A Practical Guide to AI Risk Management (W3)

Learn how to manage risks associated with artificial intelligence (AI) in an actuarial context, with a focus on machine learning.

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Introduction

If you're looking for a practical guide to performing AI risk management, this course is ideal for you. The course offers a discussion of different guidelines for AI risk management, walking through explainability techniques, and recommending best practice. An individual subscription gives you 3 months’ online access to:

  • Course materials
  • Downloadable Notebooks with code and explanations
  • Option to ask tutors questions
  • Hands-on practical examples linked to actuarial work
  • On-demand access

As Well As

Our Industry and Actuartech Resource Libraries which feature curated additional content to assist you on your data science journey.

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Someone working on an online course at their desk.

Pick from any of our introductory or advanced courses with bespoke insurance and actuarial specific case studies.

Our platform is easy to use and offers detailed guides, with course content and downloadable Notebooks offering code and explanations, enabling you to apply data science hands-on.

We provide case studies and projects relevant to actuarial work, and based on relevant datasets provided. You have the option to interact and network with your peers.

Overview

With the use of examples, we introduce delegates to the new types of risks resulting from AI, with a focus on technical considerations, including interpretability, explainability, validation, and transparency. We provide examples to make sense of apparent ‘black box’ models; and ways to validate certain types of machine learning models.

We will present participants with pre-run models; based on publicly available data; and provide hands-on examples to interpret these models. Note that familiarity with Python, Jupyter Notebooks and the ability to code foundational Python is recommended as delegates will be guided through advanced techniques.

We will also explore industry examples of ethics, professionalism and regulatory principles within the context of AI, and provide delegates with curated resources and summarised regulatory requirements.

The main challenges actuaries are facing will be discussed, particularly as it relates to the use of AI for modelling and analytics. These themes include:

  • bias, fairness, and discrimination
  • individualisation of risk assessment
  • interpretability and explainability
  • transparency, reproducibility and replicability
  • validation and governance
  • lack of relevant skills
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An Introduction to AI Risk Management

Sign up for a free preview of this AI risk management course

Free Preview

Preview

£450 once-off with assignment (3-month access)

Enroll Today

£325 once-off (3-month access)

Enroll Today

Course Structure

In Chapter 1 we introduce the course and define AI within the context of actuarial work.

Chapter 2 discusses key concerns and considerations for AI risk management, and looks at practices to help manage the risks in machine learning investigations, including transparency, validation techniques, and explainability.

Chapter 3 outlines the regulatory journey of the use of AI by actuaries, focused on the UK, and considers global regulatory requirements for AI systems.

In Chapter 4 we summarise best practice for the use of AI in insurance and provide resources on the use of AI, with Chapter 5 providing an actuarial perspective on the current AI risk landscape.

Chapter 6 discusses some considerations regarding the use of large language models for actuarial work.

The Appendix contains the downloadable notebooks and an optional assignment, along with key course references.

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Who's this course suitable for?

This course is suitable for anyone with some familiarity with R and Python who would like to explore how AI risk can be managed within an actuarial context, including:

  • Individuals and teams who wish to learn how to manage AI risks.
  • Individuals and teams who wish to understand how AI risk management can enhance their operations, including improved interpretability and explainability.
  • Individuals and teams who wish to enhance the governance associated with their AI/ML projects.
  • Individuals and teams with some experience outside the AI/ML and/or actuarial business context and want to see how traditional and modern techniques can be applied within those contexts.

Why is this topic important?

AI is changing the actuarial operating model, as it holds the opportunity to improve current processes by implementing AI, particularly machine learning, techniques. There are a lot of benefits as implementation and good practices of these techniques can ensure reproducibility, code control, out of the box thinking, and sharing development in a transparent way. But this could only be achieved if it is delivered in a risk-controlled manner; risk management and risk management considerations has to keep up with the change in operations.

Short note to say really enjoyed today’s webinar. It had a very clear message. […] fully in agreement with the comments that it is imperative we maintain our professional and ethical stance at all times if we want to continue to be trusted and relied on.

Webinars

I just wanted to say what an interesting presentation that was. Thank you so much for taking the time to put this on for us, it is very much appreciated by all – especially the flexibility around hosting as a webinar instead of the original [in-person] format. It worked very well indeed!

Webinars

I think I’m [one of the first actuaries in my area] who are pointing towards Data Science, creating the new [role] of Actuarial data Scientist. For this reason i [sic] decided to follow a post graduate master in Business Intelligence and Big data analytics. I'm actively following your company and i [sic] think it is one of the best Actuarial consulting company [sic] who [sic] is pointing towards data Science!

Webinars

I love your videos - being free and accessible really helped me. The Q&A session was fantastic! It always comes down to execution and I feel this should always accompany your presentations - answering the question of how will your participants use what you give them. Keep up the great work!

Round Table

Thank you for having me along. I really found it the most motivating conversation I’ve had in a while, and made me think about what I’m trying to achieve within this area. We all need evenings like that to get some perspective on what we *think* is going on and what actually is. It was a very good evening.

Round Table

It was a really good introduction to Data Science and afterwards I felt that I now have a platform that I could use to further my understanding in this area.

Webinars

I am really happy to have been part of the talk. It was very insightful and please keep doing more of this. I am a data science student currently but I have an actuarial background. I worked in life insurance for about 5 months before resigning to do my masters in Data science so that I blend the actuarial world and Data science together. The talk gave me perspective. Even suggested some potential topics for my Thesis.

Webinars

Short note to say really enjoyed today’s webinar. It had a very clear message. […] fully in agreement with the comments that it is imperative we maintain our professional and ethical stance at all times if we want to continue to be trusted and relied on.

Webinars

I just wanted to say what an interesting presentation that was. Thank you so much for taking the time to put this on for us, it is very much appreciated by all – especially the flexibility around hosting as a webinar instead of the original [in-person] format. It worked very well indeed!

Webinars

I think I’m [one of the first actuaries in my area] who are pointing towards Data Science, creating the new [role] of Actuarial data Scientist. For this reason i [sic] decided to follow a post graduate master in Business Intelligence and Big data analytics. I'm actively following your company and i [sic] think it is one of the best Actuarial consulting company [sic] who [sic] is pointing towards data Science!

Webinars

I love your videos - being free and accessible really helped me. The Q&A session was fantastic! It always comes down to execution and I feel this should always accompany your presentations - answering the question of how will your participants use what you give them. Keep up the great work!

Round Table

Thank you for having me along. I really found it the most motivating conversation I’ve had in a while, and made me think about what I’m trying to achieve within this area. We all need evenings like that to get some perspective on what we *think* is going on and what actually is. It was a very good evening.

Round Table

It was a really good introduction to Data Science and afterwards I felt that I now have a platform that I could use to further my understanding in this area.

Webinars

I am really happy to have been part of the talk. It was very insightful and please keep doing more of this. I am a data science student currently but I have an actuarial background. I worked in life insurance for about 5 months before resigning to do my masters in Data science so that I blend the actuarial world and Data science together. The talk gave me perspective. Even suggested some potential topics for my Thesis.

Webinars
Get started

An Introduction to AI Risk Management

Sign up for a free preview of this AI risk management course

Free Preview

Preview

£450 once-off with assignment (3-month access)

Enroll Today

£325 once-off (3-month access)

Enroll Today

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