Bounty: Tax Help Centers
Looking at how the ATO could use artificial intelligence or machine learning to locate the best locations for Tax Help Centers
Go to Challenge | 21 teams have entered this challenge.
Team Name:
#overachievers52
Team Members:
Safety Net
Project Info
Team Name
#overachievers52
Team Members
4 members with unpublished profiles.
Project Description
App that educates people about being scammed, with a gamified aspect.
Data Story
When doing our research we found alarming stats on the number and the dollar value of scams and phishing attacks, and we've all had family who has asked us to take a look at an e-mail because they thought it was legitimate. The data shows us that education is more important than preventing scams at their source, and we used that data to form our idea of educating users through examples and interactive learning. Our resident educational scammer, Sam, would be built out using machine learning and natural language processing to create a truly personalised and realistic introduction to scamming and how easy it can be.
Team DataSets
Gov Hack 2018
Description of Use The following data is listed on the ATO's website, identifying information scammers require for identity theft: accessing your bank accounts taking out loans in your name lodging false tax returns or BAS statements claiming Centrelink or other government benefits accessing your client or employee records gaining access to your superannuation. As we ask for a user's postcode, we hope to use this data to target key areas that the ATO could have a presence. Since a high percentage of elderly people are targeted, and currently Chinese people with recent scams, face-to-face and telephone support would be a high priority.
Consumer Affairs Victoria - Web based information and advice
Description of Use We wanted to find out where people are getting their information, especially if it's online or via social media. It was interesting to see how many people also visited the MoneyHelp website - another potential avenue for our target demographic.
Identity Theft
Description of Use Supporting the educational data we have used within the app.
Romance Scam Data
Description of Use Supporting the stats we found on scamwatch.gov.au to find out where people are being scammed and how. Breaking down the demographic further also helped us identify people to target the app to.
Community Interest and Engagement with Science and Technology in Victoria Data
Description of Use Researching the attitudes of Victorians towards technology, to see if lack of education is due to lack of interest. We recognise the data is quite old, but it was a useful starting point - especially with the interview questions used - to delve deeper into the issues of being scammed.
Challenge Entries
The Friendly ATO
How can the ATO use artificial intelligence or machine learning to better understand and develop ways to engage with our clients?
Go to Challenge | 15 teams have entered this challenge.
Can you beat a scammer at innovation?
How can different tools improve scam prevention?
Go to Challenge | 3 teams have entered this challenge.