Description: The cloud inspires awe and fear in equal parts these days. There is a need to learn more, but there’s much information to learn and it may be difficult to know what to learn next. In this session, we’ll carve off a small corner of the cloud and make it your own. Setting up a Data Science Virtual Machine on Digital Ocean will be demonstrated. It’s the fastest way to get a data science development environment setup for your own use. Many of the topics and ideas covered will apply to almost all other cloud offerings. What use cases Digital Ocean is good for, and what use cases you should look elsewhere for, will also be discussed.

Description: Ever wanted to do a Kaggle data science competition, but didn't know where to start? This presentation meets the needs of actuaries interested in predictive analytics and competitive data science. The presentation will describe the nature of competitive data science, and provide insights into lessons learned by competing in the Airbus Ship Detection Challenge at Kaggle, as well as other Kaggle competitions. The presenters will provide an introduction to neural networks and describe the nature of the Airbus Ship Detection Challenge and other Kaggle competitions, plus a solution approaches that can be used to obtain top scores using Convolutional Neural networks (CNNs), random forests and boosted trees.

Description: Most actuaries deal with model development at some point in their career. However, very few of us have proper training in programming, software engineering or software shop operations. Explore topics, techniques, and practices from the FinTech and IT industries that can be applied to building robust, high-quality actuarial models. This session will be of particular interest to actuaries engaged in 'in-house' model development, managers of modeling teams, and actuaries interested in software development.

Description: Machine learning models have many practical applications in the world of insurance. These applications are well documented and most actuaries, at least at a high level, are familiar with these concepts. The presenters will take this one step further and provide an introduction to the theoretical formulas and real-world considerations that make machine learning models possible.

Description: Predictive modeling continues to gain traction in the life insurance industry with the rapid growth of available data and maturity of open source tools. New methods and technology in predictive analytics have enabled the evaluation of extremely large data more quickly and allow us to incorporate features previously not considered. The presenters will provide background on predictive modeling tools and algorithms utilized by actuaries and data scientists for life insurance, highlighting applications from marketing to underwriting.

Description: This third session in the Munich Re series continues with an exploration of responses to the changing workplace landscape from those inside the industry. The presenters will focus on practical approaches to identifying new opportunities, and on ways in which traditional products and sales channels are changing to meet emerging needs. Are voluntary benefits still relevant? Yes, but they are changing. While the first session provided an overview of the future workplace, this session will provide an overview of the current and evolving voluntary benefits market. Sales processes and products will be challenged to change to keep up with the new workplace dynamic. The presenters share strategies for developing products and sales channels that are robust and flexible enough to address evolving customer needs.