Past event content

2 CPD Points

Value-Based Healthcare; What is it and How can Actuaries play a role?

Get an introduction to value-based care, a value-based care framework and delve into barriers to implementing value-based care, lessons from other parts of the world and Actuaries and value-based care.

1 CPD Point

Best Practice Catastrophe Model Evaluation

This session aims to provide a best practice overview and guiding principles for catastrophe model evaluation and validation that is useful for end users.

2 CPD Points

Best Practice Catastrophe Model Evaluation (video)

Watch the recent presentation, for actuaries seeking to gain insight into catastrophe model evaluation.

1 CPD Point

Value-Based Healthcare; What is it and How can Actuaries play a role?

Download the slides.

2 CPD Points

The Critical Role of Actuaries in the Transition to a Low-Carbon Economy

This session brings insights from board members, leading actuaries, global thought leaders and general insurance experts to challenge the status quo and provide inspiration for how the role of the actuary will evolve in coming years.

2 CPD Points

International Women’s Day Celebration Event 2025

Watch the recent recording of our recent International Women’s Day Celebration Event.

2 CPD Points

Superannuation Tax Reform: Discussing Sensible Changes for a Fairer System

The Australian superannuation system delivers considerable benefits, including a financially secure retirement for an increasing number of retirees. However, a range of taxes on contributions, earnings and benefits make the system complex in a variety of areas. In this session, the Authors of the Institute’s Discussion Paper on Superannuation Tax Reform present an option for significant tax reform, comprising of several elements and which together as a package are suitable for the major structural trends in coming decades. This option is deliberately ambitious and has been written to provoke debate on what changes are needed for the future. The Actuaries Institute and the Authors welcome feedback on the reform package covered in this Discussion Paper, which will ultimately inform an update to the Institute’s public policy position. The goal is a retirement income system that is clear in its objectives, simpler, more efficient, delivers adequacy, and enhances equity across and within generations.

1 CPD Point

Superannuation Tax Reform: Discussing Sensible Changes for a Fairer System

2 CPD Points

Bridging the Gap: Actuaries and Banking

Actuarial skillset is extremely suited to work in banking dealing with risk and uncertainty, complex products and application of quantitative models. In this session we delve into the experiences and lesson learned by a panel of actuaries who apply their actuarial skillset in banking. The panelists with diverse background and experience and brings a unique perspective. Anyone with an interest in working in the banking sector can benefit from understanding some of the challenges, pathways and benefits of making this transition.

2 CPD Points

Empowering Actuaries with AI and Data Science

In today’s rapidly evolving landscape, the integration of AI and data science into actuarial work is transforming how actuaries approach risk, analytics, and decision-making. This session will explore practical, real-world applications of data science that are already enhancing the actuarial toolkit. We will showcase cutting-edge techniques for improving predictive accuracy, optimising processes, and providing deeper insights for strategic planning. Additionally, we will introduce two essential learning resources designed specifically for Australian actuaries: the Actuaries' Analytical Cookbook and the AI and Data Science Learning Resource. These resources provide hands-on tools, frameworks, and educational pathways that empower actuaries to thrive in data science roles, bridging the gap between traditional actuarial methods and modern analytics.

2 CPD Points

Mandatory Climate Reporting is Here: Are You Ready?

The introduction of mandatory sustainability and climate disclosure requirements accompanied by independent assurance reports represents a significant shift in reporting in Australia. With Treasury Laws Amendment (Financial Market Infrastructure and Other Measures) Bill 2024 passing the senate, it is now undeniable that Australia’s largest corporate entities will face elevated corporate reporting and transparency requirements for reporting periods beginning on or after January 2025. Additionally, APRA and ASIC’s expectations as well as investors and policyholders continue to evolve. A panel session focused on covering: Australian reporting and regulatory requirements including: The latest on the Sustainability legislation, ASRS and related Assurance Standards Timeline for compliance Focus areas of ASIC and APRA Focus areas of Directors What risk/finance/actuarial professionals should be doing to prepare for the implementation of the mandatory Australian Sustainability Reporting Standards (ASRS) The panelists will discuss: the key changes in the final standards; what insurers should be doing to prepare for implementation (high level roadmap) and what this means for actuaries (e.g. scenarios analyses) Primary amendment which mandates two scenarios, key ASRS requirements for scenario analysis, how scenario analysis is used to inform strategic planning/assess climate resilience and what is needed to effectively quantify the impacts of climate-related scenario analysis.

1 CPD Point

Mandatory Climate Reporting is Here: Are You Ready?

2 CPD Points

Pricing and Reserving For Natural Catastrophes

This Insights session is brought to you by the Natural Perils Working Group; a recently formed group sitting under the General Insurance Practice Committee. This introductory session will explore key considerations and approaches for natural perils pricing and catastrophe reserving. Come along if you would like to learn more about pricing and reserving techniques for natural perils and catastrophes, or if you are a current practitioner looking to brush up on your toolkit.

1 CPD Point

Pricing and Reserving For Natural Catastrophes

2 CPD Points

The Artificial Actuarial Team

How might the actuary of the future work alongside teams of artificial actuaries? Join us for an exciting live demonstration of an artificial actuarial team in action. This session will showcase how artificial actuaries, each with diverse specialities, can collaborate with human actuaries to complete actuarial tasks. Jared will demonstrate how artificial actuaries can understand and apply relevant contextual information, utilise various tools and applications, and provide and act upon feedback. This will all happen under the watchful eye of a human actuary. Additionally, Jared will highlight why actuaries are uniquely positioned to drive AI adoption and capitalise on the opportunities it offers. This session will underscore the critical skillsets that actuaries possess, which are essential for the successful integration of AI.

1 CPD Point

Risk Margin Survey Results

2 CPD Points

What happened to My Health Record? Opportunities for improved health data sharing in Australia

The Federal Government’s Strengthening Medicare Report sets out an expansive agenda to improve healthcare in Australia through blended care pathways, supported by investment in better use of digital technology to share patient data. But the My Health Record system that underpins part of this plan has existed for over 10 years, has seen $2bn in investment and is still considered, to date, unsuccessful. This paper explores the reasons for those failures but also the possibilities for health and health actuaries should further investment in this system prompt the progress and growth long desired. With the Strengthening Medicare Report also putting the role of private health insurers in primary care back on the agenda, the presentation will also explore the current landscape and sentiments around private health insurers’ involvement in this area and the benefits to consumers of an appropriately safeguarded but better integrated data sharing platform.

2 CPD Points

AI in insurance and insuring AI: Navigating regulations, risks and opportunities

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: 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. 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. 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.

2 CPD Points

(Re)insurance for the Greater Good

]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

2 CPD Points

Joint Extremes of Precipitation and Wind Speed

The compounding effects of heavy rainfalls and strong winds can lead to severe disasters, resulting in catastrophic losses. This paper presents a novel approach to modeling joint extreme climate events involving precipitation and wind speed. A case study is undertaken, utilizing data gathered from weather observatories spanning across New South Wales, Australia. In terms of methodology, we propose an automated threshold selection method and implement an automated declustering technique to address inherent challenges in applying extreme value theory to a substantial number of datasets. Remarkably, these methodological advancements are applicable to various other forms of joint climate extremes. Furthermore, we introduce a proxy derived from these joint extremes and create a heatmap to identify any significant trends of joint heavy rainfalls and strong winds. This proxy offers a refined understanding of the compounding effects of joint extremes and holds the potential to provide valuable insights for pricing insurance products.

2 CPD Points

Optimal Illusion – A look at the practical limitations of insurance price optimisation

Price optimisation in insurance seeks to modify premiums away from risk cost in ways that maximise business objectives, such as increasing profit while achieving a target volume. Knowledge of customers’ price sensitivities can lead to sophisticated approaches to optimise premiums. While the practice has attracted some debate, it is generally accepted as effective. However, significant uncertainties and complexities arise on more careful analysis. Issues with model inaccuracy and complexities with multi-year impacts mean that establishing superior performance is less clear. This paper builds on existing research by exploring the situations where optimisation approaches can potentially struggle: • How do strategies play out over multiple years, and what is the impact on a portfolio’s price sensitivity over time? • How do nonlinearities in modelled demand curves, such as those induced by link functions, affect optimisation? • What are the practical impacts of model uncertainty on performance? • How do strategies fare in situations where customer price sensitivity can vary year to year? • How important is random price testing to maintaining accurate demand models? The paper will look at theoretical and simulated results, with an emphasis on understanding the robustness of standard optimisation approaches under plausible uncertainty assumptions on a multi-year basis.

1 CPD Point

Plenary 2: Knowing your Risk can Change your Future: the fight against hereditary disease

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.

2 CPD Points

General Insurance Reserving: Robust statistical process or artisanal cottage industry?

Our profession's move into sophisticated data science was led by GI practitioners taking techniques developed/implemented for pricing to much wider areas and applications. Yet GI claims liability estimates are largely made using techniques and processes that were developed in the 1980s. At the time, spreadsheets were a new thing and appeared to be, and indeed were by the standards of the day, excellent tools for implementing the techniques. This situation no longer pertains. We argue that modern statistical and machine learning techniques, combined with well documented research specific to the use case, require the profession to move on from traditional approaches. The many benefits can include: • more statistically robust and accurate estimates; • more flexibility and efficiency of model specification (and variation/exploration thereof); • greater automation of and statistical basis for parameter estimation ; • separation of data from model logic; • better process control and documentation; • improved collaboration. We also discuss common arguments against moving away from spreadsheet-based artisanal processes, such as their flexibility, accessibility to non-coders and perceived adequacy. In addition to outlining the need for, and value of, wholesale change in the profession's approach to claims reserving, we explore what changes are necessary to professional standards, guidance and the education system in order to assist practitioners make this change. The work is based on the authors’ experience in designing, building, operating and reviewing reserving processes, as well as interviews with a number of senior reserving actuaries.

2 CPD Points

Autonomous Reserve Segmentation: An ML Clustering Framework

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.

1 CPD Point

Why You Should Not Trust Interpretations in Machine Learning

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.

2 CPD Points

AASB17 in PHI - how's it gone

An overview of how implementation of AASB 17 for the health insurance industry has gone. Where was the conflict? Where were the tears? Where were the happy hugs? With the standard now in-force for the entire industry, I will comment on: • The path taken to where we are now. • How did the implementation ahead of the first external reporting (APRA returns for 30 September 2023) go? How did it all go down? What went well What went badly Lessons for the future • What the public accounts have to say about what is being implemented. What level of consistency is there? Where is there divergence? What is the range of the divergence? Differences between large/small or profit/non-profit? Are differences reasonable and expected? • Where did actuaries get caught out? • Next steps for the industry

2 CPD Points

Non-Discriminatory and Fair Pricing in Insurance: Bridging Research with Practice

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.

1 CPD Point

(Re)insurance for the Greater Good

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

2 CPD Points

The mental illness pandemic and its impact on lifestyle: a deep dive into the effect on diabetics

A logistic regression model was used to estimate how much more likely a diabetic with a mental health condition is to have an admission than a diabetic without a mental health condition after adjusting for a robust set of risk factors. These results indicate that diabetics with a mental health condition were 48% more likely to be admitted and 45% more likely to be admitted for a high costing admission than a diabetic without a mental health condition. In addition, these diabetic members were 14% more likely to be admitted for a diabetes-related admission and 7% less likely to be adherent to their diabetic medication. This illustrates the impact of mental health conditions on total costs, in-hospital admissions and on the management and control of diabetes. Causal inference refers to the process of drawing a conclusion that a specific treatment was the cause of the observed outcome. A causal forest model was used to determine the causative relationship between diabetics developing a mental health condition and the impact on scheme cost, adjusting for appropriate confounders. Results showed that developing a mental health condition would increase the total cost of diabetic members by 7%, increase costs in-hospital by 11% and increase total costs excluding spend on mental health related claims by 4%. Furthermore, developing a mental health condition has a greater causative impact on in-hospital costs for diabetics with progressed disease compared to those in the preliminary stages of their disease. Understanding these interactions between mental health conditions and other chronic conditions allows us to appropriately tailor disease management programmes and optimise risk management strategies with the aim of reducing scheme costs and managing premium increases.

2 CPD Points

Non-Discriminatory and Fair Pricing in Insurance: Bridging Research with Practice

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.

2 CPD Points

Qualitative Assessment of Complex and Interacting Climate Risks

We traditionally quantify climate change risks as a function of the risk determinants of hazard, exposure, and vulnerability. Traditionally, insurers have been concerned with the built environment domain, focussing on assessing the damage to properties and buildings from natural disasters. Many practitioners are extending climate risk assessments to other domains to look at climate risk more holistically, as climate change does not only impact the built environment, but also the social, natural, and economics domains. But there are limitations to only relying on a quantitative assessment as climate change risk is extremely complex and interacts both internally between the determinants of risk, and externally with many other risks. This can lead to cascading and compound events with widespread systemic risk impacts. For example, vulnerabilities in one domain can stem from multiple hazards, leading to exposures in other domains, whilst exposures that change over time can create changing vulnerabilities across domains. Hazard interactions from disasters may cause feedback loops that lead to untenable capacity to support social, economic, natural and built domains. A qualitative risk assessment can help identify deficiencies in quantitative modelling and suggest improvements for future risk assessments. Our methodology for qualitative assessment refers to reports aggregated from community interviews, which involves decision-makers, local officers, emergency response officers, and other stakeholders. The methodology combs through the main conclusions from the reports to form our basis for the interactions between hazard, vulnerability, and exposure under the four domains (built, social, economic, and natural). The confidence of the interaction increases where there are multiple instances of the same interaction being noted across different reports, or sometimes across similar themes within the same report. The output from our qualitative assessment are multiple mapping diagrams that show the interactions captured within the reports within and between domains. We then draw conclusions from the mapping diagrams, which can be then used to supplement the quantitative risk assessment and identify gaps for future assessments.

1 CPD Point

Plenary 7: There When Needed - the promise of General Insurance

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?