School of Risk and Actuarial Studies Undergraduate Research Scholarship UGCA1636:
T3/21 Research Projects

The School of Risk and Actuarial Studies Undergraduate Research Scholarship UGCA1636 exposes highly talented undergraduate students, enrolled in Business to research based experience on projects that are moreover linked with an industry partner. The scholarship program will run for a six week period over the later part of Term 3, 2021 (dates TBC with the supervisory team and succesful candidate).

 

How to apply

To apply you will need to submit the following:

Supporting Documentation

Please submit the following with your Scholarship application:

  • An electronic copy of your CV
  • An electronic copy of your academic transcript

Applications are now open and will close Friday, 22 October, 2021.

Research Projects

 

Risk and Actuarial Studies Research Projects

Project Title: Modelling Spatial Extremes of Environmental Data

Supervisor(s): Qihe Tang (Lead), Fei Huang, Bernard Wong

Description: This project studies dependence of spatial extremes among rainfall, temperature, wind, humidity, etc., using gridded Australian environmental data from the Bureau of Meteorology. Some preliminary knowledge of extreme value theory is required. Deep learning techniques will be employed for modelling and prediction purposes. The modelling outcome will be applied to reinsurance pricing/reserving or other related business applications. This project will be in partnership with industry partners from a major general insurer.

Core skills student needs: Some preliminary knowledge of extreme value theory is required. Deep learning techniques will be employed for modelling and prediction purposes.

 


 

Project Title: Critical Illness Insurance Risk Modelling with a Focus on Cancer Incidence and Mortality in Asian Countries

Supervisor(s): Katja Hanewald (Lead)

Description: This project will develop new techniques for modelling the biometric risks of cancer incidence and cancer mortality in critical illness insurance. Critical illness insurance is one of the most widely-sold private insurance products in Asia. Cancer is the most prominent cause of claim in critical illness insurance. The project will involve a review of existing actuarial and machine learning modelling approaches for critical illness risk modelling and then develop new models that will extend and improve existing approaches. The models will be tested with data from Australia, China or other countries in Asia. The project will be co-supervised with a partner from a major Asia-pacific reinsurance firm.

Core skills student needs: Background in Actuarial Studies and interest in machine learning techniques.


 

Project Title: Benchmarks for the Pricing of Public and Private Reverse Mortgages

Supervisor(s): Katja Hanewald (Lead)

Description: This project will develop benchmarks for the pricing of public and private reverse mortgages. Reverse mortgages allow older homeowners to borrow against their home equity without having to make mortgage payments while they live in the property. The project will first compare existing reverse mortgages products in Australia and other markets. In a second step, the project will review the academic literature on reverse mortgage pricing. In a third step, the project will develop new benchmarks for the pricing of different public and private reverse mortgages using actuarial modeling. The project is a collaboration with the Australian reverse mortgage lender Household Capital Pty Ltd.

Core skills student needs: Background in Actuarial Studies.


 

Project Title: Actuarial analytics of flood insurance  

Supervisor(s): Bernard Wong (Lead), Qihe Tang

Description: This project will estimate indicators of flood insurance costs via combining actuarial and machine learning techniques. The project will involve combining different sources of public and propriety data, and also to incorporate environmental and built environment factors. The project is in collaboration with a major Australian general insurer, and is expected to contribute to both sound pricing and risk management, and more broadly enhance the resilience of Australian households and business to this important risk.

Core skills student needs: Background in Actuarial Studies. including courses in Machine Learning/AI techniques. Additional complementary background knowledge in areas such as physics/climate/built environment will also be of benefit, although not required.


 

Project Title: Understanding under-insurance and resilience

Supervisor(s): Hazel Bateman (Lead), Inka Eberhardt

Description: This project will provide a literature review on aspects of underinsurance in general insurance, especially in personal property. This is part of a project involving potential industry partners to explore the role of behavioural approaches to address under-insurance.

Core skills student needs: Background in Actuarial Studies and/or behavioural economics or behavioural finance.


 

Project Title: Modelling socio-economic differences in the mortality of Australians 

Supervisor(s): Andres Villegas (Lead), Fei Huang

Description: Using potentially a big dataset and stat-of-art statistical machine learning techniques to model socio-economic differences in the mortality of Australians using education, income, occupation and other socio-economic variables. The results may support Governments in the development of retirement or social welfare policies, and the insurance/superannuation industries to create more relevant retirement income products to improve the financial wellbeing of older Australians.

Core skills student needs: Data analytics skills. Students who have taken relevant courses such as ACTL3142/5110 or ACTL4305/5305 (or similar courses offered by other schools) are preferred.