PhD Project: Real time Car insurance for the New Age
The age of big data is upon us. Every day we generate vast quantities of data but the question is how to utilize it. From the perspective of property and casualty insurance this question is truly acute. For example, car insurance companies in USA, Canada and Australia from recently have access to data generated by telematics devices. As Alliance Australia [1] describes telematics devices installed in motor vehicles allow for remote and real time tracking of vehicle’s location, speed, acceleration, deceleration and many other parameters of driving. How to use this data to understand the behaviour patterns of driving and how to integrate other sources of data such as local weather and traffic conditions, health status of driver at every point it time (available through wearable consumer electronics), is an active source of investigation in a nascent field of telematics insurance. Techniques such belonging to class of advanced data analytics such machine, deep learning and clustering can help answer this question. The purpose of this PhD project is to develop predictive analytics algorithms for sophisticated real time classification of drivers according to their driving patterns and likelihood of accidents. Also real time pricing implications in this project would be investigated. Dynamic reduction in premiums might have significant appeal to many drivers as a compensation for access to their relevant real time data. From the perspective of insurance company the ability to access the risk in a more sophisticated way is highly welcomed especially in the context of new capital adequacy rules.
1] https://www.allianz.com.au/car-insurance/news/use-of-telematics-in-vehicles
Applications can be made by selecting the below link.
Please attach supporting documentation including a covering letter outlining why you would like to undertake the PhD project and a current CV including 2 referees. Please note that more than one application can be made if you wish to be considered for more than one PhD project.