The new Research Paper from the Mortality Working Group explores how COVID-19 affected mortality in Australia from 2020 to 2023 and how Australia’s experience compares with the rest of the world.

Traditional aggregate reserving techniques assume that each data triangle used is a homogeneous group of claims. However, the practical constraints of management and reporting requirements often hinder the adoption of a statistically optimal approach to segmentation. There is often a reliance on legacy class hierarchies, business processes or expert judgement due to the difficulty of determining an optimal segmentation. This can reduce homogeneity in triangles and affect the performance of aggregate reserving techniques. To address these challenges, we propose a framework and methodology for automated segmentation to allocate individual claims in a reserving class to homogeneous subgroupings more suitable for triangle-based projections. The proposed approach involves use of machine learning techniques to: • Evaluate claim features that can relate to claim development in a statistically significant way. • Implement an algorithm to segment claims. • Assess and compare different segmentations on their impact on claim reserve accuracy. We also explore the practicalities for constructing models in a way that allows managing segmentation changes across reporting periods. Overall, we propose a methodology and practical framework for leveraging clustering techniques as part of a reserving process to improve accuracy and reduce the need for intervention of actuaries managing insurers’ claims reserves.

We model the relation between excess returns, fund size and industry size for active equity funds within four markets – global equities, emerging markets, Australia core and Australia small caps – and use the results to investigate the extent to which funds deviate from estimated capacity. We uncover a significantly negative relation between returns and both fund size and industry size across all markets. The estimated percentage of funds operating above versus below capacity varies both across markets and over time, and in the role played by fund size versus industry size. We find greater prevalence of funds operating significantly below than above capacity, in contrast to findings for US equity mutual funds. Significant deviations from estimated capacity persist for a median of between two and six quarters. Our main contribution is to show that the dynamics governing deviations from capacity for active equity funds vary across markets.

The Institute recommends policy solutions to address the financial sustainability of Private Health Insurance including the integration of health system funding to further benefit access to, and affordability of, the health network.

Questions arising from the recent competition compliance training sessions are set out in this document.

This paper from the COVID-19 Mortality working Group looks at a number of ways COVID-19 mortality has been measured around the world and in Australia by examining various datasets and discussing different statistical techniques observed. We then take a closer look at the mortality experience of Australia during 2020 and 2021, including experience by Cause of Deaths (including COVID-19), by age group, and experience during different COVID-19 waves . And finally, we take a brief look at the impact of COVID-19 on long term illness, based on studies from around the world.

Predicting customer churn is an important consideration for any business, including financial service businesses, because costs of acquiring new customers far outweigh costs of retaining existing ones. Our daily interactions with Siri, Alexa, Hey-Google, and Bixby, which are Natural Language Processing (NLP) based automation systems are currently treated as just another cool feature in our everyday lives. Imagine using this cool feature to solve a fundamental problem for a business – preventing customer churn. Different customers exhibit different behaviours and preferences and cancel their subscriptions for a variety of reasons. Most existing models predict customer churn by using demographic and transactional data of customers, which may not contain a full reflection of customers’ intentions. In this paper, a customer churn prediction model is developed using NLP by extracting features and patterns in unstructured data available against customer policies. These unstructured datasets are typically text, calls, and notes, and thanks to the advancement of NLP technology, these datasets can now transform into key information from which we can infer intention for churn. Existing commercial NLP models which predict customer intention based on text, are still in their infancy and researchers are still investigating how to improve such models. With fast emergence of new NLP features, many have become outdated. A case study is presented in this paper to predict customer churn and reason for intention to churn using call data which may not be possible using structured data alone. The model proposed in this paper uses recently available NLP tools and features to develop a customer churn prediction model. The model uses keyword matching to mine expressions of interest and profiles of people corresponding to customer criteria. The proposed model takes advantage of available pre-trained NLP models to perform sentiment analysis. A set of reference sentiments are manually generated and compared with the customer conversation to find the similarity as an index. This index is used as a threshold for a classifier model to identify the reasons for churn for any conversation. The performance shows that NLP has the potential to provide a detailed understanding customers’ churn behaviour including why a customer chose to churn.

This submission outlines the Institute’s views of APRA’s proposed revisions to the PHI capital framework and draws on previous submissions from July 2020 and May 2019. The Institute supports adoption of the Life Insurance and General Insurance Capital (LAGIC) structure for the capital standards in PHI and the introduction of the Internal Capital Adequacy Assessment Process (ICAAP) to encourage better management of risks and capital in a consistent manner. The Institute supports the tailoring of capital standards to suit PHI and this submission details further recommendations for APRA’s consideration.

The Institute supports the overarching intent of the proposals in the Discussion Paper, as well as APRA’s roadmap to strengthening the prudential regulation of the private health insurance industry. This submission responds in detail to the various issues and questions raised. It is focused on the soundness of the rationale supporting specific proposals, suggestions for further consideration by APRA and any practical considerations that may strengthen the transition and implementation of the new framework. Our comments are provided at a time when the current COVID-19 pandemic and responses by all stakeholders, including private health insurers, are still evolving. This is obviously an exceptional event. Our comments necessarily reflect our views at this point in time and may continue to evolve.

The Institute welcomes the opportunity to comment on the draft report in the areas of insurance, works compensation, superannuation and related funding issues.

Building on the Institute's recent Green Paper, this Dialogue takes another look at private health in Australia - how it is financed, whether it meets the needs of consumers and areas of potential reform.

Actuaries Summit 2019 The Australian Government provides or mandates compulsory private health cover for current and certain former military service personnel (and their families), temporary residents and foreign students. Examining the historical and current impact of these arrangements on the resident private health insurance market is crucial to understanding changes in private health insurance demographics, claims costs and premiums. This paper is being presented soon after the 2019 Federal election. While health, defence, immigration and education are all good subjects for political debate, the title of this paper reflects the additional ‘hidden insured’ groups of veterans (and their families), some temporary residents and foreign students who are covered for private hospital services separate to usual private health insurance arrangements. I presented an Actuaries Institute Insights session “War and Peace (and Health Insurance): The impact of Veterans health care on Private Health Insurance” in October 2017. This paper includes and expands on the analysis presented in that session.

In this instalment of the Actuaries Institute podcast series, Practice Excellence Adviser at the Institute, Vanessa Beenders sat down with Bevan Damm and Matthew Crane, authors of the new Green Paper 'How To Make Private Health Insurance Healthier' to discuss their research and findings. The healthcare system in Australia is complex. It involves many funders and healthcare providers with competing interests, both from the public and private sectors. However, despite its complexity, the healthcare system in Australia is one of the best in the world and, for a long time, private health insurance has been a part of that system. So, without reducing or expanding the role of PHI in the healthcare system more broadly, how can the community get more from private health insurance?

The PHI Capital Standards Working Group have made a submission to APRA PHI Capital Standards Review.

Actuaries Summit 2019 The focus on customer and customer value has never been more important for financial services with the recent Royal Commission, and specifically for Private Health Insurance given the record and increasing size of premiums relative to household budgets, and current political pressure on yearly premium increases. In this context, the paper will promote discussion on what is the true value of private health insurance for customers – focused on hospital cover – and how this compares to perceived value on average, and for different types of customers. To assess perceived value, we use the hospital cover participation rate – customers’ actual purchasing decisions - as well as customer research. We have developed a model of the factors that influence the participation rate, and reviewed the research. We aim to better understand the drivers of customer perceived value, including wealth, income, age, premiums, benefits, peace of mind, health attitudes and Government policy. We have assessed true value using reported data on PHI premiums, benefits, out-of-pockets, treatment waiting times, and other factors. We then look at whether there could be any difference between the “true value” for customers and their current perceptions of value. In other words, are customers undervaluing any aspect of their hospital cover? Value for some customers is low - is it time to act? And what could be some of the potential solutions to create better outcomes?