This paper analyzes the use of big data techniques in auditing, and finds that the practice is not as widespread as it is in other related fields. We first introduce contemporary big data techniques to promote understanding of their potential application. Next, we review existing research on big data in accounting and finance. In addition to auditing, our analysis shows that existing research extends across three other genealogies: financial distress modelling, financial fraud modelling, and stock market prediction and quantitative modelling. Auditing is lagging behind the other research streams in the use of valuable big data techniques. A possible explanation is that auditors are reluctant to use techniques that are far ahead of those adopted by their clients, but we refute this argument. We call for more research and a greater alignment to practice. We also outline future opportunities for auditing in the context of real-time information and in collaborative platforms and peer-to-peer marketplaces.

Financial illiteracy is widespread amongst the elderly. Financially illiterate people are more likely to experience asset loss and outlive their savings after retirement. This paper measures financial literacy of elderly Australians using Item Responses Theory. Using a Lasso regression, we find that younger, married males with higher income and greater net wealth are more likely to be financially literate. Better financial literacy is also associated with good health, higher educational attainment, better occupation and outright home ownership. Our findings suggest policy makers take action and we make informed and practicable policy recommendations.

No abstract

Background: A critical choice facing breast cancer patients is which surgical treatmentmastectomy or breast conserving surgery (BCS) -is most appropriate. Several studies have investigated factors that impact the type of surgery chosen, identifying features such as place of residence, age at diagnosis, tumor size, socio-economic and racial/ethnic elements as relevant. Such assessment of "propensity" is important in understanding issues such as a reported under-utilisation of BCS among women for whom such treatment was not contraindicated. Using Western Australian (WA) data, we further examine the factors associated with the type of surgical treatment for breast cancer using a classification tree approach. This approach deals naturally with complicated interactions between factors, and so allows flexible and interpretable models for treatment choice to be built that add to the current understanding of this complex decision process.

No abstract