EAA Web Session: Actuarial Data Science - Advanced
Announcement from the EAA organiser:
This is part two of four courses required to obtain the EAA Certificate in Actuarial Data Science. To earn the certificate, participants must complete all four modules, which include both the seminar and the exam. Members of AVÖ and/or DAV will obtain the additional title Certified Actuarial Data Scientist (by AVÖ and/or DAV) by fulfilling the same requirements.
Furthermore, all courses are open to interested actuaries to deepen their knowledge and skills in the field of Actuarial Data Science (without exams).
Introduction
Due to technological progress in connection with Data Science and Digitalization, summarized under the buzzword Big Data, a plethora of opportunities and challenges for the industry is arising.
Technological developments have now also reached the insurance industry and thus have a direct impact on the working world of actuaries.
Under the heading Actuarial Data Science, the procedures and methods of data mining are embedded in the actuarial context. These range from mathematics-driven statistical methods for derivation of insights from data to computation-driven methods sometimes summarized as machine learning. As a result of almost unlimited computing capacity through cloud computing and wide availability of training data, tried and tested methods of machine learning, such as artificial neural networks, are experiencing a renaissance in theory and practice.
This web session is the second part of a four-part series at the German Actuarial Association (DAV). In this online training, we will expand on and deepen some of the topics already known from the basic seminar, discussing further important techniques in the context of deep learning and data storage. It is based on the learning objectives of the DAV for Actuarial Data Science Advanced, which is part of the actuarial training in Germany.
Click here. (Note: timing via that link is in CEST [Central European Summer Time].)
Prof Dr Fabian Transchel holds the endowed chair of e+s Rück for Data Science at Harz University of Applied Sciences, Wernigerode, Germany. He's an avid proponent of Machine Learning and Artificial Intelligence in the insurance sector and has been instrumental in innovating motor insurance through telematics technologies, these days also teaching Actuarial Data Science for DAA and EAA.
Prof Dr Jonas Offtermatt is a professor of programming and mathematics at DHBW Stuttgart. He has been working as a programming actuary since 2015 and has been teaching at DAA since 2019. With previous leadership roles in the insurance industry, he possesses extensive experience of IT-management and software development.
Wolfgang Abele joined Deloitte 2018 as Senior Manager in the actuarial Non-Life team. He has more than 18 years of experience in the consulting and insurance industry, having worked for HDI Versicherung AG, MSG Consulting und Allianz. Before he joined Deloitte Wolfgang was head of the unit Reserving & Reinsurance.
Throughout his career, he was involved in a large number of actuarial projects, in pricing, reserving (IFRS, local GAAP, Solvency II), internal modelling and risk management. His focus was on predictive modelling, analytics, and process optimization. He has extensive knowledge in the programming language R and gives seminars on actuarial data science for the Deutsche Aktuar-Akademie (DAA).
Dr Marc Busse is heading the department for software solutions within the microscopy division of ZEISS. Previously, he has been working for seven years in the reinsurance sector as an actuary with focus on data science related topics. Marc is a certified actuary (DAV) and holds a PhD in theoretical physics.
Dr René Külheim is a mathematician and actuary (DAV) at PTA GmbH, where he heads the artificial intelligence department. In addition to data science-based project work in the financial sector, he is responsible for cloud-based software products with AI components.