ATO (13.256): Self-finalising Lodgement Analytical Model

Project Member(s): Cao, L.

Funding or Partner Organisation: Australian Taxation Office

Start year: 2014

Summary: The Lodgement Risk and Strategy stream with-in the Tax Practitioner and Lodgement Strategy (TPALS) business line of the ATO are seeking to engage the University of Technology Sydney (UTS) Advanced Analytics Institute to work with the ATO to develop analytical modelling that will assist the ATO to maximise the effective allocation of resources to address non lodgement. This contract will build on an existing collaborative research project between the ATO and UTS which focuses on explicit analysis to identify debts which are likely to be paid in full within a certain timeframe, and developing models on debt collection optimization using advanced analytics techniques. Through this project, the ATO seeks to utilise behavioural analytics in order to deepen and enhance its understanding of taxpayer compliance behaviour related to lodgement. This will enable improved resource efficiency through identifying appropriate compliance actions for individual taxpayers based on the taxpayer's behaviour. The ability to identify lodgements that are likely to be received reduces the requirement for compliance actions by the ATO. It enables the ATO to shift its compliance actions towards those taxpayers who will only lodge or pay in response to action and enhances the ATO's differentiation capability and enabling refined risk-based decision making to prioritise lodgement compliance action. This research project, undertaken by UTS, will be conducted in stages. TPALS Risk and Strategy will review progress, and evaluate outcomes, at the end of each stage before deciding to advance to the next stage. The first stage will be the development of a self finalisation model and will run in parallel with a similar project being undertaken by the Debt business line.

Keywords: analytical modelling, behavioural analytics, debt collection optimization, taxpayer compliance behaviour, data exploration, model development, model validation

FOR Codes: Taxation, Analysis of Algorithms and Complexity, Computational complexity and computability

Acknowledgement of Country

UTS acknowledges the Gadigal people of the Eora Nation, the Boorooberongal people of the Dharug Nation, the Bidiagal people and the Gamaygal people, upon whose ancestral lands our university stands. We would also like to pay respect to the Elders both past and present, acknowledging them as the traditional custodians of knowledge for these lands.