Data Science

Tim Harford speaks to Ruolin Wang about why it’s so important to slow down and question things from emotive headlines to the numbers and algorithms we use in our work

Vrishti Goel examines how data analytics could provide more personalised insurance products, for example within the motor insurance industry

Massimo Cavadini, Davide Burlon and Gili Smadja discuss how automated machine learning is changing the role of the pricing actuary

Yiannis Parizas and Phanis Ioannou consider how non-life organisations could gain a strategic advantage through various aspects of the pricing process

Martijn Westra reports on a recent hackathon, which aimed to boost health outcomes and demonstrate the value of both data science and actuaries

In an increasingly uncertain world, insurers can use behavioural economics to help them develop more accurate foresight, says Maura Fedderson

Juan Ignacio de Oyarbide discusses the outcomes of a motor insurance pricing game held in Saudi Arabia, and key lessons to emerge from it

Yafei (Patricia) Wang looks at the use of machine learning to predict underwriting decisions for life and health insurance

Is machine learning a threat to the underwriting practice? Reza Hekmat and Balint Bone consider this possibility and its challenges

Lisa Balboa, Maryse Nashime, Serena Soong and Joe Wilson assess how data use could help to progress actuarial understanding of mental health