The Economic Scenario Generators (ESG) are at the core of stochastic models used by insurance companies. The applications of stochastic models are very diverse and include such applications as economic capital under Solvency II, ALM projections, dynamic hedging etc. Hence, practitioners have to keep abreast of the current ESG-related challenges and approaches to overcome these.

Organised by the EAA - European Actuarial Academy GmbH in cooperation with the Österreichische Förderungsgesellschaft der Versicherungsmathematik (ÖFdV) GmbH.

This seminar builds upon the contents of our introductory ESG seminar offered by the EAA in March 2019 and before. We are now going to discuss a few advanced ESG related topics suggested by the participants:

• Practical ESG calibration challenges 
• Inflation modelling and application
• Credit risk modelling challenges
• Multi-economy modelling
• ESG and Least Square Monte Carlo

We expect that the participants of the upcoming seminar are familiar with basic ESG concepts such as interest rate models or equity models, are not afraid of some technical cooking recipes from the ESG kitchen and are keen to discuss the practicalities of ESG work in the context of the current market environment and regulatory requirements.

Attendees are encouraged to bring a laptop computer with Microsoft Excel installed.

In the seminar, we begin by providing a broad overview of current ESG topics and their challenges. We then discuss credit risk models and good practices of their calibration. Next, we discuss risk-neutral multi-currency modelling from both theoretical and operational viewpoints. We conclude Day 1 by an introduction to inflation modelling and a corresponding case study.

On Day 2, our emphasis will be on practical aspects of interest rate model calibration relevant in Solvency II context. Firstly, we will examine the volatility calibration challenges arising from the mismatch between the EIOPA-prescribed yield curves and the market yield curves used by quotation platforms. Secondly, we will show how to determine which points of the volatility surface are particularly relevant for a life insurance portfolio and how to emphasize these points in the calibration process. We will conclude the seminar by a Least Squares Monte Carlo case study.

Pierre-Edouard Arrouy
Pierre-Edouard Arrouy is leading the financial modelling team inside the Research & Development section of Milliman Paris; his consulting work relates to the design, the implementation and the review of financial models within risk-neutral and real-world ESGs. His current research topics deal with calibration methods for interest rates models with stochastic volatility, modelling of credit risk, as well as the pricing of complex derivatives. He is also actively involved in the development of the cloud based ESG solution Milliman CHESS.

Paul Bonnefoy
Paul Bonnefoy is a R&D Consultant at the Paris office of Milliman. He provides his financial modelling expertise to clients through various missions related to the implementation and the review of financial models within risk-neutral and real-world ESGs. His R&D works concern among other things the acceleration of the calibration process of financial models and the pricing of complex derivatives. He is also actively involved in the development and the management of the cloud based ESG solution Milliman CHESS.

Michael Leitschkis
Michael Leitschkis is a Principal with Milliman. Michael has been dealing with various ESG aspects for about 15 years, notably in the context of Solvency II, including proxy modelling techniques such as Least Squares Monte Carlo. He has been part of the German Actuarial Society (DAV) working party dedicated to Economic Scenario Generators and taught Financial Mathematics at the University of Cologne.