Description
Most insurers and reinsurers – across all lines of business – are increasingly active in the area of Big Data. Much of what has been written on this topic thus far has focused on the analytic techniques or on the varieties of data – from facial imaging to fitbits. But little has been published on the fundamentals of how we go about the analytics, and how we extract value and interpret results effectively. Our presentation will look at the generally hidden fundamentals – for instance, the nature of patterns and information, the validity of significance testing, the limitations of analytic and Artificial Intelligence (AI) techniques, and the implications of big data and AI on data privacy. The session is aimed at all actuaries with an interest in data analytics.
Speakers:
Matthew Edwards leads the life underwriting risk / analytics team in the life insurance practice at Willis Towers Watson, and was lead author of the 2012 SIAS paper ‘The Philosophy of Modelling’
Rachael McNaughton is a data scientist in the advanced analytics team at Willis Towers Watson, and has spoken at a number of actuarial conferences in Australia, Europe and the US on machine learning and big data in an insurance context.