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Scheme : Linkage Projects
Australian State/Territory : NSW
Research Topic : FALLS RISK ASSESSMEN
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  • Active Funded Activity

    Linkage Projects - Grant ID: LP190100732

    Funder
    Australian Research Council
    Funding Amount
    $392,445.00
    Summary
    Better communication to solve the under-saving, under-spending puzzle. This project expects to develop evidence-based communication tools that promote life-time financial security, specifically investigating the puzzling and harmful tendency of people to under-save while working and under-spend while retired. To achieve this goal, it will design and experimentally validate innovative boosts to superannuation communication including income projections and goal-setting targeted at common misconcep .... Better communication to solve the under-saving, under-spending puzzle. This project expects to develop evidence-based communication tools that promote life-time financial security, specifically investigating the puzzling and harmful tendency of people to under-save while working and under-spend while retired. To achieve this goal, it will design and experimentally validate innovative boosts to superannuation communication including income projections and goal-setting targeted at common misconceptions and biases. It will use new structural modelling techniques to measure welfare changes. The expected outcomes are rigorous explanations for the saving-spending puzzle, and robust communication strategies for superannuation funds that will benefit workers and retirees by raising financial capability and confidence.
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    Active Funded Activity

    Linkage Projects - Grant ID: LP160100956

    Funder
    Australian Research Council
    Funding Amount
    $169,000.00
    Summary
    Governance and the investment performance of not-for-profit endowments. Governance and the investment performance of not-for-profit endowments. This project aims to examine the relation between performance and governance for Australian not for profit (NFP) endowments. The not-for-profit sector now accounts for over 4 per cent of the gross domestic product (GDP) (almost $43 billion) and employs volunteers who contribute an additional $14.6 billion in unpaid work. Little research has been done on .... Governance and the investment performance of not-for-profit endowments. Governance and the investment performance of not-for-profit endowments. This project aims to examine the relation between performance and governance for Australian not for profit (NFP) endowments. The not-for-profit sector now accounts for over 4 per cent of the gross domestic product (GDP) (almost $43 billion) and employs volunteers who contribute an additional $14.6 billion in unpaid work. Little research has been done on the investment performance of the endowments held by NFPs, even though this is an important contributor to their revenues. Expected outcomes include a publicised set of principles and periodically updated index of endowment governance quality, and attendant improvement in NFP investment management.
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    Funded Activity

    Linkage Projects - Grant ID: LP130100723

    Funder
    Australian Research Council
    Funding Amount
    $232,449.00
    Summary
    Modelling claim dependencies for the general insurance industry with economic capital in view: an innovative approach with stochastic processes. This project will develop and enhance multi-dimensional models used to describe and assess the risks borne by general insurers. These innovative methods, which will be directly applicable by the industry, will strengthen the efficiency and the safety of the Australian economy.
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    Funded Activity

    Linkage Projects - Grant ID: LP0562455

    Funder
    Australian Research Council
    Funding Amount
    $144,888.00
    Summary
    Development of a Multi Threat Risk Assessment Model for Critical Infrastructure Using Scripted Agent Computer Technology. Current risk assessment paradigms are not suited to the control of catastrophic events such as terrorism. An advanced approach to risk assessment will be developed in this project for rare high impact events such as bomb blasts, where critical infrastructure is threatened. A new software platform based on scripted agent modelling will be constructed that will allow for state .... Development of a Multi Threat Risk Assessment Model for Critical Infrastructure Using Scripted Agent Computer Technology. Current risk assessment paradigms are not suited to the control of catastrophic events such as terrorism. An advanced approach to risk assessment will be developed in this project for rare high impact events such as bomb blasts, where critical infrastructure is threatened. A new software platform based on scripted agent modelling will be constructed that will allow for state of the art models to be used as agents providing a dynamic risk evaluation and necessary information for actions to infrastructure owners and emergency responders as a threat develops. Both the developed scripted agent and the risk assessment technologies can be applied to other technologies and complex risks, such as waste disposal and biotechnology.
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    Funded Activity

    Linkage Projects - Grant ID: LP0882474

    Funder
    Australian Research Council
    Funding Amount
    $153,762.00
    Summary
    Development of a Multi Threat Risk Assessment Model for Critical Infrastructure Using Scripted Agent Computer Technology. The project will develop a distributed risk network capable of real time assessment of multiple threats to critical infrastructure, which will guide decision making on the appropriate response as the nature of the threat changes. This will assist all stakeholders and allow an integrated response across industry and government agencies. The developed technology will find read .... Development of a Multi Threat Risk Assessment Model for Critical Infrastructure Using Scripted Agent Computer Technology. The project will develop a distributed risk network capable of real time assessment of multiple threats to critical infrastructure, which will guide decision making on the appropriate response as the nature of the threat changes. This will assist all stakeholders and allow an integrated response across industry and government agencies. The developed technology will find ready application in other areas where integration of science and technology is required to solve complex problems. For example, risk network technology has application to natural hazards, waste disposal and financial markets while the scripted agent has application to communication technologies and sensor networks.
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    Funded Activity

    Linkage Projects - Grant ID: LP140100104

    Funder
    Australian Research Council
    Funding Amount
    $493,000.00
    Summary
    Mandatory pre-funded retirement income schemes: Best policy and practice. This innovative project aims to leverage in-depth knowledge of two mandatory pre-funded retirement income systems, Australia and the Netherlands to create new findings to significantly advance policy and practice in these two countries. Mandatory pre-funded retirement income structures adopt a range of approaches regarding choice and drawdown structures. This project aims to use survey and experimental techniques, and stoc .... Mandatory pre-funded retirement income schemes: Best policy and practice. This innovative project aims to leverage in-depth knowledge of two mandatory pre-funded retirement income systems, Australia and the Netherlands to create new findings to significantly advance policy and practice in these two countries. Mandatory pre-funded retirement income structures adopt a range of approaches regarding choice and drawdown structures. This project aims to use survey and experimental techniques, and stochastic life-cycle models, to investigate comparative choice frameworks and the menu of retirement income products in the two countries. It aims to deliver models for improved policy and retirement income designs, producing outcomes which aim to generate global benefit as more countries move towards this pension paradigm.
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    Funded Activity

    Linkage Projects - Grant ID: LP0562470

    Funder
    Australian Research Council
    Funding Amount
    $72,444.00
    Summary
    Risk Measurement for Large Portfolios under the Benchmark Approach. The measurement of risk for large portfolios, consisting of basic assets and derivatives, will play a key role in future risk management systems. Based on a new characterization of asymptotic portfolios this project proposes the development, implementation and testing of highly efficient new risk measurement methodologies suitable for portfolios with hundreds or thousands of instruments. Comparisons with standard and new simulat .... Risk Measurement for Large Portfolios under the Benchmark Approach. The measurement of risk for large portfolios, consisting of basic assets and derivatives, will play a key role in future risk management systems. Based on a new characterization of asymptotic portfolios this project proposes the development, implementation and testing of highly efficient new risk measurement methodologies suitable for portfolios with hundreds or thousands of instruments. Comparisons with standard and new simulation methods will demonstrate their superiority. The outcomes of this project will give the Australian industry and the industry partner a competitive advantage in the measurement and management of risk for large portfolios as superannuation funds or portfolios of banks.
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    Funded Activity

    Linkage Projects - Grant ID: LP170100891

    Funder
    Australian Research Council
    Funding Amount
    $415,893.00
    Summary
    Reshaping superannuation practice in Australia using big data analytics. This project aims to reform superannuation investment practices in Australia. Using sophisticated data analytics and machine-learning techniques, combined with economic modelling and quantitative finance. The project will try to understand the broad characteristics of Australian superannuation investors and their practice from a ‘big data’ perspective. The expected outcomes of this project are the identification of key dete .... Reshaping superannuation practice in Australia using big data analytics. This project aims to reform superannuation investment practices in Australia. Using sophisticated data analytics and machine-learning techniques, combined with economic modelling and quantitative finance. The project will try to understand the broad characteristics of Australian superannuation investors and their practice from a ‘big data’ perspective. The expected outcomes of this project are the identification of key determinants for successful superannuation behaviour to inform decision-making for better superannuation practices and policies. It is expected that the insights arising from this project will contribute to safeguarding the future of Australia’s superannuation schemes, and to better financial security at retirement.
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