11th & 12th November 2019
Would you like to learn which applications deep learning techniques offer in the context of market risk, economic capital modelling, asset allocation and actuarial business planning?
If yes, our seminar "Deep Learning – Applications in Market Risk and Economic Capital Modelling: Deep dive and practical exercises" on 11/12 November 2019 in Prague, is perfect for you.
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.
This seminar will exclusively focus on applying deep learning techniques for market risk modelling and the wider economic capital modelling space as well as asset allocation and actuarial business planning which represent areas of great importance for insurance companies where deep learning techniques have typically not been widely used before. Main goal of the seminar is to present relevant tools and techniques from deep learning and bring them together with applications in market risk, economic capital modelling, asset allocation and actuarial business planning. Examples are proxy modelling, projecting cash flows and economic balance sheet items (incl. the Solvency II ratio) in the future and prediction of economic time series.
The seminar will be highly practical; all major applications presented in the seminar will be followed by hands-on sessions where the participants will be able to implement the techniques under supervision and apply them to data sets.
The early-bird registration fee is € 840.00 plus 21% VAT and valid until 11 September 2019. After this date the fee will be € 990.00 plus 21% VAT.