The Easier Way Out

Project Info

Caffeinated Pre-workout thumbnail

Team Name

Caffeinated Pre-workout

Team Members

Tylor Bunting and 4 other members with unpublished profiles.

Project Description

Filing for bankruptcy can be stressful for people. This already difficult time becomes increasingly overwhelming when you're faced with an extended form asking you about the entirety of your financial situation.

'The Easier Way Out' project aims at making it simpler for applicants to complete the application and easier to provide their income and asset information. Our solution is two-folds:
1. Digitising the form (i.e. debtor's petition).
2. Using algorithms and statistical modelling to pre-populate form fields based on documents and information provided by the applicant (e.g. bank statements, superannuation statements, property statements, etc.).

Evidence of Work


Project Image

Team DataSets

ATO Statistic Data - City of Greater Geelong

Description of Use Used to train machine-learning model to pre-populate fields in bankruptcy application form.

Data Set

Attributes of insolvent debtors

Description of Use Pre-populating fields in the bankruptcy application form using predictions generated by machine learning models (e.g. a person with a certain gender, age and occupation is mostly likely to have ~$50,000 in assets).

Data Set

Challenge Entries

🌟 Improving the customer experience of government services

How can government data be used to improve the experience of citizens interacting with government?

Go to Challenge | 24 teams have entered this challenge.

Bankruptcy – making it easier

This challenge aims to help us make it easier for people to tell us their income and assets when they become bankrupt.

Go to Challenge | 5 teams have entered this challenge.

ATO for individuals

How can ATO and other Australian public data be used to help the community fill employment opportunities?

Go to Challenge | 27 teams have entered this challenge.