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Back to Academy:
Elevate Your Actuarial Expertise |
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Dear Sir or Madam,
After a refreshing summer break, the European Actuarial Academy
(EAA) is back with renewed energy and a lineup of high-impact
training sessions aimed at enhancing your professional growth.
We've curated a diverse array of learning opportunities to keep you
ahead in the ever-evolving actuarial landscape.
We're excited to present our first five training sessions
following our summer break. These offerings include both web
sessions and on-site seminars, each reflecting the latest industry
trends and insights. Whether you're looking to broaden your
knowledge, sharpen your skills, or stay informed on the latest
developments, there's something for everyone.
This autumn is the perfect time to deepen your expertise and meet
the evolving demands of the actuarial profession. Explore our
upcoming training sessions and secure your spot today! |
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CERA, Module B:
Taxonomy, Modelling and Mitigation of Risks |
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This web session is
one part in a course that consists of four modules. They can be
booked as a whole series to fulfil the requirements for receiving
the CERA designation, or individually as CPD training. Written
exams on the course are offered subsequently.
The web seminar focuses on quantitative analyses of financial and
non-financial risks of an insurance company and the effect and
possible applications of risk mitigation techniques and has been
designed for experienced practitioners who use model results in
practice and seek guidance for management decisions. Therefore, the
focus is not on technical details but on the understanding of risk
models and their results, and on the derivation of management
actions. |
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| Actuarial Data Science - Advanced |
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This is part two of
four courses (seminar and exam) to obtain the additional title
Certified Actuarial Data Scientist by the AVÖ and/or DAV.
Participants who do not hold an AVÖ or DAV membership have also the
opportunity to obtain a newly established EAA Certificate in Actuarial Data
Science by taking part in all four modules and the
corresponding exams.
Based on the building blocks known from Basic, we want to deepen
some topics and present further important topics from the field of
Actuarial Data Science. In this three-day training, we cover a wide
range of topics. This includes an advanced introduction to the
concepts and terms of artificial intelligence, modern data
management concepts (with a special look at insurance companies),
aspects of data protection and the mathematical and statistical
concepts of data mining. On our way, we touch different use cases
in the actuarial environment. To this end, we provide a brief
insight into the widely used language Python. The training rounds
off with principles for the ethical handling of artificial
intelligence in the insurance environment. |
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Assets and Liabilities Management
(Part 1: Introduction) |
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This web session is
the first part of a two-part ALM training. The first part provides
an introduction to main concepts of ALM and is therefore
particularly suited for participants coming from different
departments (for instance, people dealing with own risk solvency
assessment techniques or enterprise risk management) and wanting to
develop a broader view on what ALM is and how it works. It is also
well suited for newcomers or people wanting to refresh their mind
on these concepts. Note that the training is not limited to people
working in ALM or treasury departments but is also adapted to other
departments.
The second part (which is to be booked separately) 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.
The participants can follow a single part or both. |
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Explainable AI for Actuaries:
Concepts, Techniques and Case Studies |
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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 the seminar, 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. |
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Open Source Tools R and Python:
Extending the Toolbox of the Actuary |
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| 30 September - 1 October 2024 |
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Organised by the EAA
- European Actuarial Academy GmbH in cooperation with Česká
společnost aktuárů.
The goal of this two-day training is to introduce the participants
to both open source ecosystems and to get a good understanding of
both languages. However, since both ecosystems are way too vast to
be covered in merely two days, the participants will be asked to go
through the basics of both languages themselves, prior to the
seminar. During the first three hours of the seminar, these basics
which will be shortly revised, but at a higher pace. In this way,
the presenters can focus more on examples and on providing more
hands-on experience to the participants. The course material,
containing the basics of both languages, will be provided by the
organizers several weeks before the beginning of the seminar, such
that the participants will have plenty of time to go through the
material at her/his ease. |
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| Explore
and Engage with EAA |
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