New CPD releases for 2026

Discover Our Latest Training Opportunities

We’re happy to announce new CPD releases of 2026. These events are designed to strengthen your skills, keep you up to date with the latest developments, and support you in fulfilling your CPD requirements.

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This session aims to explain the evolution of the interest rate capital requirement under the current formula versus the new formula following the SII review, how the deficiencies have been addressed and the remaining issues in an inflationary environment.

The purpose of this web session is to explain how the current SCR interest has been calibrated based on Principal Component Analysis and the need for changes in a low interest environment. We will then describe the new relative shifted approach and impact assessments. We will also address the question on the SCR interest up in an inflationary environment and possible solutions.

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Asset-Liability Management (ALM) sits at the heart of insurance company valuation, risk management, and strategic decision-making. In this two-part web session, we will explore both the foundations and the future of ALM modeling software. 

The web session aims to:

• Demystify the role of ALM models in insurance valuation and financial management.
• Explain how these models are built, from accounting foundations to simulation and projection frameworks.
• Highlight key challenges and best practices in implementing and maintaining an ALM platform.
• Showcase the transformation of ALM through technology, focusing on the integration of AI, automation, and intelligent assistants.
• Inspire actuaries to adapt their skills and thinking to a rapidly changing modeling landscape.

The session will combine educational content, conceptual illustrations, and live demonstrations from Solvencii’s R&D initiative—Solvencii Lab—and its AI assistant, Solvencii Copilot, designed to support actuarial teams in their modeling and analysis workflows.

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The web session discusses the requirements of IFRS 17 for aggregating insurance contracts in “portfolios of insurance contracts” and “groups of insurance contracts,” as well as their areas of application. It discusses the conceptual and practical obstacles arising for each area. Special consideration is given to reinsurance contracts and commercial contracts, as well as to special circumstances such as portfolio transfers and business combinations. Further, issues arising within consolidated groups of entities are considered. 

The online training aims to enable participants to develop solutions for these issues and provide an accounting justification. 

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The actuarial profession is transforming due to the growing complexity, types and volume of data, which traditional statistical models struggle to analyse effectively. To improve predictive performance and risk assessment, actuaries are increasingly adopting advanced analytical techniques like deep learning, and Python is gaining widespread adoption across various actuarial tasks. Within this context, PyTorch stands out as a flexible, Python-friendly, and opensource deep learning framework developed by Facebook's AI Research lab, designed for flexibility and ease of use in production environments, making it an ideal choice for actuaries transitioning into advanced analytics. Deep learning proficiency in non-linear relationships across a multitude of variables allows for a more granular understanding of risk drivers and their complex interactions. The accessibility to the PyTorch framework gives a profound shift: actuaries are empowered to move beyond merely being users of models developed by others, becoming creators and innovators of advanced analytical solutions themselves. This technology facilitates a shift from simplified risk profiles to more dynamic individual-level predictions, enabling actuaries to develop personalised insurance products and proactive risk management strategies.
 

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As the actuarial field evolves with technology, learning Python has become increasingly important. Python is a versatile programming language that enables actuaries to efficiently handle large datasets, perform complex statistical analyses, and apply machine learning techniques. Whether you are working with pricing models, risk assessments, or data visualization, Python can significantly enhance your productivity and decision-making. 

In this seminar, we will cover: 

1. Python Basics: An introduction to Python programming, focusing on data structures and fundamental syntax. 
2. Data Manipulation: Working with datasets using Pandas for data cleaning and transformation. 
3. Data Visualization: Creating insightful charts and graphs using Matplotlib and Seaborn. 
4. Machine Learning: Applying basic machine learning models to actuarial data. 

This seminar is designed to give participants hands-on experience and practical knowledge of how Python can be a valuable tool in your day-to-day work. 

The seminar will be held in person, giving participants the opportunity to learn on site alongside other actuarial professionals, exchange ideas directly, and receive immediate support from the lecturers. The evening event on the first day is giving participants the opportunity to connect, discuss practical questions, and build their professional network in an informal setting.

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This web session is the third part of a four-part series at the German Actuarial Association (DAV). In this online training, we will expand on and deepen some of the topics already known from the basic and advanced trainings, discussing further important techniques in the context of deep learning and providing further theoretical foundations. It is based on the learning objectives of the DAV for Actuarial Data Science Immersion, which is part of the actuarial training in Germany. In addition, all courses are open to interested actuaries to deepen their knowledge and skills in the field of Actuarial Data Science (without exams). 

Based on the building blocks known from Basic and Advanced, 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 including an advanced introduction to the concepts and terms of artificial intelligence, concepts of information theory, aspects of data protection, some mathematical and statistical concepts, as well as insights into innovative products (with a special look at insurance companies). On our way, we touch different use cases in the actuarial environment. 
 

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This session aims at analysing the impact of IFRS 17 versus Solvency II. After a general description of both frameworks, we highlight the most recent changes following the Solvency II review with a focus on discount rates and risk margin. We will then explain IFRS 17 accounting choices versus Solvency II and benchmark those. Finally, we will show the impact of IFRS 17 on the management of the contracts when issued and during their lifetime (profit testing and key indicators).

The purpose is to understand the key accounting choices under IFRS 17 and how they relate to Solvency II. This has an impact when valuing and managing insurance contracts. This will also allow users of financial and prudential information to get a better understanding of the figures depending on the purpose and methodology used. 

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20 November 2025

Quantifying the Prospective Impact of Air Pollution on Mortality

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24 November 2025

Solvency II Review: Framework Approaches Finalisation

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1/2 December 2025

CERA, Module 0: A Refresher Course in Financial Mathematics and Risk Measurement

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4 December 2025

EAA's Anniversary Conference

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10 December 2025

GenAI Beyond the Basics: Advanced Concepts for Actuaries

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28 January 2026

Worldwide Mortality: From Historical Trends to Future Projections

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2 February 2026

Volatility Adjustment under Solvency II

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3 February 2026

AI in Insurance: Strategic Imperative & The Actuary’s New Frontier 

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... and a lot more! Explore our CPD Flyer for more details.