IFRS 17 – Challenges in the Derivation of the Risk Adjustment and its Confidence Level
Announcement from the European Actuarial Academy organiser: Under IFRS 17, the Risk Adjustment is intended to measure the compensation that the entity requires for bearing the uncertainty associated with the amount and timing of the cash flows that arises from non-financial risk. The IFRS 17 Risk Adjustment creates challenges for both life and P&C (re)insurers such as how to estimate it and how to determine the confidence level needed for disclosure purposes.
This web session will first provide a presentation of the challenges related to the derivation of the Risk Adjustment and the fulfillment of the key IFRS 17 requirements related to its calculation. This will be followed by a discussion about the need for a proper confidence level disclosure methodology. The presentation will then provide an overview of methodological solutions and will include applications for both life and P&C companies.
The aim of this online training is to provide an overview of the modelling challenges related to the derivation of the Risk Adjustment and the disclosure of its confidence level.
Click here to register. Your early-bird registration fee is € 100.00 plus 19% VAT for bookings by 7 December 2021. After this date, the fee will be € 140.00 plus 19% VAT.
Participants: The web session is open to all interested persons working within the insurance industry.
Technical requirements: Please check with your IT department if your firewall and computer settings support web session participation (the programme Zoom is used for the web session).
Alexandre Boumezoued:
Alexandre is Research & Development Director in Milliman Paris office, covering modelling topics in life and non-life insurance as well as financial risks. Alexandre's current research interests deal with stochastic population dynamics and its use for longevity and mortality risks purposes, stochastic micro/macro non-life reserving models, scientific solutions for IFRS 17, as well as calibration methods for Economic Scenarios Generators.