Books > Reference & Interdisciplinary > Communication studies > Data analysis
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Operational Risk Management - A Practical Approach to Intelligent Data Analysis (Hardcover)
Loot Price: R2,523
Discovery Miles 25 230
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Operational Risk Management - A Practical Approach to Intelligent Data Analysis (Hardcover)
Expected to ship within 12 - 17 working days
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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.
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