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4.46 of 5 Points

WEB SESSION

25 Sep 2019

Web Session: Deep Learning–Applications in Market Risk and Economic Capital Modelling: Overview

Deep learning techniques represent a certain part of wider machine learning methods and have become increasingly popular for a variety of real-life applications solving complex high-dimensional problems.

So far, typical applications for deep learning architectures such as deep neural networks and recurrent neural networks include speech and pattern recognition, language processing, audio recognition or machine translation. In all these applications, deep learning techniques were able to yield break-through results due to their highly flexible and innovative architectures and their approach of training models towards a set of given data.

Hence, given the variety and complexity of problems in the insurance industry combined with the typically large amounts of available data, practitioners have started applying these techniques in the insurance industry.

Dr. Mario Hoerig and Dr. Daniel Hohmann will demonstrate how state-of-the art deep learning techniques can be successfully be applied to some of the most relevant and challenging topics in the context of market risk and economical capital modelling as well as asset allocation and actuarial business planning for insurance companies.

The web session will contain detailed case studies for the application of deep learning for the projection of actuarial cash flows and the Solvency II ratio as well as the prediction of economic time series.

This web session  is for practitioners who want to gain a feeling for applications of deep learning techniques in the context of market risk and economic capital modelling as well as asset allocation and actuarial business planning.

In addition to the stand alone web session, EAA offers the seminar ”Deep Learning – Applications in Market Risk and Economic Capital Modelling: Deep dive and practical exercises” on 11/12 November 2019 in Prague. The speakers describing both activities:

The web session provides an overview on current state-of-the-art techniques and illustrates them based on two case studies, while the seminar offers a deep dive into these techniques providing more and additional technical and theoretical background and allows the participants to apply DL techniques themselves under the guidance of the speakers.

Participants of the web session  who also take part in the seminar in Prague will get a discount of € 50.00 on the seminar price.

Organised by the EAA - European Actuarial Academy GmbH.

Participants

The web session is open to all interested persons.

Technical requirements and test session
Please check with your IT department if your firewall and computer settings support web session participations (the programme GoToTraining is used for the web session). Please also make sure that you are joining the web session with a stable internet connection. 

On 19 September 10:00 – 10:30 CEST, there will be a test session offered to all registered participants to test the software.

Purpose and Nature

The aim of this web session is to provide an overview on the powerful tools deep learning techniques are offering in the context of market risk and economic capital modelling as well as asset allocation and actuarial business planning. Therefore, we will provide a short introduction into the wider deep learning framework and then focus on key techniques, tools and ingredients which are particularly useful for the context of market risk and economic capital modelling. Two case studies (one on the projection of actuarial cash flows and the Solvency II ratio and one on the prediction of economic time series) will illustrate the applications and their possibilities.

Language

The language of the web session will be English.

Lecturers

Dr. Mario Hoerig, Partner, Oliver Wyman Actuarial
Mario Hoerig is a Partner with Oliver Wyman, co-leading the actuarial services offering in the German speaking markets. Mario focuses on quantitative modelling under Solvency II (economic scenario generators for risk-neutral and real-world purposes, ALM studies, risk factor modelling for Solvency II, risk aggregation, economic capital and capital management) and advises some of the largest insurance companies in Europe on these topics.

Dr. Daniel Hohmann, Senior Manager, Oliver Wyman Actuarial
Daniel Hohmann is a Senior Manager with Oliver Wyman. He has a strong quantitative background and has been advising his clients on a variety of market risk and economic capital topics such as proxy modelling, risk-neutral and real-world scenario generation and time series analysis for market data.

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