Risk Analytics

Data-Driven Decisions under Uncertainty
1. Auflage 2023
ISBN: 978-0-367-35961-4
Verlag: Auerbach Publications

Buch, Englisch, 479 Seiten, Format (B × H): 183 mm x 260 mm, Gewicht: 1093 g

The 2022 World Economic Forum surveyed 1,000 experts and leaders who indicated their risk perception that the earth’s conditions for humans are a main concern in the next 10 years. This means environmental risks are a priority to study in a formal way. At the same time, innovation risks are present in theminds of leaders, newknowledge brings new risk, and the adaptation and adoption of risk knowledge is required to better understand the causes and effects can have on technological risks. These opportunities require not only adopting new ways of managing and controlling emerging processes for society and business, but also adapting organizations to changes and managing new risks.

Risk Analytics: Data-Driven Decisions Under Uncertainty introduces a way to analyze and design a risk analytics system (RAS) that integrates multiple approaches to risk analytics to deal with diverse types of data and problems. A risk analytics system is a hybrid system where human and artificial intelligence interact with a data gathering and selection process that uses multiple sources to the delivery of guidelines to make decisions that include humans and machines. The RAS system is an integration of components, such as data architecture with diverse data, and a risk analytics process and modeling process to obtain knowledge and then determine actions through the new knowledge that was obtained. The use of data analytics is not only connected to risk modeling and its implementation, but also to the development of the actionable knowledge that can be represented by text in documents to define and share explicit knowledge and guidelines in the organization for strategy implementation.

This book moves from a review of data to the concepts of a RAS. It reviews RAS system components required to support the creation of competitive advantage in organizations through risk analytics. Written for executives, analytics professionals, risk management professionals, strategy professionals, and postgraduate students, this book shows a way to implement the analytics process to develop a risk management practice that creates an adaptive competitive advantage under uncertainty.

Zielgruppe

Professional Practice & Development

Autoren/Hrsg.

Rodriguez, Eduardo

Fachgebiete

• Wirtschaftswissenschaften Betriebswirtschaft Management Risikomanagement
• Mathematik | Informatik EDV | Informatik Daten / Datenbanken Data Mining
• Mathematik | Informatik EDV | Informatik EDV & Informatik Allgemein
• Mathematik | Informatik EDV | Informatik Daten / Datenbanken Automatische Datenerfassung, Datenanalyse
• Wirtschaftswissenschaften Finanzsektor & Finanzdienstleistungen Finanzsektor & Finanzdienstleistungen: Allgemeines

Inhaltsverzeichnis

1. Fundamental Concepts 2. Risk Management, Modelling, and Analytics Processes 3. Decision Making under Risk and Its Analytics Support 4. Risk Management and Analytics in Organizations 5. Tools for Risk Management 6. Data Analytics in Risk Management 7. Machine and Statistical Learning in Risk Analytics 8. Dealing with Monitoring the Risk Analytics Process 9. Creation of Actions and Value

Über Autor(innen)

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.