Senate Community Affairs Legislation Committee
BUDGET ESTIMATES – 3 JUNE 2015
ANSWER TO QUESTION ON NOTICE
Department of Human Services
Topic: New Compliance Measures
Question reference number: HS 15
Senator: Cameron
Type of question: Hansard page 47
Date set by the committee for the return of answer: 24 July 2015
Number of pages: 2

Question:
Ms Campbell: I think Mr Withnell talked about the cost-benefit analysis, that at some point it
was going to cost us much more to actually find this information. I think one of the features
will be that we will be able to say to people who are currently customers, 'You said this to us.
We believe this is the amount you earned. Can you tell us which is correct? Ability to access
that information has not always been there. The costs have changed over time, and it is now at
a point where it is beneficial to put in place these mechanisms.
Senator CAMERON: You have used analytics for some time?
Ms Campbell: We have used the analytics, but this issue is about being able to do that data
match and go out in a digital form to 800,000 customers and say to them, 'We have two
different sources of your income. Tell us which is correct.'
Senator CAMERON: Is it possible for you to provide to the committee a cost-benefit analysis
that has been done?
Ms Campbell: We can take that on notice.
Answer:
The main element of the measure contributing to the savings is the Pay As You Go (PAYG)
data match. The business case is summarised below.
The number of compliance interventions to be undertaken has been determined by analysing
the data matching output from the PAYG files provided by the Australian Taxation Office
(ATO) for the 2010-11, 2011-12 and 2012-13 financial years. This data is obtained via
existing data matching processes that occur every year.
The analysis undertaken considered the dollar value of the discrepancy between the PAYG
data and what has been reported to the department by the customer, and identified
approximately 1,080,000 instances where there was a discrepancy. These discrepancies
involved over 866,000 unique customers. Some customers have more than one identified
discrepancy.
To determine the total value of these historical discrepancies, a significant sample was
extracted and analysed to assess whether the discrepancies would result in a debt to the
customer, and identify the expected debt value.

 Analysis identified that in 85 per cent of instances the discrepancy would result in a debt, and
the likely average debt value is approximately $1,440. Since the Budget announcement, a
pilot has been undertaken which has confirmed the assumptions that underpin the savings.
Using the newly developed streamlined intervention approach, the savings now far outweigh
the cost of undertaking the activity and far outweigh the cost of the overall measure.