Artificial intelligence for risk management / Archie Addo, Srini Centhala, and Muthu Shanmugam. [electronic resource]
Material type:![Text](/opac-tmpl/lib/famfamfam/BK.png)
- text
- computer
- online resource
- 9781949443523
- Q335
- COPYRIGHT NOT covered - Click this link to request copyright permission: https://lib.ciu.edu/copyright-request-form
Item type | Current library | Collection | Call number | URL | Status | Date due | Barcode | |
---|---|---|---|---|---|---|---|---|
Online Book | G. Allen Fleece Library | Non-fiction | Q335 (Browse shelf(Opens below)) | Link to resource | Available | 9781949443523 |
Chapter 1. Introduction -- Chapter 2. Introduction to artificial intelligence -- Chapter 3. Introduction to risk -- Chapter 4. Knowledge base -- Chapter 5. AI solutions for risk -- Chapter 6. Identify risk or treat model -- Chapter 7. Risk categorization/classification model -- Chapter 8. Predicting risk impact score model -- Chapter 9. Risk probability occurrence model -- Chapter 10. Risk priority model -- Chapter 11. Conclusion.
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Artificial Intelligence (AI) for risk management is about using AI to manage risk in the corporate environment. The content of this work focuses on concepts, principles, and practical applications that are relevant to the corporate and technology environments. The authors introduce AI and discuss the different types, capabilities, and purposes--including challenges. With AI also comes risk. This book defines risk, provides examples, and includes information on the risk-management process. Having a solid knowledge base for an AI project is key and this book will help readers define the knowledge base needed for an AI project by developing and identifying objectives of the risk-knowledge base and knowledge acquisition for risk. This book will help you become a contributor on an AI team and learn how to tell a compelling story with AI to drive business action on risk
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