & Sons
Release Date : 2013-10-07
Predictive Business Analytics written by Lawrence Maisel and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-10-07 with Business & Economics categories.
Discover the breakthrough tool your company can use to make winning decisions This forward-thinking book addresses the emergence of predictive business analytics, how it can help redefine the way your organization operates, and many of the misconceptions that impede the adoption of this new management capability. Filled with case examples, Predictive Business Analytics defines ways in which specific industries have applied these techniques and tools and how predictive business analytics can complement other financial applications such as budgeting, forecasting, and performance reporting. Examines how predictive business analytics can help your organization understand its various drivers of performance, their relationship to future outcomes, and improve managerial decision-making Looks at how to develop new insights and understand business performance based on extensive use of data, statistical and quantitative analysis, and explanatory and predictive modeling Written for senior financial professionals, as well as general and divisional senior management Visionary and effective, Predictive Business Analytics reveals how you can use your business's skills, technologies, tools, and processes for continuous analysis of past business performance to gain forward-looking insight and drive business decisions and actions.
Ai Centric Modeling And Analytics
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Author : Alex Khang
language : en
Publisher: CRC Press
Release Date : 2023-12-06
Ai Centric Modeling And Analytics written by Alex Khang and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-12-06 with Technology & Engineering categories.
This book shares new methodologies, technologies, and practices for resolving issues associated with leveraging AI-centric modeling, data analytics, machine learning-aided models, Internet of Things-driven applications, and cybersecurity techniques in the era of Industrial Revolution 4.0. AI-Centric Modeling and Analytics: Concepts, Technologies, and Applications focuses on how to implement solutions using models and techniques to gain insights, predict outcomes, and make informed decisions. This book presents advanced AI-centric modeling and analysis techniques that facilitate data analytics and learning in various applications. It offers fundamental concepts of advanced techniques, technologies, and tools along with the concept of real-time analysis systems. It also includes AI-centric approaches for the overall innovation, development, and implementation of business development and management systems along with a discussion of AI-centric robotic process automation systems that are useful in many government and private industries. This reference book targets a mixed audience of engineers and business analysts, researchers, professionals, and students from various fields.