The intervention from APRA in December 2019 and into 2020 to drive changes to individual disability income insurance (IDII) products has helped to drive the opportunity for the insurance industry to reinvent disability insurance for its customers. APRA has flagged that it has concerns with other products not just IDII. A more holistic view must be taken to the development of a new product design to address the underlying issues and to ensure that protection can be provided to consumers in the future and in a sustainable manner.

In the short term, insurers need to perform rapid product development and re-pricing to remove agreed benefits from product ranges and anticipate APRA’s final guidance on disability income products (planned for June 2020 with implementation in July 2021). In making these changes, insurers will be required to quickly respond to associated changes in consumer and adviser behaviour.

This presentation, jointly presented by Deloitte and Montoux, will discuss:

• The future of disability insurance, exploring what it may look like in future based on insights collected from the industry through the Shifting Gears workshops run by Deloitte and Montoux.
• The potential for a transformational disability insurance product, and how to approach this using Human Centred Design to collaboratively meet customer needs and address incoming product change requirements.
• The application of immediate product and process changes needed. This includes executing system changes, consideration of strategies and tools to support rapid re-pricing and test price elasticity and lapse/retention modelling, and analysis of the impact of bundling of products.

On request of the Superannuation Practice Committee (SPC), a small working group of actuaries (Tim Gorst, Vivian Dang, Matt Burgess, Taleb Hassan) have developed a presentation to explore the use of risk based scenario analysis in developing an internal risk-based capital position for Australian Super Funds.  More specifically the working group has explored the following core question “Is there a pragmatic way that a set of operational risk scenarios can be both parameterised and then aggregated to infer an internal operational risk capital position for an Australian Super Fund?”. 

By way of context, “tail” related loss data for Australian Super Funds are generally unavailable making a risk based capital model based on historical (more extreme) loss data very difficult to construct.  As such the potential benefits to a Board (particularly in relation to non-financial risk management) in determining and regularly reviewing their own internal risk-based capital position requires an alternative method to ensure risk and internal capital remain linked.  The alternative method suggested in this presentation is management sourced scenarios aggregated together into an internal capital position using relatively simple statistical techniques.

The presentation hopes to begin a discussion which could lead to a more developed paper outlining a relatively simple fit for purpose technique that could be deployed not just for super funds but for other industries wanting to determine a simple internal risk based capital position in a data scarce environment.  The presentation will be split into three parts (1) Overview and high-level context, (2) Approach and challenges to using multiple scenarios to infer an internal capital position, and (3) a Worked Example.  

A common question asked of insurance professionals is whether a rating factor ought to be permitted for price setting. One then often falls back on a set of heuristics, for example, is the factor commonly used in the market, does it predict well, would people generally expect it to be used, or is it visible to customers. However, the underlying principles of such intuitions are not necessarily appreciated or understood.

In this paper, we draw on contemporary ideas in procedural and distributive justice to decompose the classical notion of risk into several components that in turn allow development of semiformal criteria by which rating factors may be evaluated. We hope that this new set of conceptual tools will allow practitioners to reason about ethical questions surrounding pricing systems with greater clarity.

Objective: The purpose of this paper is to embrace scenario planning for resilience and to enhance capital management in “Private Health Insurance”.

Motivation: So we create an environment where good alternatives spark lively debate, illuminate important nuances and generate commitment. There is rarely one “right” answer.

Key Issues:

• Scenario Planning – What does good look like? We examine the characteristics of good scenario processes and good scenarios. We then explore this in the context of Private Health Insurance.
• Affordability Scenario – Why prepare for critical uncertainties around affordability? We explore the affordability factors that may threaten the ability of PHI to operate successfully. This can then test the viability of current strategies by exposing assumptions and uncertainties. Numbers help add a scaling and quantum to surface what’s important in each scenario.
• Capital Stress – How to allow for adverse events? Here we explore the proposed capital standard changes with a focus on the implications of prescribed adverse events.
• Potential Challenges: A focus on debating the likelihood of a scenario rather than exploring multiple views. There is always more than one scenario of the future. A single view is a forecast.

Conclusion: What’s success look like?

The regulator’s prescribed adverse stresses are well understood.

More importantly, that scenario analysis generates the ability to ask questions on:

• Awareness: What issues, trends and implications catch your attention? (better able to see different futures unfolding).
• Development: What are the implications of the scenarios presented and what capabilities are required? (better prepared to act).
• Implementation: What strategic decisions or initiatives could we take today that would improve the chances of a preferred scenario occurring? (more ready to absorb disruptions resiliently).

It is important for superannuation members to understand the risk of a particular investment option or portfolio they are investing in. As a result, in addition to disclosing the investment performance, it is also important to disclose the risk of such investment.

The main risk metric currently disclosed to members is the Standard Risk Measure (SRM) which only focuses on losing money in any year. Given superannuation is a long-term investment, a critical risk is that the actual retirement outcomes achieved fall short of expectations. To address this risk, we are proposing the introduction of a Long-Term Risk Metric (LTRM) that could potentially be used alongside the SRM. It would show the risk of not meeting a certain long-term performance objective which reflects the risk of a member not efficiently meeting their retirement income goals.

Discussions with Treasury, APRA, ASIC and industry representatives have continued to show that there is support for the development of such long-term risk metric. Since the issue of our first discussion paper in 2017 through the Actuaries Institute, the working group has been progressing with further development that incorporates views from industry representatives and implications from recent regulatory changes.

This presentation will provide an overview of the LTRM developed to date and outline some key issues that are critical for consideration. The aim of the working group is to develop a LTRM that can be widely accepted by the industry and used as one of the core metrics for consumer disclosure purpose.

Voice analytics is a relatively new technology, particularly when it comes to being used in the insurance space. At its core voice analytics is simply the ability to search through audio data to identify the unstructured data contained within to analyse patterns and themes contained. It uses a mixture of semantics and phonetics expertise, syntax and Natural Language Processing activities combined with statistical modelling.

In late 2019 TAL partnered with Deloitte to deploy Voice Analytics over their sales calls enabling 100% of its phone-based calls to be actively reviewed through TAL’s quality assurance model and program.

Voice analytics can also be used in the claims space to understand how engaged an injured work is for example. By coupling with other claims data there is potential to identify when claims are starting to go off track and when new interventions are required.

In this presentation we will explore some of the current and emerging applications of Voice analytics.

The disability income insurance industry in Australia has been adverse claims experience over the last few years. More recently, there has been an increased focus from the regulator requiring insurers to consider implementing changes to ensure the stability and sustainability of Individual DII products in the future. There is a general sentiment in the market that the design of the disability income insurance product at present does not adequately support the customers' journey back into gainful work in Australia’s modern economy. As disability income insurance products are offered in a number of markets around the globe, we conducted research into how the Australian products differs from the disability income insurance products offered in three markets overseas, namely UK, US, and South Africa.

We have now also considered what learnings that can be taken from similar products offered in Australia by General Insurers. Workers compensation and compulsory third party products both offer income replacement benefits. What can be learned from the management of these products that can be applied to Australian DII?

In this presentation we will share with you:

• A brief history of the evolution of the disability income insurance.
• Structure and key types of the disability income insurance products offered.
• Key differences in the definitions and types of cover offered.
• Differences in the range of ancillary features on offer.
• Levers available to insurers to control claims costs.
• A comparison of the management of Australian DII and its General Insurance counterparts.

We will conclude by discussing key challenges that face the Australian disability income insurance market and what changes we may expect in the products going forward to ensure the sustainability of the product.

Australian households hold a large part of their wealth in the form of housing. Reverse mortgage products are designed to help households with accessing their housing wealth for a better living standard in retirement without selling and moving out. Hence, economic theory suggests that these products should be popular. However, the demand for reverse mortgages remains very low in Australia and internationally. While previous studies have focused rational factors in explaining this ‘reverse mortgage puzzle’ (e.g., bequest motives, debt aversion, financial illiteracy), we conduct an experimental survey to analyse how behavioural factors, in particular, mental accounting and framing via narrow bracketing influence the demand for reverse mortgage products. We identify strategies for how to overcome these behavioural barriers. Our results will help consumers to understand the products better and assist the financial services industry in designing, promoting, and selling reverse mortgage products.

• We are on the cusp on unprecedented discovery about who we are and where we are headed.
• Life insurance as a public good cuts across society and tends to closely follow these human discoveries.
• We are in the age of digital, AI, membership connectivity, and increased community voice and standards.
• Though what lies beyond this current horizon.
• Perhaps looking through a different lens might reveal a very new future for life insurance.
• One that protects the very nature of what it means to be human.

This session will provide an update on the amendments to IFRS 17 and their implications.  Topics include: scope exclusions, reinsurance contracts held (and recovery of losses on underlying insurance contracts), effective date (including IFRS 9), transition modification and reliefs, and presentation in the statement of financial position.

Digitalisation and Data Practices Remain a Key Challenge in the Pursuit of Insightful Analytics - Helena Hayes, Travis Short.

Given the upcoming commencement of AASB 17 starting in 2022, it will represent the most significant change to Australian insurance accounting in 20 years. Like all changes, AASB 17 will bring challenges but also opportunities.

For many organisations, a key customer are the owners of the business, many of whom look to the outcomes of the financial statements to measure the value of their investments.

We seek to investigate the key changes that arise from the new standard, with a particular focus on changes that are still under consideration. We also seek to highlight how actuaries can contribute their significant expertise to the solution and seize the opportunity to influence the efficiency of financial reporting process within insurers.

Meteorological data clearly shows an increasing frequency of extreme weather of the type that generates physical damage to property. Examples include the Australian Actuaries Climate Index, the Actuaries Climate Index, and IAG’s report “Severe Weather in a Changing Climate”. However, studies of normalized loss data in Australia and the USA have not shown a corresponding trend.

The American Academy of Actuaries has just issued a report entitled “Actuaries Climate Risk Index” which shows some relationship between weather and losses, but with significant uncertainly. This session will consider what these and other studies are telling us about extreme weather and losses.

It will also consider several additional questions that affect the overall framework for considering what investments should be made in adaptation measures.

• How can adaptation, including better building codes and land use policies, affected loss trends?
• What is the relationship between costs of adaptation vs. the transition risk with regard to decarbonisation?
• What process can be used to inform decisions on strengthening building codes, and how can actuarial concepts help?
• What factors may need to be considered in developing a framework to understand how extreme weather is affecting economic activity?

Actuaries have skills that are very relevant to understanding these issues. This session will draw upon the presenter’s work on the climate and climate risk index projects and also his academic work on studies of long-term trends in extreme event losses in both Australia and North America.

Non–financial risks have had significant financial implications for financial services companies, their investors and their customers. This presentation will focus on:

• What are non-financial risks?
• How can we identify and better manage them?
• Why is knowledge of non-financial risk management practice becoming essential for actuaries working in financial services? 

We will illustrate with industry case studies relating to non-financial risks such as operational, compliance and conduct risks. We will demonstrate approaches to analyse some potential “root causes” of such risks. We will develop a practical set of questions to ask when considering the types of non-financial risks that actuaries come across in a typical “day in the life” working in financial services such as product complexity, model risks and legacy systems.

These will be useful when preparing actuarial reports and for viewing non-financial risks through alternative viewpoints such as the through the “customer lens”.

Included will be some practical and actionable steps actuaries can take to contribute to more effective non-financial risk management in their organisation and for their clients, including:

• Contributing to risk taxonomy and risk appetite discussions.
• Improving key risk indicators/metrics and reporting for non-financial risks.
• Quantifying potential exposures from non-financial risks and identifying key controls to better manage these risks.
• Better incorporating non-financial risks into stress and scenario testing.
• Assisting management with developing sound risk culture and governance.

This session will discuss the challenges and lessons learned from IFRS 17 implementations for the Australian General Insurance and Private Health Insurance market.  We encourage active participation from the floor.  The discussion will include:

• Contract boundary –allowance for new business and cohorts.
• Capital / APRA considerations.

Ways of reducing IFRS 17 complexity.

LPS 117 prescribes the method for calculating the Asset Concentration Risk Charge (ACRC) component of the Prescribed Capital Amount (PCA) for a life company.

In December 2017, APRA issued a letter to all life insurers signalling a review of LPS 117 and suspending discretionary approvals to allow entities to mitigate exposures to non-registered reinsurers for the purpose of calculating the ACRC. The review was to include an assessment of the future use of collateral trust arrangements, including whether they should be permitted for the purposes of LPS 117. An information gathering exercise was undertaken by APRA in early 2018.

In March 2019, APRA issued a further letter inviting input to its review of LPS 117, including a review of asset concentration limits relevant to exposures arising from reinsurance arrangements (with particular consideration of off-shore reinsurers and related party exposures) and the definition and treatment of risk mitigants.

An Institute working group prepared a submission on behalf of the industry to APRA, considering the proposed changes to exposure limits, and providing feedback on the proposed changes to the definition and treatment of risk mitigants. This was in addition to the submissions understood to have been made by individual insurers and reinsurers.

APRA signalled that a new draft LPS 117 would be available for consideration and responses in the first half of 2020.

This presentation will:

• Provide a short summary of the proposed changes in the March 2019 APRA letter.
• Provide a summary of the Institute response.
• Provide a summary of the changes proposed in the new LPS 117 (if available).

Consider the implications of the changes for life insurers, locally licensed reinsurers and off-shore reinsurers, with particular consideration of the definition and recognition of risk mitigants including the use collateral trusts and other instruments as Eligible Collateral to mitigate an ACRC.

Australia is at the start of the journey towards understanding and insuring cyber risks.  Businesses and the government are still trying to work out what the risks are, how big they could be, how to manage them and if insurance provides a valuable solution.  

This presentation builds on the Actuaries Institute Cyber Working Group previously publications to provide an update of the cyber risks facing Australia and how insurers are responding.  Our session this year will bring the perspective from cyber security experts as well as insurance professional.

The session will aim to answer the following questions:

• Where are we at in the maturity of cyber risk and cyber insurance in Australia?
• What are the key risks facing business how big are they?
• Can cyber security really assist with reducing risk?
• How might cyber security data be useful for insurers?
• Are the current insurance solutions and products feasible and sustainable?

Air pollution is a major health risk and a persistent concern in Australian capital cities. Air pollution causes illness, premature death, reduced quality of life, lost productivity, and significant economic costs. In 2006, the NSW Government advised that air pollution caused 643 to 1,446 deaths annually in the Sydney region, and that a ‘conservative estimate’ of the health related financial costs of air pollution in NSW was $706 million to $5,994 million per annum. The 2019 – 2020 bushfire season was the worst on record, and caused abnormal levels of air pollution across Australia. 80% of Australia’s population was blanketed by bushfire smoke at various stages throughout the season. Sydney, Melbourne, and Canberra were all declared to have the worst air quality in the world at different points throughout the period. At least 400 deaths and 3000 hospitalisations can be attributed to the immediate effects of this smoke. 
 
Whilst there are other factors contributing to air quality, natural sources including bushfires is a major contributor. Climate change will exacerbate air pollution in two main ways. First hotter temperatures due to climate change will result in worse air quality by increasing the number of days with high concentrations of ozone. Second climate change will increase bushfire risk; in the future, bushfires such as those over the ‘Black Summer’ of 2019-2020 are 80% more likely because of climate change.  
 
Despite the large health and social costs of air pollution, it is often described as a “silent killer”. This is partly because the impacts of air pollution are not easily attributable or clearly quantifiable, particularly long-term impacts. Furthermore, many of the costs of poor air quality are ‘external’ to the production and consumption processes and fall on the wider community and society rather than the polluter, meaning that these costs are not priced and often ignored. Policy makers should consider all costs and benefits of air quality, including ‘external’ effects, such as air emissions. 
 
The health risks and costs of air pollution need to be better understood by actuaries and policymakers, to better manage the health and economic risks of air pollution. This project aims to:

      1. Quantify the relationship between ambient air quality and excess mortality and hospitalisations for respiratory and cardiovascular issues over the period 2013-2020.
      2. Understand the communities and geographic areas most vulnerable to poor air quality
      3. Holistically assess the health impacts and costs of poor air quality in Sydney
      4. Present scenario analysis based on different concentrations of air pollutants (linked to bushfire severity) and the implications for excess mortality and hospitalisations.

This analysis is valuable in understanding additional health risks, forming adaptation solutions, and preventing severely adverse future health impacts, particularly for those individuals with higher sensitivity to air quality.

Despite ongoing volatility in investment markets, in the context of historically low inflation and cash rates, the Australian superannuation industry continues to grow strongly. There is a long-term trend of growth in superannuation assets relative to GDP, and this growth is expected to continue over the next 20 years (although at a projected lower rate than we have seen more recently).

This presentation will explore two matters at the heart of the growth in superannuation fund assets into the future:

Investment opportunities

Superannuation’s increased share of total financial system assets has led to superannuation funds facing higher expectations for their investment activities, which has led in turn to a greater scrutiny of comparative returns, and peer relative performance metrics. This presentation will explore the implications for funds in how they manage their investment management activities for the best interests of their members into the future.

Evolution in retirement products

Deloitte conducted a survey of major superannuation funds to identify where the industry is currently placed in relation to the development of strategies and products for CIPRs. We will present some of the highlights from those survey results and discuss the perceived benefits and challenges of CIPRs and retirement product innovation as seen by the funds.

Following a 2015 review into out-of-home care in NSW, the NSW Government established the Stronger Communities Investment Unit. The Unit has been tasked with leading cross-government strategy to improve outcomes for vulnerable children and families across NSW. Its work is underpinned by an investment approach, which uses a comprehensive human services data set and investment modelling to determine population groups most in need, in order to guide investment and social policy decision-making.

The investment modelling projects lifetime pathways for all NSW residents under age 25 as at 30 June 2017 (almost 3 million people) and includes key outcomes and interactions with government agencies including child protection, health (hospital, Medicare and pharmaceutical), social housing, justice and welfare. The model also provides a family view, where parents’ outcomes interact with their children’s pathways recognising that changes to the parents’ situations can profoundly affect the pathways of their children.

This session will present the striking key results from the first round of investment modelling, published in the Forecasting Future Outcomes report, a NSW government paper released in July 2019. It will also present subsequent analysis performed on a regional level which is being used to assist with policy development, planning and commissioning. This regional work looked at population groups which the Stronger Communities Investment Unit will initially focus on for system and service responses – vulnerable young children aged 0 to 5, and Children and young people affected by mental illness.  

This presentation draws on the research carried out at the ARC Centre of Excellence in Population Ageing Research (CEPAR) on mortality modelling over the last decade. The emphasis is on methods of most interest to practitioners in life insurance and pensions.

The presentation will introduce continuous-time mortality models highlighting the analytical tractability of the models arising from closed form for cohort survival curves for the affine class of models, consistency between the mortality dynamics and functional form of the survival curve, and stability of parameter estimates.

The models include multi-factor models reflecting level, slope and curvature changes in the mortality curve, and can capture differing trends, volatility and correlations by age. A comparison of fits and prediction using historical US mortality data will be provided with an application quantifying the price of mortality risk using Blackrock CORI indices.

In Australia and much of the world, a vast difference can be observed between the academic literature on decisions relating to retirement provision, and the products available to and decisions made by individuals in planning for retirement. This is reflective of the fact that individuals are illequipped to make the complex financial decisions required of them in managing their retirement finances (Agnew, Bateman et al. (2013); Lusardi and Mitchell (2014)). Furthermore, it indicates the necessity for products to efficiently trade off the complexity of the outcomes modelled in the academic literature, with the desire for simplicity considered necessary by customers and sales agents.

A recent paper by Khemka, Steffensen et al. (2019) investigates optimal investment strategies preretirement and compares them with available products that adjust investment strategies in a deterministic way with age. Assuming risk aversion is known, the paper finds that simple reductions in risky asset allocation with age, as is consistent with many MySuper products offered in Australia, do a good job of replicating dynamic strategies from complex academic models that adjust asset allocation with age and investment performance.

This paper considers a similar issue as that described by Khemka, Steffensen et al. (2019), but from a post-retirement rather than pre-retirement perspective. This increases the complexity of the problem as retirement requires not only addressing the investment strategy but also the drawdown strategy, which both occur in the context of uncertain mortality. Our method involves applying lifecycle modelling following the seminal work of Samuelson (1969), comparing the theoretically ‘optimal’ strategy with that either embedded in current retirement products and various proposed simple rules. Our aim is to establish the loss from applying straightforward strategies, and hence what simple product designs might make suitable candidates to offer in practice. The Australian age-pension is incorporated into the modelling in order to ensure that decisions and product design reflect this vital component of the Australian retirement income system. The work builds on the research of De Ravin, Liu et al. (2019), who used a utility framework to compare a range of drawdown scenarios in an Australian context, but assumed a single diversified investment strategy and did not benchmark against optimal solutions from the lifecycle model.

The International Accounting Standard Board (IASB) is expected to issue an amended version of the new Insurance Contracts Standard, IFRS 17, in mid-2020. The Standard is expected to be effective for reporting periods starting on or after 1 January 2022 and attempts to standardise the measurement and reporting of Insurance contracts, resulting in more meaningful and comparable sets of financial statements. This Standard will represent a significant change to current Australian Insurance accounting and hence will significantly impact key performance indicators (KPIs) that are used by insurers today, both for internal performance management, as well as to communicate the reasons for historic performance, volatility, and future trajectory to investors.

The new IFRS 17 world gives insurers an opportunity to reassess the key drivers of business and how best to monitor them. This presentation considers the impact of IFRS 17 on current metrics, possible new metrics, as well as how the Australian insurance industry and investors wish to provide and utilise information within an IFRS 17 context.

This presentation will look at the non-financial side of ageing and retirement. How do we ensure a happy retirement? How can we predict people who will age happily? It will cover some surprising findings and dispel some myths. It will draw on various pieces of research including a  Harvard longitudinal study, the Blue Zones research as well as books by George Vaillant and Ellen Langer. It will traverse topics spanning mental health, diet and exercise, alcoholism, the impact of community and purpose.

As actuaries we often focus on the financial aspects. As this presentation will show, money is only a small contributor to happiness in retirement. The presentation seeks to broaden our understanding of what our customers are experiencing. It is relevant to actuaries working in superannuation, insurance, investment and technology.

“Data is the new oil” – use of data is central to modern business success and it is no surprise that all four non-state companies to achieve trillion-dollar valuations are technology companies that rely heavily on data. But how can data be accessed? Who owns data? What control do you have over your data? What happens when people do not have enough data assets, like credit or banking history, to access services that increasingly require it? This paper will consider trends in data ownership and some of the implications of these trends.

First, it will look at the implications of the current Australian Privacy Principals. Although they give significant rights to individuals, the degree to which companies are able to comply and the legal interpretation of what constitutes personal data highlight ongoing challenges. Full compliance typically requires sophisticated data management systems and constant vigilance. We look at personal examples of data requests made under the APPs. We will also discuss practices companies are using to comply with privacy rules, including transforming personal data to detailed ‘non-personal’ data.

Second, we explore trends in data portability including recent open banking rules. The intended operation of the rules is to give people greater ability to access, use and redirect data about themselves that is currently held by institutions. This is predicted to enhance competition and innovation. However, when applied as a broader theme across many sectors, there could be significant side effects, particularly around product access for those who are digitally disadvantaged. Balancing the benefits with the side effects will be a significant challenge as these systems mature.

Finally, we discuss recent developments on the data regulation front and the implications for further developments that may significantly affect how companies collect and use data.

The Retirement Income Review is currently undertaking its analysis of the retirement incomes system.  This includes consideration of the objective of the system, roles of the pillars and adequacy.

Ultimately, every dollar of retirement income comes from the contributions of the Australian population, whether self-funded or through the payment of taxes.

Many commentators discuss whether the SG should go up, whether the means test is fair, whether the Age Pension should be universal.  Without an objective of super it is difficult to determine which policy settings are optimal.  The current policy statement (not passed by parliament) to “substitute or supplement the Age Pension” leaves plenty of room for interpretation and could be used to support a universal Age Pension or a heavily means tested poverty alleviation measure.

This paper attempts to contribute to the fact base on this issue, through examining the circumstances under which it is preferable to pre-fund retirement incomes via superannuation versus an Age Pension.  The paper will discuss the necessary conditions in terms of population structure, rates of real return and intergenerational equity issues that determine the relative efficiency of self -funding retirement.

AIA and Vitality have has partnered with Quantium, a globally recognised leader in the development of data-driven insights, to create an algorithm that calculates the risk of developing depression, based on our customers’ circumstances and choices. This could be used to:

• Understand what changes in behaviour or circumstances would make the most difference to depression risk, and therefore help prioritise investment and policy into improving mental health
• Incentivise behaviour that supports mental wellbeing.

This work has involved undertaking the world’s largest and richest study of the link between depression, demographics, health, lifestyle and circumstance through:

• Over 1000 features created and investigated spanning activity, sleep, health status and wellbeing indicators
• 500 million health claim lines over 10 years
• 1 billion biometric readings collected through AIA Vitality, Discovery

The algorithm developed has identified that lifestyle choices represent around a quarter of the depression impact, which can be incentivised for improvement. This can be used to develop programs through AIA Vitality to better engage members and improve their mental wellbeing.

Extrapolating these findings, we estimate that if the Australian population who have less than average lifestyles were able to shift to average behaviours for exercise, sleep and diet were able to live their healthiest lives (potentially incentivised by programs such as AIA Vitality), the national depression incidence rate could reduce from 6% to 4.7%, which is 300,000 fewer depression incidences, leading to 4.7 million working days recovered and saving the Australian economy around $3 billion per annum.

AIA Australia intends to use the algorithm to enhance the AIA Vitality program, to further help customers know their mental health and to incentivise improvements in behaviour around sleep, exercise and diet to support improved mental health outcomes.

By their very nature, Actuaries have always needed to be adept at stepping through the risk and return trade off. More, now than ever before, we are being asked to step up. This time, into the shoes of the customer. Seeing things through the customer lens seems straightforward at first glance. But the real challenge for us is when we are required to provide insight in the form of measurable and fit for purpose metrics reflective of the actual objective(s). This session from the Customer Outcomes Working Group (COWG) provides a taste on what these metrics could look like in the context of recent developments within the Wealth Management industry.

Research suggests that uncertainty about the future is one of the key fears that Australians have when they contemplate their retirement. In addressing this issue, superannuation funds provide technological solutions (called calculators or online tools) to help guide members through their uncertain financial future. However, the current range of tools used to help support decision-making assume a certain world through deterministic assumptions.

While tools of these kind provide good long-term guidance, they often fail to capture the true uncertainty that retirees face and as a result undermine confidence in their results and provide answers which do not consider the full range of risks that Australians face. The tools often lack sufficient data about the member to provide a good gauge to the future.

In this session, we will demonstrate the difference between two custom built superannuation calculators. One that is representative of the current tools used by the industry with deterministic investment returns and one which uses stochastic returns to demonstrate and quantify uncertainty. This will allow attendees to compare and contrast the impact that a new generation of calculator, one which uses stochastic rates, might have on the quality of guidance provided to members. Through this, we anticipate that superannuation funds will be provided the business case they require to make an investment in this space and consequently provide better solutions to help their members.

This presentation will be supported by an information paper and an accompanying stochastic calculator which will be used in a live demonstration to demonstrate the value of these models now and into the future.

• Different machine learning techniques that were tested.    
• The accuracy of the different methods.
• Why some methods provide better results than others and why they predict better than standard actuarial methods.
• Using machine learning to estimate confidence intervals and risk margins for the outstanding claims.

Traditional life reinsurance products in the Australian life market have struggled in recent times, most notably financially, but also in alignment to the needs of the insurer and the end customer. An insurer’s key risks have materially evolved over the past decade, and yet we are still adopting the same reinsurance strategies to manage these risks.

This presentation will explore:

• How an Insurer’s risks are evolving.
• How well do current reinsurance models meet these risks?

Ideas around how an insurer’s reinsurance program might evolve to better enable managing the current environmental head winds and support the business growth opportunities of the 2020’s.

The gig economy has increased rapidly in size and popularity over the past decade with companies such as Uber, Deliveroo and Airtasker becoming household names. According to a recent survey, 13% of working-age Australians have undertaken digital platform work, with 7% having done so in the last 12 months. However, little is known about the economic size or growth rate of the gig economy due to a lack of regular or standardised statistical collections on the subject.

Because it is relatively nascent, there is scope for research on the gig economy’s long-term effects on worker insurance coverage, access to credit, and retirement savings. In this presentation we show how data analytics can be used to fill this knowledge gap. Specifically, we use proprietary banking transaction data and public data to answer the following questions:

• What is the size of the gig economy, and how fast is it growing?
• How is the gig economy impacting existing industry sectors?
• What are the economic impacts of the gig economy on its workers?

Illustratively, we will provide a unique view of the gig economy from a macro and micro perspective. From the worker perspective, we will provide a granular understanding on their lifestyle and financial support through analysis of their spending in comparison to workers in other industries.

It's no secret that with the industry's ongoing losses, the current DI product needs a major rethink to become more sustainable. Actuaries play an integral part in redesigning and pricing these new DI products. Many of the features and benefits of DI seem straightforward on the surface level. However, when diving into some of the key features the picture becomes less clear. Join Swiss Re's specialist panel to learn:

• What actually contributes to a replacement ratio
• How the number of hours worked at Underwriting relate to partial claims
• What the shortfall is with our disability definitions and how these can be improved

This session takes a holistic view and goes into depth how these features are handled during both the underwriting risk assessment process as well as during claims management.

Our UW and Claims specialists at the coal face will explain what works, what doesn’t, what would be downright problematic.

The well-known Black Scholes and Merton (BSM) formula is the solution to a stochastic partial differential equation and was published in 1972.  The BSM formula gives an analytic value for the price of European Call or Put options.  Since then, Cox Ross and Rubinstein in 1979 developed the widely used n-step Binomial Option Pricing Model (BOPM) as a discrete event system for pricing any call or put option.  In the limit of n, their result reproduces the same result as the BSM.

To date nobody has an analytic expression for the variance associated the mean of the option prices produced by either of the models above.  The variance, of any quantity, is of significant importance in Finance and Actuarial Science as it quantifies the risk associated with that estimate of the mean.  In this work we derive an analytic expression for the variance of the call and put option by use of the Cox Ross and Rubinstein approach.

Our analytic expression is verified by computer simulations for a wide range of the parameter phase space.  Particular note is made of the trade-off between the number of simulations run and the fineness of the steps in the BOPM.  Application to some series listed on the ASX are presented to demonstrate the variance in the observed option price.  This has not been able to be achieved previously except by computationally expensive Monte Carlo modelling.

Finally, we demonstrate an advanced application of the variance to the pricing of a capital guaranteed.

Data analytics is a fast-growing area of almost unlimited potential for actuaries to play in. How can we ensure that actuaries have the necessary tools to successfully compete in this area?

This presentation will examine ways that actuarial associations in Australia and overseas are integrating modern data analytics and machine learning techniques into their education programs.

For example, from 2020, the Actuaries Institute launched a new subject, ‘Data Analytics Principles’, into the Actuary program. This subject is being taught by accredited universities. In 2021, the Institute will introduce the subject ‘Data Analytics Applications’ into the Fellowship program. This will be taught by in-house actuarial educators with the assistance of subject matter experts.

Join us to learn about these exciting new subjects and those being offered by actuarial associations around the world.

Personal financial planning have progressed from promoting products to considering the needs and wants of individuals. This has been accelerated by an increase in fiduciary requirements and professional responsibilities placed on advisers.

Financial Advisers need to consider the best interests of the client when providing advice according to the goals and objectives of the client.  However they face a complex challenge to balance the achievability and risk across multiple goals with varied timing and priorities, which is further complicated by the uncertainty of longevity, investment returns, future cash flows, and the complexity of Australia’s superannuation and pension system.

This paper investigate an approach to tackle this challenge using stochastic asset liability management (ALM) techniques commonly used by life and general insurance actuaries. Here we consider multiple consumer objectives as being similar to life insurance liabilities, and derive a dynamic asset allocation strategy to better manage the probability of meeting these liabilities in a personal financial planning context.

In the session we will discuss the financial planning problems to be solved, using examples to demonstrate the application and potential value of using the ALM process to develop goals based financial advice strategies, and ways to engage and communicate that advice to consumers.