Operational Risk Management in Banks and Idiosyncratic Loss Theory: A Leadership Perspective offers consensus considerations that could bolster effective risk management practices in enterprise-wide risk, thereby helping to control fraud and go beyond the minimum risk assessment requirements set forth by the banking regulators.
How to apply operational risk theory to real-life banking data Modelling Operational and Reputational Risks shows practitioners the best models to use in a given situation, according to the type of risk an organization is facing. Based on extensive applied research on operational risk models using real bank datasets, it offers a wide range of various testing models and fitting techniques for financial practitioners. With this book, professionals will have a foundation for measuring and predicting these important intangibles. Aldo Soprano (Madrid, Spain) is Group Head of operational risk management at UniCredit Group.
Building upon the seminal work established in the first best-selling edition, this fully revised multi-contributor title brings you right up-to-date on all the latest issues and developments in the area of operational risk management and the regulatory environment.
This book focuses on several topical issues related to the operational risk management in bank: regulation, organisation and strategy. It analyses the connections between the different key-players involved in the operational risk process and the most relevant implications, both operational and strategic, arising from the implementation of the prudential framework.
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.
Implement next-generation techniques-before disaster strikes—and improve operation risk management "The recent global economic crisis has brought home the need for realistic operational risk management as an important element of an organization's survival strategy in turbulent times. In Risk Management in Finance Dr. Tarantino and his coauthors provide an operational risk framework for the twenty-first-century organization by culling the state-of-the-arts knowledge on next-generation techniques in financial risk management to forestall major risk management failures. This book represents a landmark contribution in attempting to create a corporate world that is able to cope with major crisis. The book should be on the must read list for all those interested in reforming corporate governance." —Dr. Anwar Shah, Lead Economist and Program Leader, Governance, World Bank Institute "As operational risk management advances, interest in process-centered risk management has grown. This timely book presents a valuable overview of leading-edge theory and practice." —Simon Wills, Executive Director, Operational Riskdata eXchange Association (ORX), the world's largest banking association for sharing operational loss data
A comprehensive and innovative look at how to protect financial institutions from operational risks Operational risk is the risk associated with human error, systems failures, and inadequate controls and procedures in information systems or internal controls that will result in an unexpected loss. According to a recent survey, about seventy percent of banks consider operational risk as important as market or credit risks. Nearly a quarter of the same banks admit to operation-related losses of more than $1.6 million-many cases are so embarrassing that banks will not actually admit any error on their part. Firms are just beginning to develop their own operational risk management systems and they need guidance on how to do it. This book will help them identify, measure, and manage their operational risks. Christopher Marshall (Singapore) is Associate Director of the Center for Financial Engineering at the National University of Singapore. He has written numerous articles in Risk magazine and Harvard Business School cases.
"Managing Operational Risk" ist ein maßgeblicher Leitfaden zum Handling des operativen Risikos in Finanzinstituten. Als operatives Risiko bezeichnet man das Risiko für mögliche unerwartete Verluste, die auf Systemfehler, nicht adäquate interne Steuerungs- und Kontrollmechanismen sowie auf menschliches Versagen und höhere Gewalt zurückzuführen sind. Erläutert werden hier alle grundsätzlichen Fragen, angefangen bei einer ausführlichen Definition des Begriffs operatives Risiko, bis hin zu Entwurf und Implementierung anspruchsvoller Riskmanagement-Systeme. Darüber hinaus werden neueste Verfahren zur Erstellung von Computermodellen ebenso erörtert wie führende Methoden zur Integration von Legacy Systemen für die Bewertung und Erfassung operativer Risiken. "Managing Operational Risk" ist ein sachlich-prägnanter Ratgeber zur Bewertung und Minimierung des operativen Risikos. Geschrieben von Douglas Hoffman, einem international führenden Experten auf diesem Gebiet. Mit zahlreichen Fallstudien zu Spitzenfinanzinstitutionen weltweit.
A practical guide to identifying, analyzing and tackling operational risk in banks and financial institutions Created for banking and finance professionals with a desire to expand their management skill set, this book focuses on operational risk and operational risk events, as distinct from other types of functional risks. It was written by the experts at the world-renowned Hong Kong Institute of Bankers, an organization dedicated to providing the international banking community with education and training. Schools you in techniques for analyzing the operational risk exposure of banking institutions and assessing how operational risk impacts on other types of risk Provides expert guidance on how to design, plan and implement systems for operational risk management and quality control Describes a comprehensive approach to operational risk management that includes data collection, modeling and an overall risk management structure Shows you how to develop operational risk management solutions to help your company minimize losses without negatively impacting its ability to generate gains Offers expert guidance on various regulatory frameworks and how the latest Basel II and Basel III requirements impact a bank's operational risk management strategy and framework
Models and methods for operational risks assessment and mitigation are gaining importance in financial institutions, healthcare organizations, industry, businesses and organisations in general. This book introduces modern Operational Risk Management and describes how various data sources of different types, both numeric and semantic sources such as text can be integrated and analyzed. The book also demonstrates how Operational Risk Management is synergetic to other risk management activities such as Financial Risk Management and Safety Management. Operational Risk Management: a practical approach to intelligent data analysis provides practical and tested methodologies for combining structured and unstructured, semantic-based data, and numeric data, in Operational Risk Management (OpR) data analysis. Key Features: The book is presented in four parts: 1) Introduction to OpR Management, 2) Data for OpR Management, 3) OpR Analytics and 4) OpR Applications and its Integration with other Disciplines. Explores integration of semantic, unstructured textual data, in Operational Risk Management. Provides novel techniques for combining qualitative and quantitative information to assess risks and design mitigation strategies. Presents a comprehensive treatment of "near-misses" data and incidents in Operational Risk Management. Looks at case studies in the financial and industrial sector. Discusses application of ontology engineering to model knowledge used in Operational Risk Management. Many real life examples are presented, mostly based on the MUSING project co-funded by the EU FP6 Information Society Technology Programme. It provides a unique multidisciplinary perspective on the important and evolving topic of Operational Risk Management. The book will be useful to operational risk practitioners, risk managers in banks, hospitals and industry looking for modern approaches to risk management that combine an analysis of structured and unstructured data. The book will also benefit academics interested in research in this field, looking for techniques developed in response to real world problems.
