EAA Newsletter: New Events Unveiled!

 

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EAA Newsletter
Stay Updated with our Latest Web Sessions

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Welcome to the latest edition of our newsletter! In this issue, we're thrilled to unveil our recently released EAA web sessions, a comprehensive collection tailored for actuaries:

  • Assets and Liabilities Management Part 1: Introduction,
  • Explainable AI for Actuaries: Concepts, Techniques, and Case Studies,
  • Discrimination-Free Pricing: of Limits & Possibilities,
  • Assets and Liabilities Management Part 2: Advanced,
  • Introduction to Natural Catastrophe Modelling,
  • Communication for Actuaries and
  • Emerging Risks: Statistical Analysis and Scenario Building.

We invite you to seize the opportunity to enrich your knowledge by participating in these upcoming web sessions. Be sure to keep an eye on our continually expanding lineup for 2024.

Dive into the content, and stay informed with EAA!

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Web Session 'Assets and Liabilities Management (Part 1: Introduction)'
on 16-18 September 2024

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For an insurance company, ensuring the proper coordination between assets and liabilities in order to achieve targeted financial objectives is of paramount interest. A strategy used to reach such objectives is "asset and liability management" (ALM in short). ALM can therefore be viewed as any ongoing process that defines, implements, and monitors financial strategies to manage assets and liabilities together.

In recent years, the modelling tools used in ALM strategies have become increasingly sophisticated and the technical aspects of current insurance regulation have increased. As a result, some ALM aspects have become more and more difficult to understand and master.

The aim of this training is to

  • Define what ALM is and describe the typical missions of an ALM department in an insurance company
  • Present the financial risks on which ALM classically focus as well as the requirements of the Solvency II regulation for insurance companies
  • Describe the essential quantitative ALM tools and methods used by insurance companies to evaluate and mitigate the risks
  • Illustrate the different concepts through numerical examples and case studies to make it practical and not just theoretical

This is the first of two ALM trainings. The second training 'Assets and Liabilities Management (Part 2: Advanced)' on 14-16 October 2024 must be booked separately (see below). The participants can follow a single part or both.

further details

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Web Session 'Explainable AI for Actuaries: Concepts, Techniques, and Case Studies'
on 19/20 September 2024

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The increasing use of artificial intelligence (AI) and machine learning (ML) in the insurance industry in general and in actuarial issues in particular presents both opportunities and risks. Acceptance of complex methods requires, among other things, a degree of transparency and explainability of the underlying models and the decisions based on them.

By the end of this web session, participants will leave with a toolkit of explainability techniques, an in-depth understanding of model interpretability, and the ability to use XAI approaches in practical actuarial applications.

Participants will also understand mathematical principles behind key XAI techniques, evaluate the strengths and limitations of XAI methods, run a machine learning workflow that incorporates XAI techniques, and analyse and interpret results in the context of actuarial cases.

further details

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Web Session 'Discrimination-Free Pricing: of Limits & Possibilities'
on 8 October 2024

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Not only upcoming regulation plays a role - fairness of treatment lies at the core of insurance in the first place. In the age of Machine Learning and Artificial Intelligence, analysis and, potentially, remedy, of direct and indirect discrimination in insurance decision making - most notably pricing - has become a more pronounced problem due to increased public interest. But in stark contrast to, say, chatbots or personal assistance systems, there are structural aspects preventing companies from creating and maintaining products that are comprehensively fair in all the relevant facets.

The purpose of this session is to introduce relevant concepts of pricing and discrimination therein as well as an overview of discrimination-reducing concepts from the literature. We will then draft some toy models, including generation of synthetic data with particular properties. Afterward, we will review limits and possibilities toward enabling (some kind of) less-discriminatory pricing.

further details

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Web Session 'Assets and Liabilities Management (Part 2: Advanced)'
on 14-16 October 2024

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The second part of 'Assets and Liabilities Management' is more advanced and intended for those wishing to gain more in-depth expertise on the topics. It includes some mathematical technicity, but nothing that goes further than a solid high school level.

This is the second of two ALM trainings. The first training 'Assets and Liabilities Management (Part 1: Introduction)' on 16-18 September 2024 must be booked separately (see above). The participants can follow a single part or both.

further details

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Web Session 'Introduction to Natural Catastrophe Modelling'
on 17 October 2024

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Natural Catastrophe Models are a key ingredient for the assessment of Nat Cat risk. Questions like “What losses do we expect from catastrophic events on average?” and “What losses do we need to expect in the worst case?” are becoming more and more relevant, in particular considering climate change. Natural Catastrophe Models try to answer these questions in a statistical sense, and have for many years now become an important tool for the assessment of (re-)insurance contracts. In this web session, we will give a basic introduction to Nat Cat Modelling and its applications.

During this web session, the basic components of a Nat Cat model will be explained: Exposure data, the hazard, vulnerabilities, and the financial model. Additionally, sources of uncertainty will be discussed together with methods for quantification. After the first part, we will build our own simple Nat Cat model in a hands-on case study. Lastly, we will look in more detail at the results a model can produce and how to use them for pricing in the reinsurance context.

further details

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Web Session 'Communication for Actuaries'
on 28-31 October 2024

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This course is tailor-made for actuaries and the situations that you encounter. It is an interactive training course that ensures that the theory is immediately applied through various exercises (e.g. exchanges in small groups, role-plays, discussions) that relate to terms or situations of your day-to-day work.

The course is designed to give you a solid foundation on the topic of communication and to practice what you learn so you can use the gained knowledge and confidence in areas that are relevant for your work. The last day offers you the opportunity to make a short presentation specific to your work for which you will be given individual feedback. At the end of the course, you will know exactly how to tackle your next communication challenge.

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The overall 12-hour course covers specific topics like:

  • Communication patterns/models, types of behavior/learning
  • Verbal, non-verbal and written communication skills
  • Virtual communication
  • Presentation (as if “on stage“ and “on screen”) skills
  • Discussion & Negotiation

The communication topics 9.1.1. to 9.1.8. of the AAE Core Syllabus are sufficiently to fully covered within this course.

further details

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Web Session 'Emerging Risks: Statistical Analysis and Scenario Building'
on 6/7 November 2024

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In a context of widespread instability, the actuarial analysis of emerging risks takes on particular importance to facilitate the adaptation of insurance to these profound changes. Whether it be old risks with poorly anticipated consequences (such as the epidemiological risk, as demonstrated by the recent Covid-19 crisis, whose consequences can significantly exceed purely healthcare boundaries), risks undergoing strong and worrying evolution (such as climate risk), or more recent risks (such as cyber risk), the task of actuaries is particularly delicate. The lack of data is notably a hindrance to a rigorous approach to these important questions. This session aims to lay the groundwork for a scientific approach to this problem and to introduce some tools for discussing the insurability of these new risks.

This session will notably have two main angles. Firstly, it will raise the question of data, their quality, and the necessary reliance on expert judgment, crucial for risks where experience is limited. Bayesian analysis notably allows for this integration, but does not exempt from a critical examination of the quality of expert data, and we will thus present some methods to attempt to evaluate it.

Secondly, we will examine the shift from a "historical data" approach to a "scenario-based" approach. Because while the notion of scenario allows for anticipating situations never encountered before, their design must adhere to scientific standards to avoid being purely speculative.

A simplified illustration of these issues will be provided during the training. An R notebook will allow participants to follow and adapt the implementation without needing an in-depth knowledge of the software.

further details

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Further Trainings in 2024

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21 March 2024
SII-Review: From Commission’s Request to an Adapted Framework
further details

22 March 2024
Data Science for Executives
further details

10-16 April 2024
Understanding the Performance of an Insurance Company: An Introduction
further details

12 Apr 2024
IFRS 17: Special Issues with Reinsurance Contracts
further details

18-20 April 2024
in Vienna
Actuarial Data Science - Basic
further details

30 Apr 2024
Climate Risk Stress Testing for Physical Risk from Natural Hazards
further details

6 May 2024
Emerging Risks
further details

14 May 2024
EAA e-Conference on Data Science & Data Ethics
further details


... and a lot more! Explore our website for more information.

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actuarial-academy.com

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