BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//AKTUARVEREINIGUNG ÖSTERREICHS (AVÖ) - ECPv6.16.2//NONSGML v1.0//EN
CALSCALE:GREGORIAN
METHOD:PUBLISH
X-ORIGINAL-URL:https://avoe.at
X-WR-CALDESC:Veranstaltungen für AKTUARVEREINIGUNG ÖSTERREICHS (AVÖ)
REFRESH-INTERVAL;VALUE=DURATION:PT1H
X-Robots-Tag:noindex
X-PUBLISHED-TTL:PT1H
BEGIN:VTIMEZONE
TZID:Europe/Vienna
BEGIN:DAYLIGHT
TZOFFSETFROM:+0100
TZOFFSETTO:+0200
TZNAME:CEST
DTSTART:20250330T010000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:+0200
TZOFFSETTO:+0100
TZNAME:CET
DTSTART:20251026T010000
END:STANDARD
BEGIN:DAYLIGHT
TZOFFSETFROM:+0100
TZOFFSETTO:+0200
TZNAME:CEST
DTSTART:20260329T010000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:+0200
TZOFFSETTO:+0100
TZNAME:CET
DTSTART:20261025T010000
END:STANDARD
BEGIN:DAYLIGHT
TZOFFSETFROM:+0100
TZOFFSETTO:+0200
TZNAME:CEST
DTSTART:20270328T010000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:+0200
TZOFFSETTO:+0100
TZNAME:CET
DTSTART:20271031T010000
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTART;TZID=Europe/Vienna:20261130T083000
DTEND;TZID=Europe/Vienna:20261201T130000
DTSTAMP:20260515T175202
CREATED:20260430T104450Z
LAST-MODIFIED:20260430T104450Z
UID:10000651-1796027400-1796130000@avoe.at
SUMMARY:EAA Web Session 'Open-Source Tools Python: Extending the Toolbox of the Actuary'
DESCRIPTION:The goal of this two half-day training is to introduce the participants to the Python open- source ecosystem and to get a good understanding of the language. However\, the ecosystem is way too vast to be covered in merely two half-days\, the participants will be asked to go through the basics of the language themselves\, prior to the web session. During the first half day of the web session\, these basics which will be shortly revised\, but at a higher pace. The course material\, containing the basics of the language\, will be provided by the organizers several weeks before the beginning of the web session\, such that the participants will have plenty of time to go through the material at her/his ease. \nAs such\, less time needs to be spent on the basic elements of the language\, hereby enabling us to organize a hands-on exercise session to more easily assimilate the course material. Note that the participants need to bring along a laptop on which Python is installed. Instructions on how to do so\, will be provided by the organizers at the same moment as the course material of Python basics\, hence several weeks in advance. \nAs a result\, a jump start on how to truly this language in practice will be provided to the participants\, by focusing on solutions for problems that they will surely regularly encounter in their day-to-day job\, by handing over lots of links to online resources and a very rich course material and by even organizing hands-on exercise sessions.\nAnmeldeschluss: 2026-11-26\nLink: https://actuarial-academy.com/en/continuing-education/upcoming-trainings/detail/open-source-tools-python-extending-the-toolbox-of-the-actuary-e0576/
URL:https://avoe.at/event/eaa-web-session-open-source-tools-python-extending-the-toolbox-of-the-actuary/
LOCATION:Online/Streaming
CATEGORIES:European Actuarial Academy (EAA)
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Vienna:20261202T090000
DTEND;TZID=Europe/Vienna:20261202T123000
DTSTAMP:20260515T175202
CREATED:20260430T105101Z
LAST-MODIFIED:20260430T105101Z
UID:10000654-1796202000-1796214600@avoe.at
SUMMARY:EAA Web Session 'Time Series for Actuarial Modelling with Machine Learning'
DESCRIPTION:Actuaries have long relied on time-tested statistical models to forecast risk. Methods such as ARIMA\, GLMs\, and the Lee–Carter model remain valuable tools\, and in many settings they still perform well. However\, the environment in which actuaries will work is changing. This web session will explore why we are moving beyond these traditional boundaries and how „Actuarial Learning“ is redefining forecasting. \nSteps towards machine learning are driven by the need to handle high-dimensional data and nonlinear patterns that standard regression techniques cannot capture. To bridge this gap\, we first consider ensemble methods\, such as LightGBM\, which outperform traditional actuarial models on complex tasks\, such as predicting flood injuries. \nBeyond ensembling\, deep neural networks offer even stronger representational capacity\, enabling us to model complex interactions directly from raw data. For instance\, while the Lee-Carter model has been the gold standard for mortality forecasting\, it often fails to capture cohort effects and cross-population heterogeneity. By adopting deep learning architectures\, such as Convolutional Neural Networks (CNNs)\, Recurrent Neural Networks (RNNs)\, and Long Short-Term Memory (LSTM) networks\, we can achieve significantly higher predictive accuracy. We will also briefly discuss emerging developments\, such as foundation models\, which enable the use of pre-trained models in actuarial contexts where data may be limited.\nAnmeldeschluss: 2026-11-30\nLink: https://actuarial-academy.com/en/continuing-education/upcoming-trainings/detail/time-series-for-actuarial-modelling-with-machine-learning-e0564/
URL:https://avoe.at/event/eaa-web-session-time-series-for-actuarial-modelling-with-machine-learning/
LOCATION:Online/Streaming
CATEGORIES:European Actuarial Academy (EAA)
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Vienna:20261203T090000
DTEND;TZID=Europe/Vienna:20261203T154500
DTSTAMP:20260515T175202
CREATED:20260430T105215Z
LAST-MODIFIED:20260430T105215Z
UID:10000655-1796288400-1796312700@avoe.at
SUMMARY:EAA Web Session 'CERA\, Module 0: A Refresher Course in Financial Mathematics and Risk Measurement'
DESCRIPTION:The web session ‚A Refresher Course in Financial Mathematics‘ gives an introduction to modern financial mathematics and derivative pricing. It is designed to prepare actuaries without adequate training in these fields for the quantitative parts of the CERA education. The web session is moreover an ideal learning opportunity for actuaries who want to become acquainted with or refresh their knowledge in these highly relevant fields. \nThe online course begins with a repetition of basic concepts in probability theory including characteristics of random variables such as moments and quantiles. In order to prepare the analysis of dynamic financial models we introduce the idea of conditional expectations and we discuss stochastic processes in discrete time. The online session continues with an introduction to financial mathematics. We study risk neutral valuation and the hedging of derivatives in discrete-time models. The last part of the web session is devoted to an introduction to financial mathematics in continuous time. Topics covered include stochastic processes in continuous time such as Brownian motion and the Ito formula\, the Black Scholes model and the Greeks very basic term structure models and the pricing and hedging of simple stock and bond options. The web session consists of lectures interspersed by short exercise sessions where participants can apply the probabilistic techniques hands-on.\nAnmeldeschluss: 2026-12-01\nLink: https://actuarial-academy.com/en/continuing-education/upcoming-trainings/detail/cera-0-a-refresher-course-in-financial-mathematics-and-risk-measurement-e0570/
URL:https://avoe.at/event/eaa-web-session-cera-module-0-a-refresher-course-in-financial-mathematics-and-risk-measurement-4/
LOCATION:Online/Streaming
CATEGORIES:European Actuarial Academy (EAA)
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Vienna:20261208T090000
DTEND;TZID=Europe/Vienna:20261210T140000
DTSTAMP:20260515T175202
CREATED:20260430T104906Z
LAST-MODIFIED:20260430T104906Z
UID:10000653-1796720400-1796911200@avoe.at
SUMMARY:EAA Web Session 'Non-Life Pricing Using Machine Learning Techniques with R Applications'
DESCRIPTION:Non-Life insurance is facing many challenges ranging from fierce competition in the market or evolution in the distribution channel used by consumers to evolution of the regulatory environment. \nPricing is the central link between solvency\, profitability and market shares (volume). Improving pricing practice encompasses several dimensions:\n– Technical: is our pricing adequate to cover the underlying cost of risk of my policyholders and the other costs we are facing? Which are the key variables driving the risk? Are they adequately taken into account in our pricing? What’s the impact of the claims history of my policyholder on its expected risk? In which segment are we profitable and in which are we not profitable?\n– Competition: at what price will we attract the segments that we target and price out those that we do not want? Is the positioning of our competitors influencing our pricing practice and our profitability? What’s my position with respect to my competitors in terms of pricing? What are the segments in which I am well positioned and the segments where I am not well positioned?\n– Elasticity: what price (evolution) are our existing customers prepared to accept? Does the sensitivity to price evolution depend on the profile of my customer?\n– Segmentation: is our segmentation granular enough for our purposes? \nThe aim of this web session is to present some advanced actuarial techniques used in non-life pricing\, competition analysis and profitability analysis. The web session focuses on some practical problems faced by pricing actuaries and product managers and presents some new techniques used in non-life pricing in order to open new perspectives for product development (competition analysis\, profitability analysis\,…).\nAnmeldeschluss: 2026-12-04\nLink: https://actuarial-academy.com/en/continuing-education/upcoming-trainings/detail/non-life-pricing-using-machine-learning-techniques-with-r-applications-e0579/
URL:https://avoe.at/event/eaa-web-session-non-life-pricing-using-machine-learning-techniques-with-r-applications-3/
LOCATION:Online/Streaming
CATEGORIES:European Actuarial Academy (EAA)
END:VEVENT
END:VCALENDAR