Media Machine Learning and Analytics in Life Insurance

Machine Learning and Analytics in Life Insurance

uploaded August 7, 2023 Views: 178 Comments: 0 Favorite: 4 CPD

Life insurers are amongst the largest financial services businesses globally and have access to extraordinary amounts of data about their policyholders and their preferences. For many years actuaries have performed deterministic or stochastic valuations intended to supplement financial reporting and explain the value inherent in long term life insurance policies. Actuaries have also sought to utilise these valuation concepts to understand the value of individual policyholders to facilitate cross-selling of products and focus retention programs. As computers and analytical techniques have developed over time, so too have the opportunities to leverage data – both a business’ own data, shared data and enrichment data. It is clear that there is tremendous opportunity in having access to data, and in utilising this data in an appropriate way, mindful of ethical considerations of an individual’s rights (e.g. privacy and anti-discrimination). Actuaries are perfectly placed to utilise their analytical abilities in an ethical framework to monetise data. In this session we will explore how machine learning and data analytics can be applied across a life insurance business to understand the underlying drivers of the business and apply this in the business – for example:

  • Applying targeted retention programs;
  • Developing marketing strategies; and
  • Setting tailored assumptions for life insurance valuations.

We invite you to an interview with Sai Shankar, General Manager of Analytics and Sue Xu, Analytics Innovation Lead as we explore the work developed by Greenstone Holdings, a life insurance distribution business in Australia and New Zealand which has embedded these techniques into all aspects of the management of the business. We welcome questions from the audience.

Find the Q&A here: Q&A on 'The Digital World and Life Insurance'

Content groups:  content2023


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