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  • Data-matching programs

    Our data-matching programs are designed to increase community confidence in the integrity of the tax system.

    We use the data to:

    • help individuals and businesses understand their tax obligations, including registration, lodgment, reporting and payment
    • protect honest businesses from unfair competition
    • make it easier for individual taxpayers by pre-filling their returns
    • assess the levels of voluntary compliance of individuals and businesses with their tax obligations.

    If we check your information, it doesn’t automatically mean we think you are dishonest in your tax affairs. If the data doesn’t match, we will contact you to find out why.

    Note: If you haven't reported all your income, or if you have made a mistake with your tax records, you should Correct the mistake or amend a return.

    Report a concern

    If you suspect a person or business isn't doing the right thing, you can tell us anonymously. This can include things like:

    • skimming some or all of their cash takings
    • running part of their business 'off the books'
    • not reporting all their income.

    See also:

    We review all reports and take action where appropriate. We conduct specific data-matching programs in a number of areas.

    Specific data-matching programs

    We collect data from a range of sources to protect honest businesses. Specific data-matching programs allow us to conduct formal data matching without it being legislated. We do this by identifying businesses that:

    • may not be reporting all their income
    • operate outside of the system
    • are operating, but are not lodging returns.

    The data is used to understand trends and patterns in industries, including where we need to develop assistance products to help the community understand their tax obligations.

    We are currently undertaking specific data-matching activities in the following areas:

    See how we have used third-party data to protect honest businesses with the following examples.

    Example: Under-reporting merchant sales

    A clothing retailer with multiple retail stores appeared to be under-reporting merchant sales. We found an $870,000 discrepancy between their business activity statement and tax return. The owner made a voluntary disclosure on reporting errors for 36 activity statements across the financial years 2010 to 2013, resulting in unpaid goods and services tax (GST) of $248,851. Since they were cooperative, no penalties were charged.

    End of example

    Example: Cash-only business caught avoiding GST

    One of the owners of a cash-only takeaway chicken shop had been previously audited twice for another chicken shop, involving cash wages and inadequate record keeping.

    The owners were claiming a large portion of GST-free sales from the sale of cold, uncooked chickens. When we tried purchasing an uncooked chicken, we were told that it was unavailable as the shop is a takeaway.

    Our audit revealed they had understated their sales by around $330,000 and were paying cash wages. The owners had to pay back $103,371 in GST and also $77,528 in penalties.

    End of example

    Example: Using benchmarks to determine unreported income

    A cleaning services company appeared to operating on a cash-only basis and was reporting outside benchmarks.

    We discovered that not only was the director receiving more payment than his reported wage, there were no records of contractor payments, and significant AUSTRAC cash withdrawals existed, which we suspected were to pay employees and contractors. We also identified an undisclosed bank account.

    The owner’s lack of record keeping and failure to provide all requested documents was enough for us to apply the industry benchmark. This resulted in $156,179 in unpaid GST and $283,602 pay as you go withholding, as well as total penalties of $156,096.

    End of example

    Example: Data matching reveals dishonest business

    A business selling horse riding equipment on an online selling platform with sales of $1,280,003 was selected for review.

    We discovered the owner had registered the account in another person’s name, and was selling unbranded horse saddles made by his parent’s company in China.

    We also found another online selling account and a website where no income was reported from either source. A specialised payment system account linked to this account and the website were linked to the owner’s personal bank account and showed significant AUSTRAC activity to Chinese bank accounts.

    Our audit determined the entity had been under-reporting income and over-reporting expenses for the life of the business – never declaring income on export sales, including unsubstantiated expenses in their income tax return and non-business activity statement expenses in activity statement purchases.

    The owner had to pay $103,263 in GST, $259,298 unpaid income tax, and penalties of $181,280.

    End of example

    Credit and debit cards

    We obtain data from banks and financial institutions to identify the total credit and debit card payments received by Australian businesses. This is detailed in the Credit and debit cards data-matching protocol.

    We don’t gather information about individual credit or debit card holders.

    From 1 July 2017, these institutions will need to automatically report this information to us each year.

    Specialised payment systems

    We obtain data on electronic payments made through specialised payment systems to Australian businesses. This data is analysed in conjunction with data collected through our credit and debit card data-matching program.

    See also:

    Online selling

    We obtain details of online sellers who sell goods and services to the value of $12,000 or more.

    Data is obtained from online selling sites where the data owner or its subsidiary:

    • operates a business in Australia that is governed by Australian law
    • provides an online market place for businesses and individuals to buy and sell goods and services
    • tracks the activity of registered sellers
    • has clients whose annual trading activity amounts to $12,000 or more
    • has trading activity for the years in focus.

    See also:

    Ride-sourcing

    We obtain data from all ride-sourcing facilitators operating in Australia and their financial institutions to identify ride-sourcing drivers.

    This information allows us to help drivers understand their tax obligations including registration, lodgment, reporting and payment obligations.

    See also:

    Motor vehicle registries

    We obtain data from all the state and territory motor vehicle registering bodies to identify all motor vehicles sold, transferred or newly registered, where the transfer or market value is $10,000 or more.

    See also:

    Cryptocurrency

    We obtain data from Australian cryptocurrency designated service providers (DSPs) to ensure people trading in cryptocurrency are paying the right amount of tax.

    See also:

    Exchanging data with other Australian Government agencies

    Our data-matching program identifies cases at risk of either:

    • incorrect personal financial assistance payments
    • tax evasion.

    We provide income information derived from tax returns to the Data-Matching Agency (DMA) – a separate agency within Centrelink – on a cyclical basis (up to nine cycles per year) on selected agency clients. This is used to determine the eligibility criteria for benefits and to help detect fraud within the welfare system.

    The data is provided by us under the provisions of the Data-Matching Program (Assistance and Tax) Act 1990.

    Assistance agencies provide client data, including tax file number (TFN) and identity details, to the DMA, who give us this data to match. The data is then passed via Centrelink and used for a series of matching exercises, before the outcomes are returned to the DMA.

    Where we have identified the client from data provided, the following data is returned to the DMA:

    • personal identity
    • declared income
    • date of most recent taxation assessment
    • amount of the spouse tax offset
    • surname and any other name details of the spouse where a spouse offset has been claimed
    • surname and any other name details
    • an indicator, if the TFN is compromised.

    We conduct matching exercises against our internal data to detect cases where:

    • individuals are receiving more than one payment simultaneously
    • a lesser entitlement or no entitlement exists
    • a greater entitlement exists
    • income details of assistance agency payments are understated in tax returns.

    Other data exchanges

    We exchange data with Department of Human Services (DHS) programs such as Centrelink and the Child Support Program, as well as other government agencies, under separate legislative provisions, as detailed in the following paragraphs.

    Centrelink

    Each week we provide taxpayer identity information derived from the processing of TFN declarations (previously employment declarations) to Centrelink. Centrelink matches this data against clients receiving unemployment benefits to ensure benefits are not paid after employment has commenced.

    We pass approximately 100,000 records to Centrelink each week. Around 12% of these are found to be Centrelink clients. ATO data is provided under table item 1 in table 1 in section 355-65 of Schedule 1 to the Taxation Administration Act 1953 (TAA).

    We provide taxpayer income details for the purpose of administering family assistance entitlements. This involves the daily exchange of income, family tax benefit and child care subsidy data between Centrelink and us, via a mutual client register, for family assistance administration and payment reconciliation.

    This information is used in the assessment of entitlements, reconciliation of payments and immediate recovery of outstanding debts to the Commonwealth. ATO data is provided under table item 6 in table 1 in section 355-65 of Schedule 1 to the TAA.

    To detect Centrelink clients failing to declare assets, we match all beneficiaries against trust data from the tax return database. This identifies welfare beneficiaries who are also recipients of trust distributions. We provide details of trust income to Centrelink, along with the Centrelink reference number as an identifier. Subsequent checks determine whether or not the trust income was declared to Centrelink at the time the entitlement to the benefit was determined. We do not pass TFNs to Centrelink. This data is provided to Centrelink under the Trust beneficiary data-matching program.

    Child Support Registrar

    The Child Support Registrar has access to our taxpayer income details (employment and investment income) via electronic transfer and direct access, for the purpose of assessing the amount of individuals' child support payments and for garnishee action, where appropriate.

    The Child Support Registrar's acquisition of taxpayer information from the Commissioner of Taxation is provided for by the Child Support (Registration and Collection) Act 1988 and the Child Support (Assessment) Act 1989.

    We can also provide information to the Child Support registrar voluntarily, for the purposes of administering the two child support Acts referred to above, under table item 7 in table 1 in section 355-65 of Schedule 1 to the TAA.

    Department of Home Affairs

    Department of Home Affairs (Home Affairs) onshore compliance staff request address information for individuals who have been classified as 'illegal non-citizens', to assist in locating them. Home Affairs provides name and date of birth details to us and we use this to retrieve address details. We are authorised to communicate information to Home Affairs for the purpose of assisting in locating persons who are unlawfully in Australia, under Item 3 in Table 7 in subsection 355-65 of Schedule 1 to the TAA.

    Some specific information about persons who are visa holders or sponsors can also be disclosed to Home Affairs for the specific purposes set out in table item 4 in the same table.

      Last modified: 21 May 2019QC 55323