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Team Name:

Neural Newbies


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Evidence of Work

Tax Assist

Project Info

Team Name


Neural Newbies


Team Members


Eliza and 4 other members with unpublished profiles.

Project Description


We created a standalone tool "TAX assist" which would help vulnerable or at-risk groups who face barriers or challenges in complying with their tax obligations. They can choose to use features like 2 minute modules, FAQs, Multilingual Pages, AdiAI who is our voice and chat assistant. The voice assistant has access to the web page/your screen and can be asked any question about any information which is being displayed on the screen, the Voice assistant however would not have sufficient privileges to file your tax for you due to security reasons.


#ato #tax #inclusive #taxation #super

Data Story


Our data analysis identified four key vulnerable groups, each with their own unique challenges. These four groups include: older individuals, people with disabilities, rural residents and migrants or non-residents. Each of these groups faces distinct barriers, from complex tax situations to digital literacy and language issues. Our solution aims to create a more tailored, user-friendly tax filing experience, ensuring that all individuals can efficiently comply with their tax obligations, regardless of their circumstances.

By leveraging data and digital tools, we can proactively identify potential challenges and provide targeted assistance. Through a combination of AI-powered prompts, accessibility features, and personalised resources, we seek to simplify the tax process for self-preparers, who are often the most vulnerable without professional guidance.

First group: Older individuals (60+)

Table 13 of the ATO’s Taxation Statistics for 2021-22 shows the total Interest charged by ATO (possibly due to late payment and/or late lodgement) according to different age groups:

We grouped the age groups 60-64, 65-69, 70-75+ as they are considered senior citizens in Australia.

Older individuals (60+) incurred $106,158,796 interest in the year of 2021-2022. They may be lodging late due to the complexity of their tax situation (retirement income, superannuation).

We note that the working population are getting more refunds from the Tax office due to overpayment of PAYG installments by their employers. But they are not relevant for our purposes, so we did not analyse further into this finding.

Australia has an ageing population:

As of 30 June 2020, there were an estimated 4.2 million older Australians (aged 65 and over) with seniors comprising 16% of the total Australian population
The number and percentage of senior Australians is expected to continue to grow. By 2070, it is projected that older people in Australia will make up between 21% and 23% of the total population

Projection of the Australian population aged 65 and over as of 30 June 2020
Source: http://www.aihw.gov.au/
52.3% of senior Australians had a disability, and 86.6% had one or more long term health conditions. 39.8% of senior Australians living at home needed at least some assistance with everyday activities.
Second Group: People with disabilities
Source: https://www.abs.gov.au/statistics/health/disability/disability-ageing-and-carers-australia-summary-findings/latest-release

According to ABS data, in 2022, 5.5 million Australians (21.4%) had a disability, up from 17.7% in 2018. That is more than one in five people in Australia.

Therefore it’s important to make our platform easy to access for all, including voice recognition, AI help assistance, and other options for them.

Third group: People in rural areas

Taxpayers in these postcodes (red circles) are earning less than $40,000 of average taxable income in the year 2021-2022.

Internet connectivity and digital literacy issues are common in rural or remote areas. This makes it harder for residents to access online services or receive timely tax information, especially when relying on digital communication from the ATO.

Fourth group: Migrants and non-residents

Language barriers and unfamiliarity with the Australian tax system can make it difficult for these individuals to meet their tax obligations. We need to ensure we speak their languages on the platform to bridge the gap.

According to Table 11, Residency Lodgement Method Data set from the ATO, work-related expenses claimed by non-residents are about 11% of their taxable income, while for residents, it is only at 5%.

According to ATO data at https://data.gov.au/data/dataset/taxation-statistics-2021-22/resource/6dd981d6-0323-427f-a19e-ed4b74061ae8?inner_span=True

Our solution is to try to improve the tax filing experience – our target audiences are myTax users and other self-preparers (a total of 36.9% of taxpayers)

As at 29 August 2024, ATO has received over 6.5 million individual tax return lodgments for 2024; which is a 3% increase compared with the same time last year.
Of these lodgments:
over 3.5 million were lodged by self-preparers.
over 2.9 million were lodged by tax agents.
over 93,000 were push returns.

Our solution will be tailored for the 3.5 million lodged by self-preparers.

The vulnerable groups identified are the self-preparers because they do not have any assistance/guidance from tax agents.

When individuals/sole traders are using Mytax (MyGov tax filing portal), we can prompt relevant questions such as, “Would you like to file using Tax Assist?” if they spend more than three hours on a tax return.

According to Chart 19, we can see the average time to complete tax return, 2017–18 to 2021–22 income years.

We can utilise this data and prompt the user if they spend more than 3 hours on the filing of their returns on Mytax.

The estimated tax gap is dominated by individuals and small businesses. These would be our primary target audience, of which we are focusing here on individuals.

We have not shared the findings on our presentation when the data are not sourced from the ATO data set in this challenge.

Optional Question
Identify how digital platforms could be used to proactively identify indicators of vulnerability. How might correlations between data points such as income (frequency, amount, source) or behaviors (delayed lodgement) give an early indication of vulnerability? How can we better use data to design digital systems? What kind of data could we collect that doesn’t compromise citizen privacy?

To address the unique needs of seniors, people with disabilities, rural residents, and migrants or non-residents, we propose a tailored website experience that delivers the right support to each group.

As users complete their tax returns on MyTax, the system will analyse the data they input to determine if they fit into one of these groups. For example, it will recognise seniors based on their date of birth and prompt them with tax tips specifically for their needs, along with a link to a personalised page.

The system will also identify early signs of potential issues, such as delays in lodgement, and offer AI-based support to assist with the process. It will track interest accrued and send timely reminders to ensure returns are filed on time.

Rural taxpayers with lower incomes will receive information about applicable offsets, and the site will adapt to provide a low-bandwidth version for faster load times. Additionally, taxpayers with irregular incomes, such as gig workers, will receive personalised advice to help manage their tax filings.


Evidence of Work

Video

Homepage

Team DataSets

Individual Statistics

Description of Use Used this data set to identify individual income patterns and how they related to lower or higher voluntary tax compliance in individuals

Data Set

Australian Tax Gap

Description of Use Used this data set to identify the the groups that had the lowest and highest Voluntary tax compliance rates and why?

Data Set

Challenge Entries

Tax inclusion for vulnerable groups

How can we use open government data to identify vulnerable or at-risk groups who face barriers or challenges in complying with the tax and super systems, and design or improve digital solutions to help them meet their obligations and access their entitlements?

Go to Challenge | 14 teams have entered this challenge.