,Contents
Acknowledgments
Chapter 1Introduction
Chapter 2Introduction to Artificial Intelligence
Chapter 3Introduction to Risk
Chapter 4Knowledge Base
Chapter 5AI Solutions for Risk
Chapter 6Identify Risk or Threat Model
Chapter 7Risk Categorization/Classification Model
Chapter 8Predicting Risk Impact Score Model
Chapter 9Risk Probability Occurrence Model
Chapter 10Risk Priority Model
Chapter 11Conclusion
CHAPTER 1
Introduction
Target audience
What you can get from this book?
What this book covers
This book’s mind map
Organization of chapters
Introduction to Artificial Intelligence (AI)
Introduction to Risk
Introduction to the AI Knowledge Base
Business Use Cases
AI Solutions for Risk
Conclusion
References
Chapter Outline
, Book Introduction
Organization of the Book
Chapter Introduction
Key Learning Points
Learn and understand: introduction
Target Audience
This book mainly focuses on artificial intelligence (AI) and how managers can apply AI to risk
management. This book follows current trends in AI in the branch of Natural Language Processing,
Natural Language Question and Answering System of AI, Conversational AI in risk domains, AI
supporting drones, AI cybersecurity, Internet of Things (IoT) devices, and use cases.
Each applicable AI topic targets:
Corporate top executives, founders, Chief Technology Officers, Chief Information
Officers, Chief Data Officers, Chief Security Officers, Chief Risk Officers, data scientists,
data architects, AI designers, AI engineers, project managers, and consultants to understand
how to manage risk using AI.
Students, teachers, and developers will find this book useful and practical. It will
provide an overview of many AI components, and introduce how it can be used in
corporate environments, start-ups, large-, medium-, and small-sized companies.
Anybody who strives to understand how AI can be used for risk.
What Can You Get From This Book?
Understand and learn about AI and how to apply AI to risk.
Design and apply knowledge-based AI solutions to solve risk-related problems.
Architecting and designing AI applied systems that mostly rely on the following:
Subject Matter Experts. Those with a practical view of how solutions can
be used, not just developed. Here, risk provides an example using case studies in
the book.
Appropriate applied mathematics and algorithms are used in the book. Do
not skip the mathematical equations if you have the need to study them. It is
important to note that AI relies heavily on mathematics.
Applied physics and usage into hardware systems and futuristic approaches
from quantum computers to parallel processing of networks in quantum computer
handlings. AI is still evolving with many new areas of possible opportunities. Give
your full attention to new concepts and applied creative ideas in the Futuristic AI
chapter.
Decision theory, decision-making process, the Markov Decision Process algorithm.
What This Book Covers
, This book covers mainly an introduction to AI and how it is applied in corporations, start-ups,
large-, medium-, and small-sized companies, to help automate the tedious jobs of mitigating risk.
This book will help those in organizations’ working environment (as a resource), applying and
automating AI and ML to help human experts.
How to get true value from AI?
What are the visionary business use cases for AI?
How do I identify the best business case to adopt AI and evaluate opportunities?
Should I build or buy an AI platform?
How do I find and recruit top AI talent for my enterprise?
How will I bring AI into my business to increase revenue or decrease costs?
How can I facilitate AI adoption in my organization?
Especially when dealing with data that include data collection, data preparation, data
transformation, securing the data, using the data to align organizational AI, use cases, and much
more. Figure 1.1 provides a mind map to give the reader an idea of what is covered in this book
and the organization of the chapters.
Acknowledgments
Chapter 1Introduction
Chapter 2Introduction to Artificial Intelligence
Chapter 3Introduction to Risk
Chapter 4Knowledge Base
Chapter 5AI Solutions for Risk
Chapter 6Identify Risk or Threat Model
Chapter 7Risk Categorization/Classification Model
Chapter 8Predicting Risk Impact Score Model
Chapter 9Risk Probability Occurrence Model
Chapter 10Risk Priority Model
Chapter 11Conclusion
CHAPTER 1
Introduction
Target audience
What you can get from this book?
What this book covers
This book’s mind map
Organization of chapters
Introduction to Artificial Intelligence (AI)
Introduction to Risk
Introduction to the AI Knowledge Base
Business Use Cases
AI Solutions for Risk
Conclusion
References
Chapter Outline
, Book Introduction
Organization of the Book
Chapter Introduction
Key Learning Points
Learn and understand: introduction
Target Audience
This book mainly focuses on artificial intelligence (AI) and how managers can apply AI to risk
management. This book follows current trends in AI in the branch of Natural Language Processing,
Natural Language Question and Answering System of AI, Conversational AI in risk domains, AI
supporting drones, AI cybersecurity, Internet of Things (IoT) devices, and use cases.
Each applicable AI topic targets:
Corporate top executives, founders, Chief Technology Officers, Chief Information
Officers, Chief Data Officers, Chief Security Officers, Chief Risk Officers, data scientists,
data architects, AI designers, AI engineers, project managers, and consultants to understand
how to manage risk using AI.
Students, teachers, and developers will find this book useful and practical. It will
provide an overview of many AI components, and introduce how it can be used in
corporate environments, start-ups, large-, medium-, and small-sized companies.
Anybody who strives to understand how AI can be used for risk.
What Can You Get From This Book?
Understand and learn about AI and how to apply AI to risk.
Design and apply knowledge-based AI solutions to solve risk-related problems.
Architecting and designing AI applied systems that mostly rely on the following:
Subject Matter Experts. Those with a practical view of how solutions can
be used, not just developed. Here, risk provides an example using case studies in
the book.
Appropriate applied mathematics and algorithms are used in the book. Do
not skip the mathematical equations if you have the need to study them. It is
important to note that AI relies heavily on mathematics.
Applied physics and usage into hardware systems and futuristic approaches
from quantum computers to parallel processing of networks in quantum computer
handlings. AI is still evolving with many new areas of possible opportunities. Give
your full attention to new concepts and applied creative ideas in the Futuristic AI
chapter.
Decision theory, decision-making process, the Markov Decision Process algorithm.
What This Book Covers
, This book covers mainly an introduction to AI and how it is applied in corporations, start-ups,
large-, medium-, and small-sized companies, to help automate the tedious jobs of mitigating risk.
This book will help those in organizations’ working environment (as a resource), applying and
automating AI and ML to help human experts.
How to get true value from AI?
What are the visionary business use cases for AI?
How do I identify the best business case to adopt AI and evaluate opportunities?
Should I build or buy an AI platform?
How do I find and recruit top AI talent for my enterprise?
How will I bring AI into my business to increase revenue or decrease costs?
How can I facilitate AI adoption in my organization?
Especially when dealing with data that include data collection, data preparation, data
transformation, securing the data, using the data to align organizational AI, use cases, and much
more. Figure 1.1 provides a mind map to give the reader an idea of what is covered in this book
and the organization of the chapters.
