Data-matching program assistance and tax act

The OAIC suggests the following approach to estimating the cost of staff time involved in developing a new data matching project:. Step 1: Estimate the amount of time in person weeks, months or years that will be spent by all staff on initial development of the project.

Step 2: Estimate the average salary of project staff per week, month or year , and multiply it by the estimated staff time needed for project development. Step 3: Multiply the result of Step 2 by a factor to allow for labour on-costs and overheads. The Department of Finance and Deregulation recommends multiplying the basic salary cost by a factor of 2.

The staff costs must include time spent on the project by all staff, including administrative, corporate services, IT and support staff, as well as staff dedicated to the project. It is not acceptable to minimise the apparent costs of a data matching program by trying to shift costs associated with the program to other areas of the agency.

The statement of costs and benefits should indicate the amount of staff time estimated for project development, the total staff cost of setting up the project and the method of calculation. Most data matching programs do not require capital expenditure. If capital outlays are required for a program for example, if computer facilities are to be expanded to cater for the project they should be stated see page 13 of the Department of Finance and Deregulation Guidelines for Costing of Government Activities for more information on assessing capital costs.

It is not necessary to include other costs, such as publicity costs and use of computer facilities unless they are significant in magnitude. As a general rule, it will not be necessary to quantify such costs if they represent only a few per cent of overall establishment costs. Agencies should ensure that all other costs, including other costs incurred by IT, corporate services or special projects areas are considered in this category.

If these costs are negligible they may be excluded from the statement of costs; a statement that the costs are negligible and have been excluded should be included in the protocol. The costs associated with taking action in response to matches obtained through a data matching program will also tend to be predominantly comprised of staff costs.

The method used to estimate those costs will depend on the way the data matching program results are used. If the response to matches is carried out by dedicated staff, the cost of this activity can be readily calculated.

If staff who carry out reviews based on matches also have other functions, the time required for those reviews could be calculated either by:. The latter approach would be most suitable in situations where the task of responding to matches is decentralised, and data on how review staff allocate their time is not available.

The total amount of overpayments identified as a result of the program should be reduced to recognise:. For example, an agency may estimate that 70 per cent of identified overpayments represent actual savings; the remaining 30 per cent of overpayments will be unable to be recovered, or the recovery costs would exceed the amount to be recovered. The statement of benefits should include both the total amount of overpayments identified and the method of calculating how much of those overpayments represent actual savings.

If full figures for recovered amounts and the costs of recovery are available either from a pilot project in the case of a new program or from experience with a program being evaluated , these could be used rather than adopting the approach outlined above. This may occur, for example, where a data matching program identifies that someone currently receiving a Government payment is not entitled to it, or is not entitled to payment at the current rate, and this leads to termination or reduction of the payment.

Especially in the case of continuing payments for example, welfare benefits it will often not be possible to conclusively determine how much would have been incorrectly paid had the payment not been terminated or reduced.

If a general assumption is made for example, that the incorrect amount would have continued to be paid for a standard period , the statement should clearly specify the assumption, and the reasons for its adoption. For example, an agency might assume that an incorrect payment would have continued to be paid for half the average period for which payments of that type are made, based on past experience regarding the average time required to identify incorrect payments. In making such an assumption, agencies should account for the possibility that other review methods if relevant or applicable could have identified the incorrect payment had the data matching program not done so.

If a program identifies cases where additional revenue is owed to an agency, the estimate of the benefit derived should either:. Savings of this sort are likely to be most important where data matching allows an activity that would have to be carried out in any case, to be performed more efficiently.

Agencies may think that public knowledge that a data matching program is operating leads to increased compliance with the law, thus reducing regulatory costs. This kind of benefit is obviously difficult to quantify. If agencies believe that benefits of this sort are likely to be achieved, they should include them in the statement of benefits, along with the reasons for holding this view and any information that indicates the likely magnitude of benefits from this source.

Many data matching programs have benefits that cannot readily be expressed in financial terms. For example, data matching is used to facilitate visa compliance, to detect criminal offences and to build up intelligence holdings of law enforcement agencies. Some types of benefits probably cannot be quantified at all, but should still be described. For example, if a benefit of data matching is improved services to clients or improved data quality, the statement of benefits could describe the effect of the data matching program in these regards.

Where possible, it is helpful to quantify non-financial benefits. For example, if a program is aimed at facilitating visa compliance, it may be useful to state how many visa overstayers have been, or are expected to be, located by means of the program.

This would help to illustrate the reasons why a data matching program is considered worthwhile, and provide a basis for comparing actual performance against initial estimates. If a data matching program does not have a readily quantifiable outcome of this sort, other measures of performance can be found.

For example, if the function of a program is to add significant items of information to an intelligence database, it may be relevant to estimate how many items of information the program will identify.

If matches contribute to an outcome but are not the sole factor, it may be useful to indicate in how many instances the output from the data matching program contributes to a result being achieved.

The results of DA may be used to identify areas of key risk, fraud, errors or misuse; improve business efficiencies; verify process effectiveness; and influence business decisions. Document no longer available by this link. Main menu. What is CDR data? Search Submit. Guidelines on data matching in Australian Government administration 18 June Tags: data matching. Background The purpose of these Guidelines 1. Who should use these Guidelines? Status of the Guidelines 6.

History of the Guide In , the Privacy Commissioner released the former guidelines for adoption by agencies. Privacy safeguards Exemption from the Guidelines Guideline 1 — Application of the Guidelines Guideline 1 — Summary 1. Data matching programs involving more than one agency 1. Guideline 2 — Deciding to carry out or participate in a data matching program Guideline 2 — summary 2.

Guideline 3 — Prepare a program protocol Guideline 3 — summary 3. Purpose of the program protocol 3. What should the program protocol contain? Program protocols for similar data matching programs treated as a single program 3.

Guideline 4 — Prepare a technical standards report Guideline 4 — summary 4. Purpose of the technical standards report 4. What should the technical standards report contain? Comply with the technical standards report 4. New data matching programs 4. Changes to data matching program specifications 4. Guideline 5 — Notify the public Guideline 5 — summary 5. Obligation to notify 5.

Content of public notice 5. All participating agencies or source entities 5. This could be done by, for example: including information in a privacy policy about using and disclosing personal information for data matching purposes including information about the proposed data matching program in material given to individuals when they provide information that is likely to be used in the data matching program informing relevant individuals about the proposed data matching program directly for example, by letter or email by placing notices in relevant special-purpose publications or newsletters 5.

Privacy policy 5. Notify individuals 6. Guideline 7 — Destroy information that is no longer required Guideline 7 — summary 7. Destroy information that is no longer required 7. Guideline 8 — Do not create new registers, data sets, or databases Guideline 8 — summary 8.

Do not create new registers 8. Regular evaluation 9. Guideline 10 — Seeking exemptions from Guideline requirements Guideline 10 — summary However, the OAIC will keep such advice confidential if, in the advice, the agency head: requests that the advice remain confidential provides reasons for that request that the Commissioner considers to be sufficient Guideline 11 — Data matching with entities other than agencies Guideline 11 — summary Entities other than agencies Guideline 12 — Data matching with exempt agencies Guideline 12 — summary Exempt agencies OAIC review Description of the data matching program The description of the data matching program needs to cover the following matters.

An overview of the data matching program Overview A short, simply expressed statement of what the data matching program does and why. The objectives of the data matching program Objectives A basic statement of what the data matching program is trying to achieve.

What action, administrative or otherwise, may be taken as a result of the data matching program Action resulting from the program This should cover all agencies that use the results of the matching. If the agency is writing to the OAIC to depart from the Guidelines on public interest grounds under Guideline 10 Departure from Guidelines Any departure from the Guidelines on public interests grounds should be explained, and the specific exemption sought.

Reasons for deciding to conduct the data matching program The reasons for deciding to conduct the data matching program should cover the following matters. The legal authority for the uses and disclosure of personal information involved in the data matching program Legal authority The reasons should include the justification of the use and disclosure of personal information in terms of the Privacy Act and any other relevant legislation.

The protocol should specify which exceptions in APP 6 apply, and why. Alternative measures to data matching that were considered, and the reasons why they were rejected Alternative methods If it is considered that there are no practicable alternatives to data matching, the protocol should include a brief explanation of why this is the case.

Information about any pilot testing of the program Pilot programs Where a pilot program has been conducted, the following information is likely to be relevant and should be included: the number of records involved in the pilot program the number of matches that resulted an estimate or report of the benefits of the pilot program if the matches were acted upon, it may be possible to give a detailed account of the benefits; if the matches were not acted upon, an estimate of the benefits that would have resulted should be given , and information about any problems or difficulties with the matching program that was obtained from the pilot program If the protocol relates to a new data matching program rather than one already operating and no pilot project has been conducted or is planned, the protocol should indicate why a pilot program is not considered to be necessary.

A statement of the costs and benefits of the data matching program Costs and benefits See Appendix C: Statement of costs and benefits for data matching programs regarding the preparation of a statement of costs and benefits.

Risks The technical standards report should identify any risks posed by the data matching program including, but not limited to, risks to the privacy of individuals, reputational risks, and risks relating to incorrect matches. Data quality controls and audit The technical standards report should clearly document: any relevant measures taken to ensure data quality for example, the timing of any extract files that may be taken for the data matching program any audit processes to which the data used in the data matching program has been, or is regularly, subjected e.

Security and confidentiality The technical standards report should clearly document the precautions proposed to be taken at all stages of a data matching program to ensure that personal information used in and arising from a data matching program: is not subject to accidental or intentional modification is not accessed by staff within the agency except where such access is necessary for the conduct of that data matching program or resulting action is not disclosed otherwise than as is intended by the program protocol The technical standards report should make specific reference to access controls such as password security, encryption, and audit trails, including logging of access.

Appendix C: Statement of costs and benefits for data matching programs Introduction Guideline 2 recommends that, prior to deciding to participate in or conduct a data matching program, agencies should take into account the estimated costs and benefits of conducting a data matching program.

As a matter of best practice, the OAIC recommends that agencies prepare a statement of costs and benefits as outlined in this Appendix: when starting a new data matching program as part of the program protocol , and when evaluating data matching programs While it is desirable for the statement to be as comprehensive and rigorous as possible, it is not intended to be a formal cost-benefit analysis.

Sources of information Key sources of data on costs and benefits will be: for data matching programs that are already running, data obtained from the actual operation of the program. This should include in addition to more detailed information on costs and benefits basic data on: the total number of matches the number of cases in which matches led to further investigation the outcomes from investigation of cases for new data matching programs, any pilot program or other preliminary assessment of the data matching program.

If estimates of costs and benefits are based on results from pilot program, those results should be included While international comparisons may be useful in limited circumstances, the grounds of comparison are rarely firm. Methods of presenting information The best way of presenting the information will depend on the nature of the data matching program and the information available.

Agencies could consider the following formats for statements of costs and benefits: Compare the costs and benefits of the data matching program with the most likely alternative use of the resources required — that is, what those resources would be used for if the program did not go ahead.

The benefits of the alternative use of resources are, effectively, the cost of carrying out the program as they represent the opportunity cost of devoting those resources to the program. For example, if the resources used in the program have been diverted from a random audit program, then that would be the appropriate basis for comparison.

Compare the costs and benefits of conducting the data matching program against the costs and benefits of achieving the same result by some alternative method for example, a manual process. This may be most appropriate where: one of the main benefits of the data matching program is administrative savings from the more efficient performance of a task that would otherwise have to be carried out by other means, or the benefits of the data matching program are quantifiable, but are not financial for example, detection and prosecution of people breaking a law.

If the alternative uses of the resources required for the data matching program, or the costs of achieving the same outcomes by alternative means, cannot be ascertained, estimate the actual costs of the resources to be used in the program, and the expected benefits from the program, without making a comparison with an alternative scenario.

This option should only be used where it is impossible to apply either of the other approaches; it gives much less useful information about the data matching program and makes it much more difficult to judge whether it constitutes an efficient application of resources. If this approach is taken, the statement should include the reasons why neither of the other approaches could be taken.

Establishment costs Staff costs The OAIC suggests the following approach to estimating the cost of staff time involved in developing a new data matching project: Step 1: Estimate the amount of time in person weeks, months or years that will be spent by all staff on initial development of the project. Capital costs Most data matching programs do not require capital expenditure. Other costs It is not necessary to include other costs, such as publicity costs and use of computer facilities unless they are significant in magnitude.

Running costs Cost of conducting matching The cost of conducting the data matching program would include: staff time of both IT staff and administrative staff with continuing responsibility for managing the program IT services If these costs are negligible they may be excluded from the statement of costs; a statement that the costs are negligible and have been excluded should be included in the protocol.

Endnote 2—Abbreviation key Endnote 3—Legislation history Endnote 4—Amendment history An Act to provide for the matching of data in relation to certain assistance and tax and to amend the Privacy Act Part 1 — Preliminary.

This Act commences on the day on which it receives the Royal Assent. Chapter 2 of the Criminal Code applies to all offences against this Act. Education Department means the Department that is responsible for administering the payments known as child care benefit and child care rebate. TFN data , in relation to a person, means:. The steps in a data matching cycle are as follows:. STEP 1. The assistance agencies give the matching agency the basic data about persons that is held by those agencies for the purposes of personal assistance.

The matching agency checks the validity of the TFN data given under paragraph 1 by using any algorithm given to it for the purposes of this Act by the tax agency. Where the check identifies TFN data that appears to be incorrect, the matching agency gives particulars of the data to the source agency that gave it.

STEP 2. The matching agency extracts from data given to it in Step 1 the TFN data, and any identification numbers for the purposes of personal assistance, of assisted persons.

The matching agency gives the tax agency the data extracted under paragraph 5. STEP 3. The tax agency uses tax data from not more than the 4 financial years immediately before the current financial year and data given to it under Step 2 to find out the following available data in respect of each person who has a tax file number:. The tax agency gives the matching agency the data found out under paragraph 7 and any identification numbers for the purposes of personal assistance of the person.

STEP 4. The matching agency carries out identity matching by matching the personal identity data given under paragraph 8 with the family identity data given to it. Where there is an unresolved discrepancy in data given to the matching agency by a source agency, the matching agency gives the source agency particulars of the discrepancy.

STEP 5. The matching agency carries out payment matching by matching the following data given by assistance agencies in Step Where the matching of family identity data given by assistance agencies in Step 1 cannot identify a person for the purposes of paragraph 12, the matching agency matches TFN data given to it in Step 1 with the data being matched under that paragraph.

The matching agency carries out income matching of persons by using any identification number for the purposes of personal assistance of a person to match:. If the source agency and the matching agency have agreed that this paragraph applies, the following subparagraphs apply:. STEP 6. The matching agency gives to each source agency the results of matching under earlier steps that are of concern to that other agency and have not been given to the other agency in an earlier step, being results that indicate:.

Information exchanged in paragraph 15 may include the return of TFN data from the matching agency to an assistance agency. Note: Section 34C of the Acts Interpretation Act sets time limits for giving reports to Ministers and for presentation of reports to the Parliament. Commissioner means the Information Commissioner acting in the performance of the privacy functions within the meaning of the Australian Information Commissioner Act Payments of any personal assistance made because of the operation of subsection 11 1 must be made out of the Consolidated Revenue Fund, which is appropriated accordingly.

Endnote 1—About the endnotes. The endnotes provide information about this compilation and the compiled law. The following endnotes are included in every compilation:. The abbreviation key sets out abbreviations that may be used in the endnotes. Legislation history and amendment history—Endnotes 3 and 4.

Amending laws are annotated in the legislation history and amendment history. The legislation history in endnote 3 provides information about each law that has amended or will amend the compiled law.

The information includes commencement details for amending laws and details of any application, saving or transitional provisions that are not included in this compilation. The amendment history in endnote 4 provides information about amendments at the provision generally section or equivalent level. It also includes information about any provision of the compiled law that has been repealed in accordance with a provision of the law. The Legislation Act authorises First Parliamentary Counsel to make editorial and presentational changes to a compiled law in preparing a compilation of the law for registration.

The changes must not change the effect of the law. Editorial changes take effect from the compilation registration date. If the compilation includes editorial changes, the endnotes include a brief outline of the changes in general terms. Full details of any changes can be obtained from the Office of Parliamentary Counsel.

Misdescribed amendments. A misdescribed amendment is an amendment that does not accurately describe the amendment to be made. Endnote 2—Abbreviation key. Endnote 3—Legislation history.

Application, saving and transitional provisions. Social Security Legislation Amendment Act Schedule 3 item 53 : 30 June e.

Student Assistance Amendment Act Schedule 2 Part 2 : 1 Jan f. Part 2 ss. Part 3 ss. Part 4 s. Schedule 18 items 1—3 : Royal Assent l. Part 4 ss. Schedule 2 items 3—10 : Royal Assent o Schedule 2 items 11—13 : 1 Jan o.

Schedule 2 item 48 : p. Schedule 2 item 11 : 1 July q. Schedule 3 items 1, 2 : 30 June r. Income Tax Consequential Amendments Act Schedule 1 items 9, 10 : s. Schedule 2 item 2 : sa. Schedule 6: Royal Assent t. Schedule Royal Assent u.

Schedule 5 items 28, 29 : 1 July v Schedule 13 item 9 : 1 July v. Schedule 7 item 11 : 1 Apr w. Schedule 5: 1 July x. Schedule 2 item 1 : y. Youth Allowance Consolidation Act Schedule 5 item 1 : Royal Assent z. Schedule 4 item 1 : za. Schedule 3 item 13 : 1 July see s. Schedule 8 items 82—86 : Royal Assent. Schedule 1 items 17, 18 : Royal Assent.

Freedom of Information Amendment Reform Act Sch 5 items 27—31 and Sch 7: 1 Nov s 2 1 item 7. Schedule 1 items 34, 35 and Schedule 2 items 1, 2 : 1 Oct see s. Schedule 7 item 46 : 19 Apr Human Services Legislation Amendment Act Schedule 4 items 56—67 : 1 July Schedule 1 item : 1 Oct Sch 5 items —, and Sch 6 items 15—19 : 12 Mar s 2 1 items 11, 13, 19 Sch 5 item and Sch 6 item 1 : 12 Dec s 2 1 items 12,