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EAA Web Session 'Agentic AI for Actuaries: Practical Use Cases with Claude Code' on 14 December 2026

 

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EAA Web Session 
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Agentic AI for Actuaries: Practical Use Cases with Claude Code

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14 December 2026 | 9:30-13:00 CET

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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.


Agentic 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.


All 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.


Early-bird discount is available for bookings made by 2 November 2026.

Event Detail Registration
 
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Coming soon...

Assets and Liabilities Management Part 1: Introduction | 14-16 October 2026


The ORA under IORP II: From EU Landscape to Board Conclusions | 5/6 November 2026


Time Series for Actuarial Modelling with Machine Learning | 2 December 2026


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