BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//AKTUARVEREINIGUNG ÖSTERREICHS (AVÖ) - ECPv6.17.4.1//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
BEGIN:DAYLIGHT
TZOFFSETFROM:+0100
TZOFFSETTO:+0200
TZNAME:CEST
DTSTART:20280326T010000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:+0200
TZOFFSETTO:+0100
TZNAME:CET
DTSTART:20281029T010000
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTART;TZID=Europe/Vienna:20261208T090000
DTEND;TZID=Europe/Vienna:20261210T140000
DTSTAMP:20260630T152934Z
CREATED:20260430T104906Z
LAST-MODIFIED:20260630T152934Z
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
BEGIN:VEVENT
DTSTART;TZID=Europe/Vienna:20261211T090000
DTEND;TZID=Europe/Vienna:20261211T121500
DTSTAMP:20260703T103536Z
CREATED:20260703T103536Z
LAST-MODIFIED:20260703T103536Z
UID:10000671-1796979600-1796991300@avoe.at
SUMMARY:EAA Web Session 'Building Experience Mortality Tables – Practical Aspects'
DESCRIPTION:In life and protection insurance\, accurately assessing mortality is a cornerstone of pricing\, reserving\, and risk management. Standard mortality tables provide a useful benchmark but often fail to reflect the specific characteristics of an insurer’s portfolio. As a result\, insurers increasingly rely on experience-based mortality tables to better capture their own risk profile. \nHowever\, building such tables involves significant challenges\, including data quality\, statistical credibility\, segmentation choices\, smoothing techniques\, and methodological assumptions. \nThis web session provides a practical and structured approach to constructing experience-based mortality tables\, combining actuarial theory with real-world insights applicable across different markets.
URL:https://avoe.at/event/eaa-web-session-building-experience-mortality-tables-practical-aspects/
LOCATION:Online/Streaming
CATEGORIES:European Actuarial Academy (EAA)
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Vienna:20261214T093000
DTEND;TZID=Europe/Vienna:20261214T130000
DTSTAMP:20260909T085728Z
CREATED:20260909T085728Z
LAST-MODIFIED:20260909T085728Z
UID:10000689-1797240600-1797253200@avoe.at
SUMMARY:Agentic AI for Actuaries: Practical Use Cases with Claude Code
DESCRIPTION:Actuarial work is full of tasks that are technically routine but stubbornly manual: rebuilding a Solvency II balance sheet\, regenerating year-end reporting and QRTs\, reconciling a cashflow model against the numbers it is supposed to reproduce\, refreshing an MI dashboard\, or standing up a small tool to answer a one-off question from the business. Each is individually straightforward\, yet together they consume a large share of an actuary’s time and are a recurring source of key-person and spreadsheet risk. \nAgentic AI describes an emerging class of coding tools that do more than answer questions. Rather than returning a snippet to paste\, an agentic tool reads your files\, writes and runs code\, inspects the output\, and iterates towards a working result under your direction. Used well\, it lets an actuary automate genuinely complex workflows – end-to-end reporting\, model reconciliation\, assumption-setting\, validation harnesses\, model and process documentation\, and internal tools – without a dedicated software-engineering team. This session uses Claude Code\, one example of this class of tools\, to demonstrate the ideas throughout; the principles transfer to comparable agentic tools. \nAll examples are illustrative and deliberately generic – the focus is on the techniques and the working method\, not on any organisation’s proprietary models\, data or results. The emphasis throughout is practical and honest – what works\, what does not\, and how to keep agentic AI safe\, validated and defensible in a regulated actuarial setting. \nAfter this web session\, participants will be able to: \n\nExplain what agentic AI coding tools such as Claude Code are\, and how they differ from general-purpose chatbots.\nIdentify actuarial workflows – reporting\, reconciliation\, modelling\, assumption-setting and internal tooling – that are strong candidates for this kind of automation.\nFollow a repeatable pattern for scoping a task\, directing the tool\, and reviewing its work.\nUse the tool to generate and maintain model and process documentation that stays in step with the underlying code and satisfies Solvency II evidence requirements.\nApply validation and governance techniques (fail-closed checks\, reconciliation to a trusted source\, golden-master tests\, documentation) so that AI-assisted work is safe and defensible.\nRecognise the limitations and risks – model risk\, key-person risk\, professional and regulatory responsibility – and judge where agentic AI is and is not appropriate.\n\nThe approach is applied and example-led\, grounded in real actuarial applications. Demonstrations are kept short and purposeful – each chosen to illustrate a specific Claude Code capability in a couple of minutes – and any longer-running task is shown through its prepared inputs and results rather than by watching the tool work\, so the session keeps moving. Throughout there is candid discussion of what works\, what does not\, and the pitfalls to avoid. No prior software-development experience is required\, though familiarity with actuarial modelling will help participants get the most from the session.
URL:https://avoe.at/event/agentic-ai-for-actuaries-practical-use-cases-with-claude-code/
LOCATION:Online/Streaming
CATEGORIES:European Actuarial Academy (EAA)
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Vienna:20270212T093000
DTEND;TZID=Europe/Vienna:20270212T130000
DTSTAMP:20260910T084841Z
CREATED:20260910T084841Z
LAST-MODIFIED:20260910T084841Z
UID:10000695-1802424600-1802437200@avoe.at
SUMMARY:Tail Risk Measurement: Estimation\, Sensitivity\, Uncertainty
DESCRIPTION:Regulatory frameworks such as Solvency II require non-life insurers to quantify extreme risks — most notably the 99.5% Value-at-Risk over a one-year horizon for the Solvency Capital Requirement (SCR). In practice\, however\, this poses a fundamental challenge: historical loss data contains little to no information about such rare events\, making direct estimation inherently unreliable. \nThis web session addresses exactly this gap. It provides participants with a structured and practical toolkit to estimate high-confidence risk measures from limited data — and\, crucially\, to understand and communicate the uncertainty involved\, enabling more robust risk quantification\, particularly in contexts such as SCR validation and ORSA. \nStarting with classical parametric approaches and kernel density estimation\, the course progresses to Extreme Value Theory (EVT)\, with a focus on the Peaks-over-Threshold (POT) method and the Generalised Pareto Distribution (GPD). Particular attention is given to threshold selection and to Bayesian formulations in which the threshold is treated as an uncertain parameter\, enabling posterior-predictive inference for high quantiles. We also consider flexible bulk-tail mixture models that combine non-parametric bulk estimation with an EVT-based tail component. \nFor each method\, the course takes a structured perspective across four dimensions: \n\nthe point estimator and its finite-sample properties\,\nparameter uncertainty and confidence intervals\,\nsensitivity to modelling assumptions\, and\noverall model uncertainty.\n\nFinally\, we connect tail risk modelling to practical risk steering by linking estimated risk measures to capital allocation via the Euler (gradient) principle\, enabling a decomposition into marginal risk contributions across business units or risk types. \nFor the core methods\, participants apply estimation procedures in hands-on R exercises using real non-life insurance loss data\, developing both technical proficiency and the critical judgement required to interpret results. \nThe course provides a critical overview of methods for estimating tail risk at high confidence levels under real-world data constraints\, examining where and why they differ in their conclusions. \nR exercises on real non-life insurance data illustrate the methods in practice\, with particular attention to the interpretation and limitations of the resulting estimates.
URL:https://avoe.at/event/tail-risk-measurement-estimation-sensitivity-uncertainty/
CATEGORIES:European Actuarial Academy (EAA)
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Vienna:20270215T090000
DTEND;TZID=Europe/Vienna:20270218T143000
DTSTAMP:20260910T085716Z
CREATED:20260910T085716Z
LAST-MODIFIED:20260910T085716Z
UID:10000696-1802682000-1802961000@avoe.at
SUMMARY:CERA\, Module A: Quantitative Methods of ERM
DESCRIPTION:The 4-day web session assists actuaries in broadening their knowledge about modern quantitative financial and actuarial modelling; these topics form an essential part of the CERA syllabus. At the beginning of the online training we give a brief overview of the EAA-route to the CERA designation. The core part of the web session begins with an introduction to the modern theory of risk measures. Next\, a number of statistical techniques are discussed\, that are highly relevant for the analysis of actuarial and financial data and for the model-building process in risk management. Among others\, we will consider extreme value theory\, dependence modelling\, copulas\, and various aspects of integrated risk management. The training continues with an introduction to the modelling and the management of interest rate and credit risk. In particular\, participants will learn how to price simple interest options or Credit Default Swaps\, how to account for counterparty risk and how to deal with credit portfolio risk. \nThe web session consists of lectures and exercise sessions. In fact\, exercise sessions\, where various exercises and supplementary examples are discussed\, form an integral part of the seminar: they help the participants to understand the qualitative and quantitative techniques introduced in the lectures\, and they are a key element in the preparation for the CERA exam.
URL:https://avoe.at/event/cera-module-a-quantitative-methods-of-erm-2/
CATEGORIES:European Actuarial Academy (EAA)
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Vienna:20270225T090000
DTEND;TZID=Europe/Vienna:20270226T170000
DTSTAMP:20260910T090310Z
CREATED:20260910T090310Z
LAST-MODIFIED:20260910T090310Z
UID:10000697-1803546000-1803661200@avoe.at
SUMMARY:CERA\, Module C: Processes in ERM
DESCRIPTION:This module deals with the challenges of implementing ERM Processes. It includes requirements on ERM Processes and the discussion of best practices. It will be presented how to define an organisation’s risk strategy\, risk appetite\, risk tolerances and limits. We discuss how business strategy influences risk strategy and show their necessary interaction. We demonstrate the close relationship between ERM and Value and Risk Based Management and show how financial and other risks influence the selection of strategy. We show how ERM can be appropriately imbedded in an entity’s strategic planning and discuss the Own Risk and Solvency Assessment. We present the application of an internal risk control process. In the context of ERM reports to different stakeholders are required (management\, supervisory body\, regulators\, public disclosure). We give an overview of the different reports and the main contents. Further we show examples of communication processes in the context of ERM. During the web session we present case studies to discuss the main subjects.
URL:https://avoe.at/event/cera-module-c-processes-in-erm/
CATEGORIES:European Actuarial Academy (EAA)
END:VEVENT
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)
END:VEVENT
END:VCALENDAR