Article

Actuarial Modelling in APAC: From Status-quo to Future-fit

Published date: 20 December 2023

The actuarial modelling status-quo is under pressure to transform – we are in the midst of one of the most significant regulatory changes in decades through IFRS 17, combined with a rapidly changing technology landscape. It is imperative for companies to revisit their actuarial modelling ecosystem to ensure it is future-fit.

Many insurers across APAC struggle to adapt and maintain their actuarial models to meet the increasingly complex reporting requirements (such as IFRS 17 and local RBC frameworks) of an ever-evolving business and regulatory environment.

Industry trends are heading towards the need for high data granularity and scalable systems to handle the increasing data and business demands.

The Deloitte APAC actuarial modelling community organised a series of workshops to consolidate our viewpoints on what the future should look like for actuarial modelling ecosystems. The workshops highlighted that actuaries have traditionally prioritised complexity and accuracy of model calculations over future-fit architecture and process requirements. This is understandable as it leans on the traditional actuarial strengths, however it can lead to solutions that lack the depth and efficiency to provide the insights and response times required by its business stakeholders.

In practice, there is often a communication gap between business stakeholders and the actuarial modelling team – neither necessarily speak the same language. This gap can lead to poor outcomes for insurers that can cause increased operational risks, cost overruns on development and execution, disenfranchised team members working overtime and/or on non-value adding tasks, and lost or delayed insights.

Specific poorer outcomes we have observed across APAC include:

  • Models that are difficult to update and maintain, and frequently poorly documented and controlled;
  • Many hours are wasted on routine maintenance and upgrading of models;
  • Risks associated with manual intervention, obsolete models and the time needed to update;
  • Under-utilised data and lost insights that could have been derived from a better-designed ecosystem;
  • Actuarial modellers confused about the true nature of actuarial work as they are overloaded by technology related activities.

This paper describes what a future-fit actuarial modelling ecosystem should look like to help solve these issues, focusing on people and skillsets, as well as systems, models and data.

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