EAA Web Session ‘Life Biometric Assumptions: Bringing Together New & Classic Methods’

Advances in data analytics techniques, along with greater availability of data, have significantly impacted many industries. However, in insurance, these advances merely add to the technical foundations upon which the industry was built. It is only recently that modern data analytics techniques have begun to impact insurance companies, especially in the work actuaries do.

The impact has been even slower to emerge in the life insurance sector where, due to the nature of the business, there is significantly less claims and exposure data available compared to non-life insurance. As a result, classic data analytics techniques and data sources are still key to the work actuaries do, especially when developing biometric assumptions. However, given the important role biometric assumptions play in the success of a company, it is important to understand how and if these new techniques should be applied.

To help make sense of the evolving landscape, this web session looks at the various components of life biometric assumptions (e.g. mortality tables, adjustment factors, improvement factors, etc.). For each component the potential sources of internal and external data will be explored. From there the value of classic data analytics techniques, particularly credibility theory, will be discussed, as well as modern techniques, such as machine learning. All of this will be brought together to give an understanding of the benefits, drawbacks, and pitfalls of the various data sources and analytics techniques, including considerations for data privacy and discrimination. The participants can then use this knowledge to effectively gain the benefits from each based on the quality and quantity of data available within their company and its market.
Anmeldeschluss: 2024-12-03
Link: https://actuarial-academy.com/seminars/seminar?No=E0455