Risk Intelligence (eBook)

How Artificial Intelligence can transform Risk Management

Gregory M. Carroll (Autor)

eBook Download: EPUB

2021 | 1. Auflage
196 Seiten
Bookbaby (Verlag)
978-1-6678-0332-6 (ISBN)

Infos

As an executive's guide, this book 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. This includes using Knowledge Graphs for supply chain risk, Blockchain to eliminate fraud, and Bayesian Game Theory modelling for strategic planning. 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. The book shares a wealth of learning and life experience gained from implementing artificial intelligence based solutions for enterprise risk management in Defence and mission critical industries. It is essential reading for 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 ideal text for upper-level undergraduate, postgraduate and MBA students.

---

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 "e;Military Intelligence"e;, defined as: "e;a military discipline that uses information collection and analysis approaches to provide guidance and direction to assist commanders in their decisions."e;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

Textauszug

0.1 Foreword

This book is not a training manual on how to build Artificial Intelligence (AI) models. It is intended as an executive’s guide to applying AI technologies to transform risk management into a proactive management tool for informed decision-making and exploiting opportunities.

It expands on book 1 - “Mastering 21st Century Enterprise Risk Management”, and assumes readers understand event driven and objective base risk management. This includes the use of scenario analysis, casual mapping, horizon scanning, and risk aggregation. If you are not comfortable with these techniques, I strongly suggest reading my previous book before proceeding. As an Executive’s Guide, it covers these topics at a high level, so it is an easy read.

AI, although a technical subject, it is not difficult to understand from an application and management perspective. I have taken the approach that the reader does not have prior technical IT or AI background or knowledge. Hence, I have used everyday language to explain the techniques and concepts.

The title refers to AI, but more accurately I am referring to the whole raft of disruptive technologies. This general term covers the swath of technologies that are changing the face of the world as we know it. From bitcoin to drone pizza delivery these new technologies are IT based, use an augmented intelligence, and are most likely “cloud” dependent. End-point delivery might be via a local hardware device, but the solutions rely on distributed or massive processing power facilitated by “the cloud”.

These disruptive technologies open a completely new level of ability to risk management for identifying, evaluating, and monitoring risk. Also for control and mitigation as well as training and reporting. My Top 10 Disruptive Technologies that will change Risk Management in the 2020s are:

1. Probabilistic Modelling – to mirror real-world uncertainty and aggregate the effects of risk on strategic objectives.

2. Knowledge Graphs – to map risk network relationships to identify and understand sources of risk.

3. Neural Networks (aka Deep Learning) - to classify risk, identify patterns in data and images, and recommend courses of action.

4. Big Data & Predictive Analytics - to build risk collateral, identify trends & evolving risk, anomaly detection, and threat management.

5. IoT – Intelligent Things - to monitor changes in environmental factors in real-time, and using streaming analytics to identify stress and internal risks.

6. Virtual & Augmented Reality - to gain a quantum leap in staff training, building a robust risk culture, and provide real-time expertise to critical tasks.

7. Natural Language Processing (NLP) - providing text analysis to identify regulatory compliance issues and sentiment analysis to monitor behaviour.

8. Robotic Automated Processes (RPA) – AI infused workflows to augment human processes integrating research and risk-based decision-making at the coalface.

9. Blockchain Distributed Trust Systems – that will transform everything from cybersecurity and supply chain risk to making individuals responsible for their carbon footprint.

10. Bayesian Decision Networks – applying expert experience and probabilistic modelling to risk scenarios to identify the most likely outcome of complex events.

These are just some of the AI-based techniques that will transform ERM from today’s mystical based approach of coloured heat maps and the risk matrix. In its place will be a real value-adding management technique to drive growth and exploit opportunities.

This book builds on my 10 years of providing AI embedded solutions in mission critical risk and compliance. I have implemented pro-active AI risk analytics solutions using deep learning to identify and classify risk, random forests & regression models for scenario analysis, and Bayesian networks for aggregation of risk. These practices are in use with the likes of Victorian Infectious Diseases Reference Laboratories, Australian Quarantine Inspection Service and the Australian Department of Defence, all leaders in risk and compliance.

Gregory M Carroll – July 2021.

Risk Intelligence

To become relevant, Risk Management has to move from a 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”.

Military intelligence is 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, we can define Risk Intelligence as:

“a business discipline that uses information collection and analysis approaches to provide guidance and direction to assist managers in their decisions.”

Ask any manager what they need to make a decision and they will tell you they want the facts. Operational information interpreted with experience. Not lists of possible maybes, or a coloured thought-bubble matrix. AI technology can provide insightful recommendations based on historical data, and proven mathematical insights, i.e. situational awareness. A commander’s ability to adjust strategy in the heat of battle is the key to success. In today’s volatile business environment, managers need no less.

Gartner predicts that by the end of 2024, 75% of organisations will move from piloting AI to its mainstream adoption. This will drive a five times increase in streaming data and analytics infrastructures.

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.

The New Normal

While many are still debating what will be the new normal post COVID, I am prepared to go out on a limb and call it. Simply, it is a fluid operational environment, with continual disruption, requiring flexible and innovative response. And I mean normal. Identifying and handling issues will be a soft skill of future survivors. No stress involved, just part of their day to day work.

Solutions will not only need to be innovative, but composite. Multiple techniques and approaches taken simultaneously. New terms like psychometric and not so new ones like bionic, will become the standard vernacular in business engineering. From work-life balance and augmented reality, creative solutions require the combination of multiple disciplines social and business, people and process, psychological and technological, physical and digital, human and AI.

At the start of the industrial revolution, societal change was the biggest change and hardest to manage. Traditional jobs were lost and new ones were created yes, but the bigger problem came from the changes in values. Movement of people from the countryside to towns, land to money, working hours, and moving outdoors to indoors, resulted in changes in health and hygiene. This all took a toll on their mental and social wellbeing. Old habits die hard and tend to require generational change to assimilate the new norm. Instead of 100 years, COVID accelerated this to one, 2020.

We are now subject to the Chinese curse, “may you live in interesting times!” The change is now on us, and we have to take a serious look at changing our mindset or be left behind. As covered in my last book, Millennials won’t have a problem. They already existed in the new normal, to the point they don’t “get” the old world. Gen-Z are being educated in it, while Gen-Y will probably adapt fairly easily. But what of Gen-X, now forty-plus? They are in serious threat of being run over by the younger generation hungry for promotion and looking for the chance. Watch your backs.

In my 20s, I worked in the UK and initially couldn’t understand their business success, given their lack of motivation and drive. As an Australian, our competitive nature always has us looking for a better way of winning. An example of the very different approach to business of Aussies and Brits was a Brit advertising executive criticism: “You Australians don’t understand advertising; all you want to do is flog (sell) stuff!”, to which I replied, “isn’t that the purpose of advertising?”. Apparently, in the UK it was about building image and market position, i.e. the long game. I subsequently learned that the secret to British business success is planning and development. Action is just a medium. Like the tortoise and hare, their methodical approach might appear longer, but counterintuitively, arrives at a better outcome sooner.

In the UK, I had to adapt or get left behind. To quote Charles Darwin:

“It is not the strongest of the species that survives, nor the most intelligent, but the one most responsive to change.”

Artificial Intelligence (AI) is the electricity of the post-COVID world. It is the enabler of most disruptive technologies that are framing the new normal....

Produkt-Details

• Erscheint lt. Verlag: 30.9.2021
• Sprache: englisch
• Themenwelt: Mathematik / Informatik ► Mathematik
• ISBN-10: 1-6678-0332-8 / 1667803328
• ISBN-13: 978-1-6678-0332-6 / 9781667803326