Fundamental Aspects Of Operational Risk And Insurance Analytics
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| Author | : Marcelo G. Cruz |
| Publisher | : John Wiley & Sons |
| Total Pages | : 939 |
| Release | : 2015-01-29 |
| Genre | : Mathematics |
| ISBN | : 1118573005 |
A one-stop guide for the theories, applications, and statistical methodologies essential to operational risk Providing a complete overview of operational risk modeling and relevant insurance analytics, Fundamental Aspects of Operational Risk and Insurance Analytics: A Handbook of Operational Risk offers a systematic approach that covers the wide range of topics in this area. Written by a team of leading experts in the field, the handbook presents detailed coverage of the theories, applications, and models inherent in any discussion of the fundamentals of operational risk, with a primary focus on Basel II/III regulation, modeling dependence, estimation of risk models, and modeling the data elements. Fundamental Aspects of Operational Risk and Insurance Analytics: A Handbook of Operational Risk begins with coverage on the four data elements used in operational risk framework as well as processing risk taxonomy. The book then goes further in-depth into the key topics in operational risk measurement and insurance, for example diverse methods to estimate frequency and severity models. Finally, the book ends with sections on specific topics, such as scenario analysis; multifactor modeling; and dependence modeling. A unique companion with Advances in Heavy Tailed Risk Modeling: A Handbook of Operational Risk, the handbook also features: Discussions on internal loss data and key risk indicators, which are both fundamental for developing a risk-sensitive framework Guidelines for how operational risk can be inserted into a firm’s strategic decisions A model for stress tests of operational risk under the United States Comprehensive Capital Analysis and Review (CCAR) program A valuable reference for financial engineers, quantitative analysts, risk managers, and large-scale consultancy groups advising banks on their internal systems, the handbook is also useful for academics teaching postgraduate courses on the methodology of operational risk.
| Author | : Marcelo G. Cruz |
| Publisher | : John Wiley & Sons |
| Total Pages | : 928 |
| Release | : 2015-01-20 |
| Genre | : Mathematics |
| ISBN | : 1118573021 |
A one-stop guide for the theories, applications, and statistical methodologies essential to operational risk Providing a complete overview of operational risk modeling and relevant insurance analytics, Fundamental Aspects of Operational Risk and Insurance Analytics: A Handbook of Operational Risk offers a systematic approach that covers the wide range of topics in this area. Written by a team of leading experts in the field, the handbook presents detailed coverage of the theories, applications, and models inherent in any discussion of the fundamentals of operational risk, with a primary focus on Basel II/III regulation, modeling dependence, estimation of risk models, and modeling the data elements. Fundamental Aspects of Operational Risk and Insurance Analytics: A Handbook of Operational Risk begins with coverage on the four data elements used in operational risk framework as well as processing risk taxonomy. The book then goes further in-depth into the key topics in operational risk measurement and insurance, for example diverse methods to estimate frequency and severity models. Finally, the book ends with sections on specific topics, such as scenario analysis; multifactor modeling; and dependence modeling. A unique companion with Advances in Heavy Tailed Risk Modeling: A Handbook of Operational Risk, the handbook also features: Discussions on internal loss data and key risk indicators, which are both fundamental for developing a risk-sensitive framework Guidelines for how operational risk can be inserted into a firm’s strategic decisions A model for stress tests of operational risk under the United States Comprehensive Capital Analysis and Review (CCAR) program A valuable reference for financial engineers, quantitative analysts, risk managers, and large-scale consultancy groups advising banks on their internal systems, the handbook is also useful for academics teaching postgraduate courses on the methodology of operational risk.
| Author | : Marcelo G. Cruz |
| Publisher | : Wiley |
| Total Pages | : 0 |
| Release | : 2015-07-13 |
| Genre | : Mathematics |
| ISBN | : 9781118909577 |
Two cutting-edge guides for the theories, applications, and statistical methodologies essential to operational risk and heavy tailed risk modeling Focusing on the quantitative aspects of heavy tailed loss processes in operational risk and relevant insurance analytics, Advances in Heavy Tailed Risk Modeling: A Handbook of Operational Risk presents comprehensive coverage of the latest research on the theories and applications in risk measurement and modeling techniques. Featuring a unique balance of mathematical and statistical perspectives, the handbook begins by introducing the motivation for heavy tailed risk processes in high consequence low frequency loss modeling. With a companion, Fundamental Aspects of Operational Risk and Insurance Analytics: A Handbook of Operational Risk, the book provides a complete framework for all aspects of operational risk management. Fundamental Aspects of Operational Risk and Insurance Analytics covers the theories, applications, and models inherent in any discussion of the fundamentals of operational risk, with a primary focus on Basel II/III regulation, modeling dependence, estimation of risk models, and modeling the data elements.
| Author | : Harry H. Panjer |
| Publisher | : John Wiley & Sons |
| Total Pages | : 460 |
| Release | : 2006-10-13 |
| Genre | : Business & Economics |
| ISBN | : 0470051302 |
Discover how to optimize business strategies from both qualitative and quantitative points of view Operational Risk: Modeling Analytics is organized around the principle that the analysis of operational risk consists, in part, of the collection of data and the building of mathematical models to describe risk. This book is designed to provide risk analysts with a framework of the mathematical models and methods used in the measurement and modeling of operational risk in both the banking and insurance sectors. Beginning with a foundation for operational risk modeling and a focus on the modeling process, the book flows logically to discussion of probabilistic tools for operational risk modeling and statistical methods for calibrating models of operational risk. Exercises are included in chapters involving numerical computations for students' practice and reinforcement of concepts. Written by Harry Panjer, one of the foremost authorities in the world on risk modeling and its effects in business management, this is the first comprehensive book dedicated to the quantitative assessment of operational risk using the tools of probability, statistics, and actuarial science. In addition to providing great detail of the many probabilistic and statistical methods used in operational risk, this book features: * Ample exercises to further elucidate the concepts in the text * Definitive coverage of distribution functions and related concepts * Models for the size of losses * Models for frequency of loss * Aggregate loss modeling * Extreme value modeling * Dependency modeling using copulas * Statistical methods in model selection and calibration Assuming no previous expertise in either operational risk terminology or in mathematical statistics, the text is designed for beginning graduate-level courses on risk and operational management or enterprise risk management. This book is also useful as a reference for practitioners in both enterprise risk management and risk and operational management.
| Author | : Patricia L. Saporito |
| Publisher | : Pearson Education |
| Total Pages | : 204 |
| Release | : 2015 |
| Genre | : Business & Economics |
| ISBN | : 0133760367 |
Data is the insurance industry's single greatest asset. Yet many insurers radically underutilize their data assets, and are failing to fully leverage modern analytics. This makes them vulnerable to traditional and non-traditional competitors alike. Today, insurers largely apply analytics in important but stovepiped operational areas like underwriting, claims, marketing and risk management. By and large, they lack an enterprise analytic strategy -- or, if they have one, it is merely an architectural blueprint, inadequately business-driven or strategically aligned. Now, writing specifically for insurance industry professionals and leaders, Patricia Saporito uncovers immense new opportunities for driving competitive advantage from analytics -- and shows how to overcome the obstacles that stand in your way. Drawing on 25+ years of insurance industry experience, Saporito introduces proven best practices for developing, maturing, and profiting from your analytic capabilities. This user-friendly handbook advocates an enterprise strategy approach to analytics, presenting a common framework you can quickly adapt based on your unique business model and current capabilities. Saporito reviews common analytic applications by functional area, offering specific case studies and examples, and helping you build upon the analytics you're already doing. She presents data governance models and models proven to help you organize and deliver trusted data far more effectively. Finally, she provides tools and frameworks for improving the "analytic IQ" of your entire enterprise, from IT developers to business users.
| Author | : Tony Boobier |
| Publisher | : John Wiley & Sons |
| Total Pages | : 296 |
| Release | : 2016-10-10 |
| Genre | : Business & Economics |
| ISBN | : 1119141079 |
The business guide to Big Data in insurance, with practical application insight Big Data and Analytics for Insurers is the industry-specific guide to creating operational effectiveness, managing risk, improving financials, and retaining customers. Written from a non-IT perspective, this book focusses less on the architecture and technical details, instead providing practical guidance on translating analytics into target delivery. The discussion examines implementation, interpretation, and application to show you what Big Data can do for your business, with insights and examples targeted specifically to the insurance industry. From fraud analytics in claims management, to customer analytics, to risk analytics in Solvency 2, comprehensive coverage presented in accessible language makes this guide an invaluable resource for any insurance professional. The insurance industry is heavily dependent on data, and the advent of Big Data and analytics represents a major advance with tremendous potential – yet clear, practical advice on the business side of analytics is lacking. This book fills the void with concrete information on using Big Data in the context of day-to-day insurance operations and strategy. Understand what Big Data is and what it can do Delve into Big Data's specific impact on the insurance industry Learn how advanced analytics can revolutionise the industry Bring Big Data out of IT and into strategy, management, marketing, and more Big Data and analytics is changing business – but how? The majority of Big Data guides discuss data collection, database administration, advanced analytics, and the power of Big Data – but what do you actually do with it? Big Data and Analytics for Insurers answers your questions in real, everyday business terms, tailored specifically to the insurance industry's unique needs, challenges, and targets.
| Author | : Gareth W. Peters |
| Publisher | : John Wiley & Sons |
| Total Pages | : 667 |
| Release | : 2015-05-26 |
| Genre | : Mathematics |
| ISBN | : 1118909534 |
ADVANCES IN HEAVY TAILED RISK MODELING A cutting-edge guide for the theories, applications, and statistical methodologies essential to heavy tailed risk modeling Focusing on the quantitative aspects of heavy tailed loss processes in operational risk and relevant insurance analytics, Advances in Heavy Tailed Risk Modeling: A Handbook of Operational Risk presents comprehensive coverage of the latest research on the theories and applications in risk measurement and modeling techniques. Featuring a unique balance of mathematical and statistical perspectives, the handbook begins by introducing the motivation for heavy tailed risk processes. A companion with Fundamental Aspects of Operational Risk and Insurance Analytics: A Handbook of Operational Risk, the handbook provides a complete framework for all aspects of operational risk management and includes: Clear coverage on advanced topics such as splice loss models, extreme value theory, heavy tailed closed form loss distribution approach models, flexible heavy tailed risk models, risk measures, and higher order asymptotic approximations of risk measures for capital estimation An exploration of the characterization and estimation of risk and insurance modeling, which includes sub-exponential models, alpha-stable models, and tempered alpha stable models An extended discussion of the core concepts of risk measurement and capital estimation as well as the details on numerical approaches to evaluation of heavy tailed loss process model capital estimates Numerous detailed examples of real-world methods and practices of operational risk modeling used by both financial and non-financial institutions Advances in Heavy Tailed Risk Modeling: A Handbook of Operational Risk is an excellent reference for risk management practitioners, quantitative analysts, financial engineers, and risk managers. The handbook is also useful for graduate-level courses on heavy tailed processes, advanced risk management, and actuarial science.
| Author | : Harold Kent Baker |
| Publisher | : Oxford University Press, USA |
| Total Pages | : 709 |
| Release | : 2015 |
| Genre | : Business & Economics |
| ISBN | : 0199331960 |
Investment Risk Management provides an overview of developments in risk management and a synthesis of research on the subject. The chapters examine ways to alter exposures through measuring and managing risk exposures and provide an understanding of the latest strategies and trends within risk management.
| Author | : David Procházka |
| Publisher | : Springer Nature |
| Total Pages | : 368 |
| Release | : 2021-02-05 |
| Genre | : Business & Economics |
| ISBN | : 3030552772 |
This book explores current digitalization issues in finance and accounting with particular focus on emerging and transitioning markets. It features models, empirical studies and cases studies on topics such as Fintech, blockchain technology, financing renewable energy, and XBRL usage from sectors such health care, pharmacology, transportation, and education. Such a complex view of current economic phenomena makes the volume attractive not only for academia, but also for regulators and policy-makers, when deliberating the potential outcome of competing regulatory mechanisms.
| Author | : Paola Leone |
| Publisher | : Springer |
| Total Pages | : 225 |
| Release | : 2017-12-26 |
| Genre | : Business & Economics |
| ISBN | : 3319694103 |
This book covers Operational Risk Management (ORM), in the current context, and its new role in the risk management field. The concept of operational risk is subject to a wide discussion also in the field of ORM’s literature, which has increased throughout the years. By analyzing different methodologies that try to integrate qualitative and quantitative data or different measurement approaches, the authors explore the methodological framework, the assumptions, statistical tool, and the main results of an operational risk model projected by intermediaries. A guide for academics and students, the book also discusses the avenue of mitigation acts, suggested by the main results of the methodologies applied. The book will appeal to students, academics, and financial supervisory and regulatory authorities.
