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X-WR-CALNAME:AKTUARVEREINIGUNG ÖSTERREICHS (AVÖ)
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X-WR-CALDESC:Veranstaltungen für AKTUARVEREINIGUNG ÖSTERREICHS (AVÖ)
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TZID:Europe/Vienna
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DTSTART:20260329T010000
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DTSTART:20261025T010000
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BEGIN:VEVENT
DTSTART;TZID=Europe/Vienna:20270301T080000
DTEND;TZID=Europe/Vienna:20270302T163000
DTSTAMP:20260910T090544Z
CREATED:20260910T090544Z
LAST-MODIFIED:20260910T090544Z
UID:10000698-1803888000-1804005000@avoe.at
SUMMARY:CERA\, Module D: ERM – Economic Capital
DESCRIPTION:The present training is concerned with the question of economic capital in corporate management. \nKey aspects are: \n\neconomic valuation and performance\neconomic steering\nkey performance indicators\nvalue based management\n\nA simplified case study for a life insurer shows in a nutshell the central aspects of corporate management in practice. The course consists of lectures and workshops. Participants are encouraged to bring their own topics to discussion.
URL:https://avoe.at/event/cera-module-d-erm-economic-capital/
CATEGORIES:European Actuarial Academy (EAA)
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Vienna:20270303T090000
DTEND;TZID=Europe/Vienna:20270303T134000
DTSTAMP:20260909T095511Z
CREATED:20260909T095511Z
LAST-MODIFIED:20260909T095511Z
UID:10000693-1804064400-1804081200@avoe.at
SUMMARY:The Pricing-Reserving Bridge: Portfolio Management in Practice
DESCRIPTION:In commercial insurance\, pricing and reserving are often treated as separate disciplines – different teams\, different tools\, different cycles. Yet they are two lenses on the same portfolio. When they operate in isolation\, they might give conflicting messages to underwriting and management\, resulting in portfolio mismanagement. \nIndividual risk pricing\, as sophisticated as it has become\, is no longer sufficient on its own. In a world where risks correlate more strongly than ever\, accumulations are harder to detect\, and decisions need to be made faster\, actuaries need to think and act at portfolio level\, not just risk by risk. \nTo address this challenge\, the web session introduces a Portfolio Management Framework that bridges pricing and reserving within a single operating model. The framework consists of four layers: Insight\, Steering\, Execution and Feedback. The session provides a detailed view of each layer\, as well as practical implementation tips within the organisation. \nA key element of the session is the hands-on case study\, which allows participants to apply the framework to a realistic commercial insurance portfolio. Participants will be asked to analyze the portfolio\, assess its alignment with the strategic goals\, develop a tiering structure and produce summary recommendations on portfolio steering. The follow-up debrief will explore divergent approaches and highlight key differences and practical takeaways. \nUsage of AI tools is explicitly encouraged throughout the case study. \nThe session closes with a forward-looking discussion on how AI is reshaping each layer of the framework\, accelerating anomaly detection\, improving strategy calibration\, and enabling real-time monitoring while keeping the actuary’s judgment and accountability central. \nAfter this web session\, participants will be able to: \n\nExplain why portfolio-level thinking is a necessary complement to individual risk pricing in commercial insurance\nApply the four-layer Portfolio Management Framework (Insight\, Steering\, Execution and Feedback) as an operational tool\nConduct a structured portfolio profitability assessment\nDefine concrete steering parameters and guardrails for portfolio segments\nIdentify where AI tools can augment actuarial portfolio management and where human judgment remains essential\n\nThe session takes a practical approach by combining conceptual instruction with a hands-on case study. Participants actively work through a realistic commercial lines portfolio scenario\, using AI tools of their choice\, and produce a short ExCo presentation pack as the deliverable. The debrief explores divergent approaches and highlights practical implementation insights.
URL:https://avoe.at/event/the-pricing-reserving-bridge-portfolio-management-in-practice/
CATEGORIES:European Actuarial Academy (EAA)
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Vienna:20270305T093000
DTEND;TZID=Europe/Vienna:20270305T130000
DTSTAMP:20260909T091507Z
CREATED:20260909T091507Z
LAST-MODIFIED:20260909T091507Z
UID:10000690-1804239000-1804251600@avoe.at
SUMMARY:Inside LLMs: How They Work and Why They Scale
DESCRIPTION:Deep learning has become the core engine of modern AI\, enabling models to learn rich\, non linear patterns directly from data. In recent years\, this paradigm has scaled into a new generation of systems capable of generating text\, solving problems\, and interacting in natural language: Large Language Models (LLMs). \nParticipants will revisit\, during this 3-hour online training\, the core ingredients of deep learning\, i.e. embeddings and non linear transformations\, and see how these principles extend to models trained on massive text corpora. We then introduce the conceptual foundations behind modern LLM architectures\, explaining at a high level how they process sequences\, capture relationships between tokens\, and scale with data and compute. \nThe web session highlights the key intuition behind the transformer framework without committing to a full technical deep dive. Attendees will gain a clear sense of why transformers replaced earlier approaches\, how they enable efficient parallel processing\, and discuss the practical implications of these models: what they are good at\, where they struggle\, and how their behavior is shaped by the underlying architecture. \nThe goal is to provide a compact\, accessible\, technically informed introduction to how modern language models work. \nThe objective of this 3 hour session is to build a solid\, intuitive understanding of how modern Large Language Models (LLMs) are structured and why their architecture unlocks such powerful capabilities.
URL:https://avoe.at/event/inside-llms-how-they-work-and-why-they-scale/
LOCATION:Online/Streaming
CATEGORIES:European Actuarial Academy (EAA)
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Vienna:20270308T084500
DTEND;TZID=Europe/Vienna:20270309T150000
DTSTAMP:20260909T155412Z
CREATED:20260909T155412Z
LAST-MODIFIED:20260909T155412Z
UID:10000694-1804495500-1804604400@avoe.at
SUMMARY:Fit4AI Compact
DESCRIPTION:The two-day in-person seminar offers actuaries a structured entry into the broad field of artificial intelligence. It teaches the key terms of data science and AI\, the essential concepts of machine learning\, and current developments in generative AI\, along with the principles of trustworthy AI and the requirements of the EU AI Act. The techniques are built up step by step\, from decision trees\, random forests\, and neural networks\, through clustering and dimension reduction\, to the tokenisation\, embeddings\, and transformer architectures behind today’s large language models. Beyond the methodological and mathematical background\, the seminar concentrates on practical knowledge\, suggestions\, and assistance for participants‘ own work: a hands-on block introduces the working environment of a data scientist and follows a complete analysis in Python\, from preparing the data to training and evaluating a model. Actuarial use cases from various sectors of the insurance industry illustrate and motivate the procedures and concepts throughout. Equal attention goes to the limits of these methods\, such as overfitting\, bias\, and the black-box problem\, and to the judgement that their responsible use requires. \nDeveloped by actuaries of the German Association of Actuaries (DAV)\, the seminar format has already been delivered very successfully in Germany\, where it has attracted more than 350 participants to date. Its strong reception underlines both the relevance of the topic for actuarial practice and the practical value of the programme for actuaries seeking to build AI literacy and apply AI methods in their day-to-day work. \nParticipants will gain a practical introduction to key concepts and methods in artificial intelligence\, data science\, machine learning\, and generative artificial intelligence\, with a particular focus on actuarial use cases in insurance. \nThe practical parts of the seminar are demonstrated live in Jupyter notebooks (Python)\, covering the basic data science workflow as well as selected machine learning and generative artificial intelligence case studies. Participants receive these notebooks afterwards as supplementary material and can explore and adapt them at their own pace. \nNote: According to Article 4 of the European Union’s AI Regulation (AI Act)\, all persons working with AI must have the necessary level of AI literacy. Participants in the seminar will receive confirmation of their AI literacy for actuarial use cases in insurance.
URL:https://avoe.at/event/fit4ai-compact/
CATEGORIES:European Actuarial Academy (EAA)
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Vienna:20270310T090000
DTEND;TZID=Europe/Vienna:20270312T123000
DTSTAMP:20260703T091334Z
CREATED:20260703T091334Z
LAST-MODIFIED:20260703T091334Z
UID:10000667-1804669200-1804854600@avoe.at
SUMMARY:EAA Web Session 'Assets and Liabilities Management Part 2: Advanced'
DESCRIPTION:The aim of this training is to\nDefine what ALM is and describe the typical missions of an ALM department in an insurance company\nPresent the financial risks on which ALM classically focus as well as the requirements of the Solvency II regulation for insurance companies\nDescribe the essential quantitative ALM tools and methods used by insurance companies to evaluate and mitigate the risks\nIllustrate the different concepts through numerical examples and case studies to make it practical and not just theoretical \nThis second part 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.
URL:https://avoe.at/event/eaa-web-session-assets-and-liabilities-management-part-2-advanced-4/
LOCATION:Online/Streaming
CATEGORIES:European Actuarial Academy (EAA)
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