The Institute and Faculty of Actuaries is launching their first virtual conference on the topic of Data Science, and it is free to attend. This is an exciting and forward thinking move by IFoA to reach members all over the world and to share knowledge and discuss developments and techniques within data science.
The virtual conference will demonstrate how actuaries can develop their existing knowledge or move into the world of data science and will offer a platform for members and students to learn more on AI, Machine Learning and other areas of Data Science.
IFoA also plans to record the live webinars and will be recorded and available to watch up to 48 hours after the live event, so if you are unable to watch it live, you won’t miss out. The virtual event will be open for a time after the final live event, so delegates will still be able to watch the recorded webinars and on-demand videos after the conference has finished.
Chair– Philip Darke
Committee Members– Alex Breeze, Mahidhara Davangere, Niall Fennelly, Nicolas Nghidipaa, Valerie du Preez, Tom Rutter, Maribel Vazquez, Heting Yang
|Advanced ‘big data’ analytics for mortality||Advanced analytics and ‘big data’ are one of the latest sources of competitive advantage. In this session, originally presented at Life 2018, the speakers outline a broad range of advanced analytical techniques (e.g. neural networks, GLMs, GBMs) and the appropriate criteria for choosing between them (e.g. predictiveness v interpretability).||Matthew Edwards and Rachel McNaughton|
|Artificial Intelligence – Through the Looking glass||Discussing AI||Professor Dame Wendy Hall|
|Case Studies in Machine Learning and AI||Willis Towers Watson will present a number of case studies showing how Machine Learning and AI techniques can be deployed to deliver benefit across the insurance sector, with a particular focus on claims, pricing and underwriting.||Chris Halliday, Andy Rigby and Craig Stevens|
|Data Science in Health Care: Leveraging Big Data in Predictive Modelling||Exploring how big data sources are being leveraged in data science models around the world. Examples include improving quality of care, forecasting and preventing epidemics, streamlining the hospital admissions and discharge process and cost savings.||Lisa Balboa|
|Data Visualisation as a Powerful Means of Communication – Examples from the IFoA Working Party||Data Visualisation helps to communicate information clearly and effectively through graphical means. This talk originally presented at Life 2018 will showcase some visualisations that the working party has found useful for common actuarial situations.||Rob Black and Julian Ellacott|
|Emerging risk: actuaries, artificial intelligence and the Board||This session originally presented at Life 2018 will show you examples of how to create dynamic and novel content using your company’s experts, complemented with artificial intelligence, and how to communicate it effectively to a range of executive and non-executive audiences to prompt action.||Neil Cantle and Chika Aghadiuno|
|Machine Learning for Actuaries||This talk, originally presented at GIRO 2018, aims to address elements of integration of machine learning techniques into the day-to-day by providing an introduction to machine learning as well providing worked examples to illustrate the application of machine learning in an actuarial context.||Steven Perkins and Hazel Davis|
|Machine Learning Actuaries||This workshop will cover machine learning techniques with examples in R. This will be a hands-on session.||Louis Rossouw|
|Pathway for Actuaries into the field of Data Science – An interview with a Practitioner||The interview focuses on following questions regarding pathway for actuaries to become data scientists and its relevance to our members||Mahidhara Davangare|
|Putting Data Science to Work||We share our experiences over the past year of introducing data science processes and open source software (R, Python, Git) into our workflow.||Alex Breeze and Martin Tynan|
|Training a neural network to fit curves to claims data||A novel method of producing smooth curve-fits to claims Severity refers to the amount you have received Insurance claim for. Average Severity would be the loss associated with an average Insurance claim. data for use in frequency-severity modelling of insurance claims.||Alexander Hanks|
|The use of predictive analytics to enhance life insurance portfolio management||Explains, using practical and easy to follow steps, how leading life insurers are using predictive analytics to manage their portfolios, growth, persistency and profitablity.||Assaf Mizan; Valerie Du Preez and Martin Snow|
|You can code your own way? Building data science capability in Risk||Discusses why now for data science, developing actuaries and identifying projects.||Matt Saker, Finn Clawson and John|
Pricing information- This event is free to attend
Let us know if you are planning to attend it and what do you expect from this Webinar.
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