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Risk Modeling - Practical Applications of Artificial Intelligence, Machine Learning, and Deep Learning (Hardcover)
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Risk Modeling - Practical Applications of Artificial Intelligence, Machine Learning, and Deep Learning (Hardcover)
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A wide-ranging overview of the use of machine learning and AI
techniques in financial risk management, including practical advice
for implementation Risk Modeling: Practical Applications of
Artificial Intelligence, Machine Learning, and Deep Learning
introduces readers to the use of innovative AI technologies for
forecasting and evaluating financial risks. Providing up-to-date
coverage of the practical application of current modelling
techniques in risk management, this real-world guide also explores
new opportunities and challenges associated with implementing
machine learning and artificial intelligence (AI) into the risk
management process. Authors Terisa Roberts and Stephen Tonna
provide readers with a clear understanding about the strengths and
weaknesses of machine learning and AI while explaining how they can
be applied to both everyday risk management problems and to
evaluate the financial impact of extreme events such as global
pandemics and changes in climate. Throughout the text, the authors
clarify misconceptions about the use of machine learning and AI
techniques using clear explanations while offering step-by-step
advice for implementing the technologies into an organization's
risk management model governance framework. This authoritative
volume: Highlights the use of machine learning and AI in
identifying procedures for avoiding or minimizing financial risk
Discusses practical tools for assessing bias and interpretability
of resultant models developed with machine learning algorithms and
techniques Covers the basic principles and nuances of feature
engineering and common machine learning algorithms Illustrates how
risk modeling is incorporating machine learning and AI techniques
to rapidly consume complex data and address current gaps in the
end-to-end modelling lifecycle Explains how proprietary software
and open-source languages can be combined to deliver the best of
both worlds: for risk models and risk practitioners Risk Modeling:
Practical Applications of Artificial Intelligence, Machine
Learning, and Deep Learning is an invaluable guide for CEOs, CROs,
CFOs, risk managers, business managers, and other professionals
working in risk management.
General
Imprint: |
John Wiley & Sons
|
Country of origin: |
United States |
Release date: |
September 2022 |
First published: |
2022 |
Authors: |
T. Roberts
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Dimensions: |
242 x 158 x 18mm (L x W x T) |
Format: |
Hardcover
|
Pages: |
208 |
ISBN-13: |
978-1-119-82493-0 |
Categories: |
Books >
Business & Economics >
Finance & accounting >
General
|
LSN: |
1-119-82493-1 |
Barcode: |
9781119824930 |
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