The Institute supports the Government’s decision to ban adverse genetic test results in life insurance underwriting. This will give the Australian community certainty and assurance on the way forward and support medical advances that can benefit society in many potentially profound ways. As genetics research is a rapidly advancing field, we recommend policy that can adapt to the advances in genetics so that life insurance balances accessibility of insurance and equity to the insured population as a whole.

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.

The Actuaries Institute welcomes the opportunity to provide this submission to the Senate Community Affairs References Committee’s Inquiry into Excess Mortality. The comments draw on the extensive work of the Institute’s Mortality Working Group to analyse pandemic-related data to inform the actuarial profession, the industries they advise, and policy discussions, which focus on the excess mortality experience in Australia during the period 2020 to 2023.

The purpose of this paper is to understand mortality trends in Australia by capturing cohort effects using the Continuous Mortality Investigation (CMI) model developed by the British institute of actuaries. In particular, we look at what can be expected in terms of future mortality improvements over the next few years by extrapolating explainable cohort effects in the Australian population. We compare life expectancies at retirement age using the Australian Life Tables 2015-2017 (ALT15-17) and scenarios of mortality improvements consistent with historic cohort effects observed in the Australian population. We discuss whether excess mortality in Australia in 2023 is a glitch caused by COVID-19 or the early sign of a more deeply rooted pattern of mortality improvement slowdown, such that has been observed in other countries. The research shows some headwinds are already noticeable in the pre-COVID-19 data and suggests the 25-year mortality improvement factors of the ALT15-17 are likely to be optimistic for the general population.

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.

In an era where financial literacy and risk management are paramount, understanding the motivations behind life and health insurance purchases is crucial for the industry. This report explores the behavioral factors influencing insurance purchase among Gen Z and Millennials for forward-looking purposes, leveraging a rich dataset spanning 22 markets across six continents. Employing both traditional economic regression and state-of-the-art machine learning models, this study offers a dual perspective on market behaviors and purchasing trends. Our comprehensive study is based on data from the Global Consumer Study 2023-24, a global survey of over 12,000 individuals carried out by SCOR’s Digital Solutions division. It delves into demographics, insurance preferences, personal circumstances, and digital engagement. With an analytical focus on younger generations, the findings illuminate key predictors for insurance purchase: 1. Insurance Knowledge: A foundational factor, where higher understanding correlates with increased insurance purchases. 2. Marital Status: Highlighting a trend where married individuals are more prone to purchasing life and health insurance than their single peers. 3. Employment: Demonstrating that those with full-time and part-time employment are more inclined to invest in life and health insurance. 4. Property Ownership: Linking property ownership with a higher likelihood of having insurance coverage. 5. Urban Residency: Observing that urban dwellers are more apt to purchase insurance. 6. Age Dynamics: For Gen Z and Millennials, relatively young segments of the general population, there’s a trend where interest in life insurance slightly increases with age, while the inclination to purchase health insurance experiences a marginal decline. 7. Sex Preferences: Men show a predilection for life insurance, whereas women display a preference for health insurance. The study delves into the inclination towards recent insurance purchases, particularly noting an uptick among younger generations endowed with high insurance literacy. It has been observed that individuals who have made claims are also more inclined to engage in recent purchases. This trend underscores the generations’ readiness to adopt online solutions, especially those prioritizing cost efficiency and effectiveness. Among middle-aged groups, a notable interest in utilizing health apps correlates with a higher likelihood of recent insurance acquisitions. The findings highlight a major move towards using digital methods to buy insurance, especially noticeable in major urban cities. This move to online platforms is a big change in the insurance world, requiring companies to skillfully adapt to these changes to remain relevant. This is especially important as they try to attract the growing buying power of younger generations. In conclusion, the future trajectory of the insurance market hinges on a nuanced understanding of these evolving trends. By embracing technology-driven solutions and catering to the preferences of an informed, tech-savvy generation, insurance companies can establish a strong presence in the constantly changing market.

There is a growing need to review approaches to insurance pricing such that they continue to serve the public interest. This need for a review of insurance pricing principles has been highlighted by three overarching themes. Firstly, community expectations, which are a function of social factors and society, evolve over time. The community has always expected high standards of conduct from financial institutions including insurers, and increasingly expects institutions to explicitly consider the perspectives of an increasing number of distinct and different customer groups. Community expectations regarding the pricing of insurance products, particularly around transparency and affordability, are topical, with an increasing onus on companies to explain and justify insurance pricing for different customer groups or individual customers. At the same time, inflation and other factors are driving up claim costs, and insurers must consider this in pricing products if they are to remain financially sound to pay claims when they are called upon. Insurers alone may not be able to fully meet the expectations of every stakeholder group in all situations. There are tensions, limitations and trade-offs involved with needs of different stakeholders which need to be considered, which we discuss in this paper. Secondly, recent regulatory interventions in the insurance industry have highlighted issues in established pricing practices, which have not met customer and community expectations. Regulators in Australia and overseas have introduced stricter requirements for insurers to safeguard consumers’ interests such as the introduction of product design and distribution obligations in Australia1 and the consumer duty obligations in the UK2 . Regulators have conducted reviews into insurers’ pricing practices which uncovered several shortcomings in how insurers met their pricing obligations towards customers3 . Thirdly, the rapid advancement of technology and data capabilities has led to more complex data processes, models and additional considerations which have introduced layers of complexity into pricing decision-making processes. These technology and data advancements could disrupt the balance among the diverse objectives of different stakeholders. Pricing decisions now carry a greater level of intricacy, requiring both risks and controls to be carefully reviewed. In this context, insurance pricing and its feedback loop becomes more crucial than ever to align pricing approaches with evolving values of transparency, fairness, and a customercentric focus. This alignment will consider the varied interests of stakeholders, reflecting a collective commitment to fairness and balance. This Research Paper has been written to provide a thought stimulus for professionals working in insurance, including actuaries, with responsibility for and oversight of pricing-related functions. It discusses six principles we suggest be considered in a pricing process. The six principles are not intended to serve as the definitive list that must be considered, although it is important that each business has a set of principles that are well articulated, understood, applied and monitored to ensure there is strong governance. Each business situation is unique, and professionals should continue to use their best judgment regarding the relevance of the principles presented in this paper to their situation and the extent to which other factors exist.

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.

This document is intended as a guide to assist life insurers with determining what data they could collect for their portfolio having regard to community expectations, privacy, and other considerations to inform their understanding of product sustainability. The document is intended to be useful for all life insurance practitioners.

The Institute strongly supports the Government's objective to maximise the benefits of genetic testing while ensuring consumers can access affordable life insurance and the life insurance industry is sustainable. The Institute urges for key protections to be part of any legislative intervention, including setting financial limits below which applicants are not required to disclose predictive genetic test results and a mechanism to periodically review policy settings.

The Institute welcomes the opportunity to provide feedback to the Commonwealth Government COVID-19 Response Inquiry and provides observations of Australia's mortality experienced during the pandemic and experiences to be improved including communication and financial assistance.

The Institute has a strong record of engaging on issues of discrimination in insurance pricing and underwriting and the impact of mental health and other health conditions upon the availability of insurance

Developed with the Australian Human Rights Commission, this resource provides guidance on complying with federal anti-discrimination legislation in relation to use of artificial intelligence in insurance pricing and underwriting decisions.

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.

The Institute is supportive of the proposed changes to integrate AASB 17 with the exception of those impacting Friendly Societies. The draft standards will require some friendly societies to dual report on an APRA AASB 17 basis and on an ASIC AASB 17 basis. The Institute believes this is unjust and constitutes too high a regulatory burden upon friendly societies. Additional feedback from a general and life insurance perspective is outlined below; feedback from a private health insurance perspective has been provided separately.

The Actuaries Institute has launched its latest Green Paper, titled Aged Care Funding: Assessing the Options and Implications. The Green Paper, commissioned by the Institute and written by actuaries Gillian Harres, Andrew Matthews, Hadyn Bernau and Kylie Hogan, calls for a considered conversation about funding of the Aged Care system.

This paper looks at a number of ways Covid19 mortality has been measured around the world and in Australia. We then take a closer look at the impact of the whole Covid19 experience (including border closures and other non-pharmaceutical measures) on the mortality experience of Australia during 2020. And finally, we take a brief look at the impact of Covid19 on long term illness, based on studies from the US, the UK and Denmark. An important way in which the impact of Covid19 on mortality can be measured is by looking at the total deaths from a population and comparing them with some measure of expected deaths (either deaths in recent years, or some more sophisticated projection). This information is not available for all countries, but for many countries shows that the impact of Covid19 on mortality has been higher than the reported Covid19 deaths. In Australia, by contrast, because Covid19 outbreaks and deaths have been very low in comparison with the rest of the world, we can see the effect of border closures and other non-pharmaceutical measures. Overall, Australian mortality has been much lower than our model predicts, with particularly lower deaths from all forms of respiratory diseases. In other countries, a significant number of those who contract Covid19 stay ill with a wide variety of long-term symptoms including organ damage, neurological issues and psychiatric issues. The longterm morbidity implications for countries which have had significant outbreaks are likely to be material.