| Description |
1 online resource |
| Contents |
Intro -- Half Title -- Title Page -- Copyright Page -- Dedication -- Contents -- Author -- Introduction -- 1. Fundamental Concepts -- 1.1 All organizations require risk analytics -- 1.2 Evolution of risk analytics -- 1.3 Risk analytics is a crucial concept in risk management processes -- 1.4 Enterprise risk management (ERM) -- 1.5 Measuring, metrics, and business concepts -- 1.6 Understanding data, scales, and data arrays -- 1.7 Basic probability concepts useful in risk analytics -- 1.8 Examples of stochastic processes -- 1.9 Compound Poisson distribution -- 1.9.1 Distribution Function |
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1.9.2 Distribution Function -- 1.9.3 Mean and Variance -- 1.10 Understanding Linear Algebra -- 1.11 Traditional models in finance -- 1.12 RAS: Hybrid system of human and artificial intelligences -- 2. Risk Management, Modeling, and Analytics Processes -- 2.1 Risk management and modeling processes -- 2.2 Risk modeling and risk knowledge development -- 2.2.1 Risk Knowledge Creation -- 2.2.2 Risk Knowledge Storage/Retrieval -- 2.2.3 Risk Knowledge Transfer -- 2.2.4 Risk Knowledge Application and Learning -- 2.3 General analytics process for risk management -- 2.4 Exploratory data analysis (EDA) |
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2.4.1 Illustration Example of EDA-Data Visualization -- 2.5 Data sources and data sampling in risk analytics -- 2.6 Data partition: Training, test, and validation data -- 2.7 Inference and generalization in risk analytics -- 2.8 Method of the moments -- 2.9 Maximum likelihood estimation -- 2.10 Estimators by optimization -- 2.11 Risk analytics road map -- 2.11.1 A View of Combining Marketing Risk and Credit Risk -- 2.11.1.1 Multivariate Analysis -- 2.11.1.2 Clustering Using k-Means -- 3. Decision Making Under Risk and Its Analytics Support -- 3.1 About general tools for supporting decision making |
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3.2 Benchmark approach for defining metrics -- 3.3 Steps to start the definition of metrics -- 3.4 Creating clusters of companies based on their returns -- 3.5 About risk indicators in a multivariate approach -- 3.6 Comparing risk metrics in groups -- 3.7 Decision making on investments in a risk prescriptive analytics approach -- 3.8 Forecasting and time series as a means to support decision making -- 3.8.1 Forecasting Models for Stationary Time Series -- 4. Risk Management and Analytics in Organizations -- 4.1 How to start a risk measurement system |
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4.2 Default rates, probabilities of default, and risk scales -- 4.2.1 Graphical Review of Loss Distribution Fitting -- 4.3 Exposure and default rate construction -- 4.4 An illustration of default rate calculation -- 4.5 Example of particular metric: Probable maximum loss -- 4.6 Adapting metrics to risk conditions: Banks illustration -- 4.6.1 Metrics in a Bank Setting -- 4.7 Exposure management in supply-chain risk -- 5. Tools for Risk Management -- 5.1 Prevention, resilience, and prediction -- 5.2 Risk analytics knowledge of return |
| Summary |
"Organizations and institutions are looking for implementing data-driven decision-making processes, business process improvement and methods for advancing faster in innovation. This book is about implementing the analytics process to develop a risk management practice that creates competitive advantages under uncertainty"-- Provided by publisher |
| Bibliography |
Includes bibliographical references and index |
| Notes |
Eduardo Rodriguez Ph.D. is a member of the Advisory Board of the new Finance, Innovation and Technology Certificate from the Fields Institute of Mathematics, University of Toronto. He is an Assistant Professor in the School of the Mathematical Sciences at Wenzhou -Kean University in Wenzhou China. He is the founder and leader of the Risk Analytics Lab at Wenzhou Kean University. Lately, he has been active participant in the creation and development of the Data Science Program at the Inter-American University of Puerto Rico and keynote speaker in the CSAE International Conference on Computer Science and Application Engineering 2021 and 2022. Moreover, he is an Analytics Adjunct Professor at Telfer School of Management at University of Ottawa , Canada. He is the Founder and Principal at IQAnalytics Inc. Research Centre and Consulting Firm in Ottawa Canada. Eduardo was the first Sentry Endowed Chair in Business Analytics University of Wisconsin-Stevens Point. He has been Corporate Faculty of the MSc in Analytics at Harrisburg University of Science and Technology Pennsylvania USA, Senior Associate-Faculty of the Center for Dynamic Leadership Models in Global Business at The Leadership Alliance Inc. Toronto Canada, and in his work, he has created and developed the Analytics Stream of the MBA at the University of Fredericton, Canada. He has been Visiting Scholar Chongqing University China, and EAFIT University for the Master of Risk Management. Eduardo has extensive experience in analytics, knowledge, and risk management mainly in the insurance and banking industry. He has been the Knowledge Management Advisor and Quantitative Analyst at EDC Export Development Canada in Ottawa, Regional Director of PRMIA (Professional Risk Managers International Association) in Ottawa, Executive Vice-President, Vice-President Marketing and Planning for Insurance Companies and Banks in Colombia. Moreover, he has worked as a part-time professor at Andes University and CESA in Colombia, author of six books in analytics, reviewer of several journals and with publications in peer-reviewed journals and conferences. He created and Chair the Analytics Think-Tank, organized and Chair of the International Conference in Analytics ICAS, member of academic committees for conferences in Knowledge Management and international lecturer in the analytics field. Eduardo holds a Ph.D. from Aston Business School, Aston University in the UK, an MSc. Mathematics Concordia University Montreal Canada, Certification of the Advanced Management Program McGill University Canada, and an MBA and bachelor's in mathematics from Los Andes University Colombia. His main research interest is in the field of Strategic Risk, Risk Analytics, Startegic Intelligence Development, and Knowledge Management applied to Enterprise Risk Management |
| Subject |
Management -- Statistical methods
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Risk assessment -- Data processing
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Decision making.
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Organizational effectiveness.
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decision making.
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COMPUTERS / Database Management / Data Mining
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COMPUTERS / Data Processing / General
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Decision making.
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Management -- Statistical methods.
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Organizational effectiveness.
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Risk assessment -- Data processing.
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| Form |
Electronic book
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| ISBN |
9781000893090 |
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100089309X |
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9780429342899 |
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0429342896 |
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9781000893083 |
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1000893081 |
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