Cookies must be enabled to use this web application.

To allow this site to use cookies, use the steps that apply to your browser below. If your browser is not listed below, or if you have any questions regarding this site, please contact us.

Microsoft Internet Explorer
  • 1. Select "Internet Options" from the Tools menu.
  • 2. Click on the "Privacy" tab.
  • 3. Click the "Default" button.
  • 4. Click "OK" to save changes.
Chrome Chrome
  • 1. Click the "Spanner" icon in the top right of the browser.
  • 2. Click Options and change to the "Under the Hood" tab.
  • 3. Scroll down until you see "Cookie settings:".
  • 4. Set this to "Allow all cookies".
Firefox Firefox
  • 1. Go to the "Tools" menu and select "Options".
  • 2. Click the "Privacy" icon on the top of the window.
  • 3. Click on the "Cookies" tab.
  • 4. Check the box corresponding to "Allow sites to set Cookies.
  • 5. Click "OK" to save changes.
Opera Opera
  • 1. Click on the "Tools" menu and then click Preferences.
  • 2. Change to the Advanced tab, and to the cookie section.
  • 3. Select "Accept cookies only from the site I visit" or "Accept cookies".
  • 4. Ensure "Delete new cookies when exiting Opera" is not ticked.
  • 5. Click OK.
Netscape and Mozilla Suite Netscape and Mozilla Suite
  • 1. Select "Preferences" from the Edit menu.
  • 2. Click on the arrow next to "Privacy & Security".
  • 3. Under "Privacy & Security" select "Cookies".
  • 4. Select "Enable all cookies".
  • 5. Click "OK" to save changes.
Safari Safari
  • 1. Click on the "Cog" icon in Safari.
  • 2. Click Preferences.
  • 3. Change to the Security tab.
  • 4. Select "Only from sites I visit" or "Allow".
  • 5. Close the dialog using the cross.
Book Image Not Available Book Image Not Available

See inside

Book details
  • Genre:BUSINESS & ECONOMICS
  • SubGenre:Business Mathematics
  • Language:English
  • Series title:Future of ERM
  • Series Number:2
  • Pages:196
  • eBook ISBN:9781667803326

Risk Intelligence

How Artificial Intelligence can transform Risk Management

by Gregory M. Carroll View author's profile page

Book Image Not Available Book Image Not Available

See inside

Overview

As an executive’s guide, “Risk Intelligence” walks the fine line between AI technical and ERM strategy. Using everyday language, it lays out how to exploit the latest advances in machine learning and related AI technologies, as a toolkit to navigate uncertainty.

Risk Intelligence provides engaging and practical advice on solving ISO 31000 and COSO ERM’s biggest challenges. Covering the 7 risk domains of financial risk, strategic risk, third-party risk, operational risk, security risk, market risk, and compliance risk, it maps out how senior managers can use advanced technology to navigate the volatile and disruptive post-COVID business world, and turn risk management into a tool for growth and exploiting opportunities.

This is essential reading for executive, CROs, and GRC practitioners wanting to understand the broader organisational context of deep learning and implementing true risk-based decision-making. With an executive’s perspective on policy and solutions, it is also the ideal text for upper-level undergraduate, postgraduate and MBA students.

Included in Risk Intelligence is how to apply Machine Learning to manage:

  • Strategic Risk with Bayesian Game Theory
  • Financial Risk with Time Series Forecasting 
  • Security Risk and Blockchain Trust Systems
  • OpRisk with Behavioural Analysis
  • Third Party Risk with Knowledge Graphs
  • Compliance Risk with NLP Text Analytics
  • Market Risk with Big Data & Clustering
  • Virtual & Augmented Reality for Training
  • Bayesian Decision Networks for risk-based decision-making


Description
To become relevant, Risk Management must move from subjective awareness to a practical toolkit for operational managers to make informed decisions. Since Napoleon, the military has relied on such support. They call it "Military Intelligence", defined as: "a military discipline that uses information collection and analysis approaches to provide guidance and direction to assist commanders in their decisions." In the same vein, business requires Risk Intelligence. Artificial Intelligence (AI) can advise strategy-makers on likely scenarios and influences, create networks to monitor changes in the environment, and provide rank and file with the collateral they need to achieve objectives. Given the right set of tools, Risk Management teams can provide Risk Intelligence to support your commanders in the field. Covering the 7 risk domains of financial risk, strategic risk, third-party risk, operational risk, security risk, market risk, and compliance risk, Risk Intelligence shows how to apply Machine Learning to manage: * Strategic Risk with Bayesian Game Theory * Financial Risk with Time Series Forecasting * Security Risk and Blockchain Trust Systems * OpRisk with Behavioural Analysis * Third Party Risk with Knowledge Graphs * Compliance Risk with NLP Text Analytics * Market Risk with Big Data & Clustering * Virtual & Augmented Reality for Training * Bayesian Decision Networks for risk-based decision-making
About the author
Gregory M. Carroll is an evangelist for AI based Risk Management. He has extensive experience in Enterprise Risk Management (ERM), IT, and Artificial Intelligence (AI) systems in mission critical environments. Greg's has worked with the likes of Aust. Dept. of Defence and Victorian Infectious Diseases Labs. Author of "Mastering 21st century Enterprise Risk Management", Greg is a strong advocate for applying Bayesian techniques and disruptive technologies to Risk Management. As founder and Director of Fast Track (Aust), Greg has implemented both Machine Learning and Risk Management solutions for multinationals like Motorola and Serco. This includes pro-active AI and risk analytics solutions using deep learning to classify risk, random forests for scenario analysis and Bayesian networks for risk aggregation. Since doing a Graduate Diploma in Computer Simulation (Operations Research) at Swinburne University, he has been heavily involved with computer-based decision tools. Greg also has a Certificate in Machine Learning from Stanford University, in Data Science from the University of Michigan and is a Microsoft MCP full stack developer.
Thanks for submitting a review!

Your review will need to be approved by the author before being posted.

See Inside
Front Cover

Loading book cover...

Book Image Not Available Book Image Not Available
Session Expiration WarningYour session is due to expire.

Your online session is due to expire shortly.
Would you like to extend your session and remain logged in?

Session Expired

Your session has expired.We're sorry, but your online session has expired.
Please log back into your account to continue.

This site uses cookies. Continuing to use this site without changing your cookie settings means that you consent to those cookies to enhance site navigation and the overall user experience. Learn more about our privacy policy or learn more about how to turn off cookies.