Actuaries Institute President David Whittle leads a discussion on the consumer promise of General Insurance. Is the process, payout and the ‘human experience’ of making a claim lining up with the promise made to consumers? Joined by Shez Ford, EGM Consumer at Allianz Australia, and Helen Rowell, David will ask – is it time to rewrite the promise? And what should the new promise look like?

Hear from leading Australian author of thrillers and Non-Executive Director John M Green on the questions you should ask and how you can craft your scenario narratives to better engage management and boards in the risk discussions every organisation needs to have. Joining him in this session is Actuary/Director, Finity Estelle Pearson.

Digitisation can be more than enhancing processes and cutting costs. It’s about creating new way to understand and reach your customer, reshaping business models and upending traditional views of the customers experience. In this session actuary Iwan Juwono, Head of Insurances at Grab Insure Business and Frankie Chan, Head of Programme Value Optimisation, Air & Insurance, Cathay Pacific Airways explore how data science and AI is transforming their businesses.

How can actuaries help families take control of their hereditary risk of disease? Where are the next great scientific, medical, and technological advances coming from in the field of genetics? What do these developments mean for industries like insurance and superannuation, and for actuaries working in the health sector? This session will be chaired by award-winning journalist and former National Medical Reporter for the ABC, Sophie Scott. Speakers are Professor David Thomas, CEO of Omico: the Australian Genomic Cancer Medicine Centre and inaugural Director of the Centre for Molecular Oncology at UNSW, Krystal Barter, founder of Humanise Health and a passionate genomics advocate, and actuary Jessica Chen, as they deep dive into innovations in genetics and bio-tech and analyse the impact on our work as actuaries, key industries and businesses, and the rest of society.

Pricing promises are representations made by insurers to help customers save money when purchasing insurance policies, provided they meet certain eligibility requirements. Over the past few years, developments have prompted general insurers across Australia to undergo reform and transformation due to failures in delivering pricing promises. This was largely initiated by ASIC, which required several insurers across Australia to conduct a review of their pricing practices. This primarily involves identifying instances where pricing promises were not fully delivered, addressing the root causes, and compensating affected customers. We will explore together: • How these pricing promise developments initially began • The launch of the ASIC pricing promises review • The current state of the industry from a pricing promises perspective • Strategies for enhancing pricing practices in the future

In an era where data reigns supreme, data science actuaries aren't just crunching numbers—they're shaping futures! Data Science Applications, as an actuarial Fellowship subject and microcredential, delves deep into modern data science techniques. The subject offers actuaries powerful tools to analyse, predict, and pioneer in this age of information. But how have these tools been implemented in the trenches of traditional actuarial work? By engaging with a panel of former students, this session will unpack the tangible benefits that data science brings to the actuarial table.

The adoption of artificial intelligence (AI) across industries, including insurance, has led to the widespread use of complex black-box models such as gradient-boosting machines and neural networks. Although these models offer enhanced efficiency and accuracy, their lack of transparency has raised concerns among regulators and consumers. To address this, interpretation methods from the growing field of interpretable machine learning have gained attention for understanding relationships between model inputs and outputs. However, while stakeholders may possess a certain level of understanding regarding the limitations of these explanations, there is often a lack of awareness regarding the inherent vulnerability of these methods. This presentation uses an adversarial framework to uncover the vulnerability of permutation-based interpretation methods for machine learning tasks, with a particular focus on partial dependence (PD) plots. This adversarial framework modifies the original black box model to manipulate model predictions for instances in the extrapolation domain, which produces deceived PD plots that can hide discriminatory behaviors while maintaining the prediction accuracy of the original model. This framework can produce multiple fooled PD plots via a single model. By using real-world datasets including an auto insurance claims dataset and COMPAS dataset, our results show that it is possible to intentionally hide the discriminatory behaviour of a predictor and make the black-box model appear neutral through interpretation tools like PD plots while retaining almost all the predictions of the original black-box model. Drawing on the findings, this presentation will offer suggestions and insights for utilising machine learning models in business decision-making. This includes strategies to mitigate adversarial attacks on Partial Dependence (PD) plots (and other permutation-based methods) and responsible practices for using machine learning interpretation tools.

Recent regulatory interventions in insurance pricing have highlighted issues in established 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 Australia and consumer duty obligations in the UK. Further, the regulators conducted reviews into insurers’ pricing practices that uncovered several shortcomings in how insurers met their pricing obligations towards customers. In this context, and with the rapid advancement of technology and data capabilities, what are the responsibilities of insurance professionals, including actuaries, to protect the public interest in insurance pricing? This question was explored by a working group of actuaries. In this session, we will discuss principles for consideration and to inform a pricing process, discuss responsibilities of insurance professionals and share some reference material which may be helpful to professionals working in insurance pricing.

Previous research shows the most pressing question faced by superannuation fund members is how much they need to save for their retirement and how they are tracking against that target. The typical retirement calculator in the industry today relies on deterministic projections and focuses more on showing the projected outcomes instead of guiding members to improve their retirement plan. In this presentation, we will introduce Aware Super’s “My Retirement Planner”, which was launched to Aware Super members in July 2023. My Retirement Planner is a new retirement calculator aiming to help our members get retirement ready. It implemented a Retirement Confidence Score that takes into account investment risk in the projection as the measure to track against retirement goals. This allows the users to explore the impact of different financial decisions on their retirement outcomes in a meaningful way. With a human-centred design as core, the My Retirement Planner was designed to make it easy for members and empower members to make better financial decisions through a ‘play mode’. The play mode allows members to explore what are the implications of different financial decisions on their retirement confidence score: retiring sooner or later, changing their retirement income targets, contributing more or less, and investing differently. We observed encouraging member usage since launch which doubled previous tool in terms of usage and significantly outperformed in completion rate. About 60% of the users used the play mode before completing the journey. About 70% of these members found a way to improve their retirement confidence score. About 30% indicated additional contributions, and 15% of these actioned it by adding contributions following the use of the tool. Out of those making investment option switches, we observed members in cash option were almost 6x more likely to switch out of cash following the use of the tool than those in MySuper default option. These are all encouraging insights that show early success of the My Retirement Planner tool which helps nudge members into making the right financial decisions and improve their financial position leading up to retirement.

The rapidly evolving landscape of insurance in the modern era brings with it a unique conundrum—how do we ensure fair pricing, especially when introducing new products with sparse data? Though long-standing, the principle of fairness and anti-discrimination is complicated by the dynamics of innovative products, evolving consumer behaviour, and the complexities of AI and emerging risks. In the first part of this presentation, Michael will share practical challenges he faced when helping relaunch the startup insurtech PassportCard Travel Insurance after the Covid pandemic forced the hibernation of the business. He will discuss the team's approach to applying established guidance and literature around anti-discrimination for protected attributes such as age and disability, especially where the apparent lack of data requires more diverse thinking. Through real-world examples, attendees will gain insight into practical strategies to navigate these challenges, ensuring product pricing that aligns with both business goals and societal expectations. In the second segment of our session, Fei will review the state of the art of research in this area with an international perspective. She will then respond to the practical challenges shared by Michael with insights and potential solutions. A list of open questions that need further work and collaboration between academia, government, and industry will be summarised and discussed in the end.

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 recent times, the reinsurance market has been going through a hardening phase with substantial price increases (corrections), tightening coverage, and even withdrawn capacity. While it is relatively well understood that the key drivers are post-COVID recoveries, challenging state of the economic, claims activities, and uncertainty associated with climate changes and geo-political risks, the solutions are not obvious, especially for the public sectors. When it comes to natural catastrophe risks, many in the private sector speaks of the language of economic and/or regulatory capital, e.g., ICRC, 1/200, 1/1000, return period, etc. The public sector speaks the language of funding, e.g., taxations, levy, etc. Since (re)insurance is an important form of funding for the government, a hardening (re)insurance market means that the government will face even wider protection gap, delay in infrastructure projects development, bigger risk in economic development, etc. Thera are, however, other public sector solutions available which has proven to be innovative and effective. These solutions help facilitate economic development and increase insurance protection and financial inclusion. In this context, the public sector refers to governments (at sovereign and sub-sovereign levels), state-owned enterprises (SOEs), sovereign wealth funds (SWFs), development banks, export credit agencies (ECAs), multilateral organisations and 'third sector' entities/NGOs. The presentation will conclude with a few case studies. Indicatively, there will be case studies like: (To be confirmed) - Catastrophe bond for Pacific Alliance sovereign earthquake protection covering four countries. - Mexico Hurricane Coral Reef Cover - first insurance coverage to protect a natural asset. - Sovereign catastrophe risk transfer in the Asia-Pacific region – PCRIC - Livestock protection against drought for smallholder farmers - Longevity swap for sovereign pension

FY 2022/23 marked Australia’s cyber wake-up call – Australia experienced the largest breaches in its history, with the personal details of more than 10 million Australians impacted by one data breach alone. In response, there has been a suite of initiatives from government looking to tighten Australia’s cyber security settings, and prepare individuals, corporates and the companies for the breaches that will inevitability come. This has included strong signals from Australia’s corporate regulator that it will look to prosecute those companies who have not adequately prepared for cyber incidents, the development of a new cyber security strategy for the nation, and incorporation of cyber into new prudential standards for APRA regulated entities. Corporate Australia has responded to the ‘annus horribilis’ by increasing its investment in information security, and looked to the cyber insurance market to transform some of the risks faced. In this paper we: • Look at the major changes to the cyber landscape that have occurred over the previous year, and score how well corporate Australia has responded to the cyber wake-up call • Discuss how actuaries can use our unique skillset to address the challenges posed by cyber risk, and add value both in the boardroom and to policy makers by 1) measuring cyber risk, 2) designing solutions to address cyber risk, and 3) quantifying the impacts of cyber risk.

In this paper the author(s) address the effects of shifts in inflation on the work of general insurance actuaries in Australia with reference to: • The types of inflation (economic and superimposed, which are defined in the paper); • How the different types of inflation can affect: o Claim sizes over time; o Pricing o Reserving o Policy design o Asset liability management o Reinsurance • The allowance for inflation in models used by actuaries in general insurance work in Australia; There is also a discussion of the difficulties encountered in recent years in forecasting inflation. Earlier work in the area of inflation and its effects on general insurance in Australia by other Australian actuaries is discussed and acknowledged and used as a foundation for suggestions about further developments in actuarial practice in general insurance.

Artificial Intelligence is having a significant impact on the insurance industry, with rapid development and investment across the value chain. While AI presents opportunities for efficiency and improved service, it also brings new risks and regulatory challenges. We will explore three perspectives on the emerging relation between AI and insurance, with a focus on how regulatory and legislative changes are likely to impact insurers’ own use of AI, change the risk landscape for existing lines and introduce opportunities for new product innovations. We’ll cover: 1. Impacts of emerging regulations and standards on insurance applications: We'll explore the rapidly expanding legislative, regulatory and standards environment. Examples include specific AI legislation in the EU and US, emerging regulations in Australia and updates to existing legislation to explicitly capture algorithmic and AI risks, such as the proposed changes to the Privacy Act 1988 (CMW). Complementing the regulatory development are standards and guidelines on appropriate application and governance of AI, including the ISO 42 group of standards that seek to provide a rigorous framework for system validation and audit, akin to existing standards around Cyber risk. 2. AI-induced risks on existing insurance lines: Here we’ll address the ripple effects of AI on established lines. Examples include the potential for breach of duty claims impacting Directors and Officers insurance, complex changes to liability risk for organisations that include AI in their products and increased risks of privacy and data breaches impacting risk exposures for cyber cover. We'll discuss relevant international developments and examples, including the EU's ambitious Artificial Intelligence Liability Directive, which seeks to update the EU liability framework to make it easier for individuals to bring claims for harms caused by AI. 3. Insurance solutions for emerging AI risks: In this section, we'll cover the potential for insurance products that cover new and emerging AI risks, including existing emerging examples. This includes nascent product-warranty like cover, and cover for consequential losses arising from underperformance of AI models. We'll discuss potential for cover against insurability criteria, and some of the associated likely product, underwriting and claims challenges.

Over the past 20 years, the ageing population has seen an increase in the use of healthcare services. At the same time, costs per service have increased. These factors have driven private health insurers to increase premiums at a faster rate than wage inflation. At face value, this suggests that the affordability of private health insurance has declined over that time and has become less attractive to healthier people who are less likely to benefit from private health insurance. As healthy people lapse their cover, average benefit costs increase leading to higher premiums again, further conflating affordability issues leaving the private health insurance industry in an unsustainable position. While the COVID-19 pandemic saw an increase in participation amongst the young as well as low benefit inflation, these impacts are unlikely to be permanent. This paper seeks to explore what the Australian Private Health Insurance industry might look like under the status quo in another 20 years, and seeks to answer the following: • How will the ageing population continue to affect benefit levels? • How will affordability pressures impact participation, and in turn, insurance premiums? • What impact will Government incentives like the Medicare Levy Surcharge and the Private Health Insurance Rebate have? • Are certain private health insurers likely to fare better over the next 20 years than others? In exploring these issues, the paper aims to provide private health insurers with an understanding of the key risks to the long-term sustainability of their funds and actions that managers can implement in the short-tomedium term to improve sustainability.

Natural disasters are often linked to extensive insurance losses. Their occurrence is rooted in the prevailing climate conditions that facilitate weather extremes, causing socio-economic impacts and damages. Climate conditions, most notably conditions that promote weather extremes, can be expressed as so called “climate indices” – quantities that measure aspects of the planet’s circulation and weather dynamics. Climate indices have broad applications across many fields, first emerging from the scientific community to identify environmental trends in weather dynamics. Due to their versatility and relative simplicity, various sectors have since adopted climate indices into their operations (e.g., emergency services, agribusiness, and financial services). In the context of insurance, climate indices can provide a critical source of information for insurers in quantifying the broadscale geographic risk of natural hazards, and how these are changing with time. Further, climate indices are useful in quantifying the changing behaviour of extreme weather risks – being able to discriminate geographical differences, their frequency of occurrence, and to some extent their intensity. While traditionally the goal of insurance pricing is to set rates against the average cost of annualised losses, this approach largely ignores changing climate conditions caused by anthropogenic greenhouse gas emissions. This can lead to a misunderstanding of the role climate change and natural variability has on the interannual volatility of claim size and frequency, as the focus can be biased towards recent experience. To prevent this, Suncorp has developed a suite of climate indices based on observational data, output from climate models and the latest research from the scientific community. We use these indices to inform our view of developing climate risk – specifically, the natural hazard events which cause the largest insurance losses, i.e., flood, bushfires, tropical cyclones, hail, and storms. In this session, we demonstrate this practice and how we are using AI to expand the utility of climate indices in quantifying expectations on weather extreme claim size and frequency.

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.

The rapidly evolving landscape of insurance in the modern era brings with it a unique conundrum—how do we ensure fair pricing, especially when introducing new products with sparse data? Though long-standing, the principle of fairness and anti-discrimination is complicated by the dynamics of innovative products, evolving consumer behaviour, and the complexities of AI and emerging risks. In the first part of this presentation, Michael will share practical challenges he faced when helping relaunch the startup insurtech PassportCard Travel Insurance after the Covid pandemic forced the hibernation of the business. He will discuss the team's approach to applying established guidance and literature around anti-discrimination for protected attributes such as age and disability, especially where the apparent lack of data requires more diverse thinking. Through real-world examples, attendees will gain insight into practical strategies to navigate these challenges, ensuring product pricing that aligns with both business goals and societal expectations. In the second segment of our session, Fei will review the state of the art of research in this area with an international perspective. She will then respond to the practical challenges shared by Michael with insights and potential solutions. A list of open questions that need further work and collaboration between academia, government, and industry will be summarised and discussed in the end.

FY 2022/23 marked Australia’s cyber wake-up call – Australia experienced the largest breaches in its history, with the personal details of more than 10 million Australians impacted by one data breach alone. In response, there has been a suite of initiatives from government looking to tighten Australia’s cyber security settings, and prepare individuals, corporates and the companies for the breaches that will inevitability come. This has included strong signals from Australia’s corporate regulator that it will look to prosecute those companies who have not adequately prepared for cyber incidents, the development of a new cyber security strategy for the nation, and incorporation of cyber into new prudential standards for APRAregulated entities. Corporate Australia has responded to the ‘annus horribilis’ by increasing its investment in information security, and looked to the cyber insurance market to transform some of the risks faced. In this paper we: • Look at the major changes to the cyber landscape that have occurred over the previous year, and score how well corporate Australia has responded to the cyber wake-up call • Discuss how actuaries can use our unique skillset to address the challenges posed by cyber risk, and add value both in the boardroom and to policy makers by 1) measuring cyber risk, 2) designing solutions to address cyber risk, and 3) quantifying the impacts of cyber risk.