Individualized Super Assessment

Team Name

Team 1612

Team Members

Project Description

A personalized super health check would go a long way in nudging individuals to maintain a healthy super and in turn reduce pressure on government. ATO is uniquely positioned to deliver this service as it has access to every individuals income, assets details. Expense information which we find it critical could be asked to be provided by individual or taking consent from individual, ATO can obtain this from the bank.

We propose to use advanced machine learning techniques like clustering to group individuals into clusters. Every cluster will have individuals with similar income-expense ratio.

For every such cluster, we forecast their income and expenses into the future using time series forecasting techniques of machine learning.

Using this forecasted expense number, we could predict what could be considered a healthy super.

Data Story

Here we used the dataset "Taxation Statistics 2018-19" to start with. Since, this information was at the aggregated level, we tried to convert this into individualized information.
https://data.gov.au/dataset/ds-dga-2805b28d-2c3b-47e2-87c3-50aacc6ea212/details?q=