While insurance principles have been used for centuries, the industry has been quick to adopt new technologies, including investing in insurtech startups to benefit from disruptive ideas. Many of the developments in insurance that attracts headlines is around the impact of analytics on automation, distribution channels or transaction models on growth and profitability.
With data becoming more widely available, there are more and more companies using powerful machine learning models to gain an edge over their competitors, writes Jonathan Tan.
One of the biggest challenges in adopting machine learning models is their lack of interpretability. It is important for actuaries to be able to understand what models are doing. This article discusses the popular SHAP approach as a superior method of calculating feature importance.
While the 2019 Australian Federal Election can be a very serious matter, the young Actuaries Data Analytics Group (yDAWG) decided to have a bit of fun. Using a Markov Chain generator and existing library of historical tweets, they explain how synthetic tweets can impersonate our political leaders.
Posted 20 November 2018