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Web Session "An Introduction to Economic Scenario
Generators and their Validation" on 14/15 March 2022
The Economic Scenario Generators are at the core of stochastic
models used by insurance companies. The applications of stochastic
models are very diverse and include such applications as economic
capital under Solvency II, ALM projections, dynamic hedging etc.
All these applications impose different requirements upon the
generation and the validation of economic scenarios.
In the web session, we begin by discussing the principles of
risk-neutral modelling, where we are going to focus on equity
modelling and interest rate modelling. We proceed by discussing
real-world capital market modelling. Finally, we talk about ESG
validation aspects relevant for Solvency 2 work and other
applications.
further details
Web Session "Practical Machine Learning Applications in
Finance and Insurance" on 16 March 2022
The objective of this web session is that participants should
become familiar with machine learning techniques used to solve
practical problems in finance, banking and insurance. To achieve
this we begin from the scratch and introduce machine learning
workflows and techniques step by step: To start with, we give an
overview of this interesting field with the primary focus on
several techniques such as neural networks, among others. The key
for an efficient application is the way of training machine
learning algorithms and thus we focus our attention on this
optimization as well. We strengthen our learned knowledge by
focusing on several case studies: We consider an example within the
Solvency II context such as implementing an internal model to
calculate the Solvency Capital Requirement (SCR), but also
applications to financial market such as option pricing by Monte
Carlo methods or trading strategies. During our complete web
session we learn how the introduced algorithms can be implemented
so that the participants are able to build up their own use cases
in Python at the end.
further details
Web Session "Mathematical Modelling for Actuaries" on 6/7
April 2022
Actuaries are very experienced in modelling financial risks either
stemming from population dynamics or from random events.
Probability theory and statistics is their daily bread. But there
are many other phenomena out in the world without having a direct
financial impact but should be understood by actuaries as well.
This web session is about models which typically are not covered in
full by actuarial exams, but which could bring better insights to
risks actuaries have to price. We will show very general approaches
to set up models with applications from many different areas,
whether it is medicine, construction, meteorology, biology or
others. Of course, this web session can only be seen as an
introduction into modelling and cannot cover all interesting
models, but it should enable participants to find more in
literature or develop their own ideas.
The purpose of the online training is to open the mind for
problems which are by nature not actuarial but are very much linked
to typical actuarial questions. It should enable actuaries and risk
managers to think out of the box and find new ways to solve their
challenges.
This online training is very interactive, participants are
required to participate in several breakout sessions.
further details
Web Session "Understanding the Performance of an Insurance
Company: An Introduction" on 2-5 May 2022
Due to the inversion of the production cycle, the insurance
business is very different from other traditional industries.
Understanding, measuring and managing the performance of insurance
companies is difficult due to the specific risks insurance
companies must cover. It is therefore essential that you, as
employee of the insurance sector, understand how your company is
functioning, how its activity is measured via the balance sheet and
the P&L, what are the main regulations influencing this
measure, which indicators are used to assess the performance and
what levers can improve this performance.
The aim of this workshop is to
- Present the functioning of an insurance
company and the insurance and financial products it manages
- Explain how to read and understand the
different elements of an insurance balance sheet and P&L
- Compute performance indicators used in
different regulatory frameworks (Local GAAP, Solvency 2)
- Understand the impact of pricing &
portfolio management, risk mitigation (reinsurance) and ALM on the
performance
We will cover life as well as non-life insurance. Health
insurance will not be specifically covered.
further details
Web Session "Understanding IFRS 17" on 19/20 May
2022
The goal of the two-day web session is to provide participants
with a comprehensive introduction to the new measurement,
presentation and disclosure guidance for insurance contracts. It
will cover life, health and non-life business, including the
special guidance on direct participating contracts and shorter term
non-life contracts and give useful examples.
In the web session, we will first shed a light on the context of
accounting for insurance contracts within the IFRS 17 framework. We
will present and discuss the general concepts behind the new model
and refer to the application of valuation models like the Variable
Fee Approach (VFA) and the Premium Allocation Approach (PAA). The
web session will proceed with a discussion of topics specific to
individual lines of business (highlighting topics still under
discussion) and summarize potential approaches and solutions. We
will close with an overview of methodical hot topics relevant for
technical implementation seen in various European markets, share
emerging market views and discuss these with the
participants.
Overall, the goal is to enable participants to understand the
standard and help transferring the requirements into your specific
situation. It is thus intended to prepare participants for model
development, implementation, testing, reviewing and consulting with
management, accounting and auditors.
further details
Web Session "Macro-Level Actuarial Reserving Models" on
20/21 October 2022
Over time, the understanding of all the assumptions behind the
typically used reserving models can have grown a bit stale, and
more recent developments might not have percolated all the way to
the day-to-day practice. This web session will help the
participants to overcome this.
The most widely used deterministic macro-level models, such as the
Chain Ladder and the Bornhuetter-Ferguson model, will be discussed
in full detail during this web session, but also stochastic
macro-level models, such as the OverDispersed Poisson model or ODP
model for example, will be covered. This entails a proper freshing
up of the underlying assumptions and how the model is estimated,
but also checks on determining if the chosen model is appropriate
for the data at hand, and under which circumstances one should go
for one type of macro-level model or the other.
In this web training a detailed overview is provided of the
aforementioned models and during the practical sessions, R code is
provided on how to implement most of the discussed topics, hereby
rendering the participants completely autonomous after the
webinar.
During the web session however, even if practical sessions will be
organized, the main focus will be on the theory.
further details
Web Session "Deep Learning with a Focus on Text Analysis"
on 24/25 November 2022
In computational science, deep learning probably is one of the
most heralded techniques of present time and recent history, mainly
due to its versatility and impressive achievements likewise.
Indeed, applications of deep learning range from beating the
(human) world champion of the highly complicated Go game to the
promise of deploying self-driving cars in the near future, on a
large scale and all over the world.
Deep learning (DL) pertains to the field of artificial
intelligence and is great at extracting and mastering the often
highly non-linear patterns of a given process, whatever this
process might be. The only main requirement is the availability of
a large amount of data that describes the behaviour of the process
under different conditions and a truckload of computational power.
However, since the price of data storage and the effort of sampling
data has dropped dramatically over the last years, and since
Moore's law on the increase of computational power does even
nowadays not show any signs of a slowdown, fitting deep learning
models that are able to produce extremely useful predictions are a
reality and this already for some years now.
In other words, the time is high to also deploy this amazing
technology in the insurance industry! However, the methodological
framework that underlies this amazing technology is somewhat
different from the statistical one that we've all grown accustomed
to (mainly through our general love for GLM models), and the
computational horsepower, needed to merely fit these models, is of
an order of magnitude higher than the one needed to fit the
classical statistical models.
further details
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