Part 3: Detecting benefit fraud
3.1
In this Part, we outline our expectations for the detection of benefit fraud and present our findings and recommendations on how the Ministry:
- receives and manages allegations of benefit fraud; and
- detects cases of suspected benefit fraud.
Our expectations
3.2
Early detection of benefit fraud is critical for the Ministry to protect the integrity of the benefits system. We expected the Ministry to have effective systems, policies, and procedures to:
- manage allegations of benefit fraud – this includes encouraging reporting by staff and members of the public of suspected benefit fraud, as well as recording, tracking and taking action on all allegations received; and
- proactively search for, and detect, suspected benefit fraud – this includes using risk profiling to assign detection (and subsequent investigation) resources to identify higher risk areas and benefit types, and ensure that detection activity is cost-effective.
Receiving and managing allegations of benefit fraud
Our findings
3.3
The Ministry has several systems and procedures in place to receive and manage allegations of benefit fraud from staff and members of the public.
Staff allegations and suspicions of benefit fraud
3.4
There are formal and informal systems for Ministry staff to advise Benefit Control staff if they suspect that a client may be committing benefit fraud. Work and Income staff can raise allegations (known as “file suspicions”) using an intranet allegations email link which connects to the relevant regional Benefit Control Unit. They can also directly contact Benefit Control staff to discuss concerns about a client’s circumstances and the potential for benefit fraud. Benefit Control Investigators are assigned in a liaison role with each Work and Income service centre and provide training on identifying anomalies in a client’s circumstances that may indicate benefit fraud. Work and Income service centre staff told us that Investigators are accessible and available to provide guidance in cases where staff have suspicions about possible benefit fraud by clients.
3.5
The Ministry has a protected disclosures policy to protect staff making allegations of benefit fraud. Staff can use the Ministry’s intranet site to get guidance on making a protected disclosure.
Allegations of benefit fraud from the public
3.6
The Ministry has several systems in place for the public to make allegations of benefit fraud. Allegations can be made in writing, in person at Work and Income service centres, by email, or by using the free-call Benefit Fraud Allegations telephone line. The free-call telephone line is the method most frequently used by the public when making allegations of benefit fraud. The Benefit Fraud Allegations telephone number is listed in telephone directories, on benefit fraud promotional posters and pamphlets, and on the Work and Income website.
3.7
Staff use prescribed procedures to systematically record information received on the Benefit Fraud Allegations telephone line. Call-takers are trained and given scripts to ensure that they collect necessary information to enable any subsequent investigation of allegations. Allegation details are forwarded to the relevant regional Benefit Control Unit for a determination of whether the allegation requires investigation.
3.8
All allegations of benefit fraud are recorded and tracked in the Benefit Control Unit’s computerised case management system, TRACE. This system records basic logging information, such as case received dates, case allocation dates, and case completion dates. The Ministry’s policy is to act on all allegations of benefit fraud. We discuss the assignment of allegations of benefit fraud for investigation in Part 4.
Detecting suspected cases of benefit fraud
Our findings
3.9
Data matching is an important tool used by the Ministry for detecting possible benefit fraud. It involves the electronic comparison of millions of records every year to help limit and prevent benefit overpayments. Data matching results in the detection of many potential benefit fraud cases. There is potential for the Ministry to use its recently introduced Intelligence Unit to help evaluate and review its data-matching and other detection activities.
Data matching
3.10
Data matching is the use of electronic matching of personal records held by different agencies to determine if benefit fraud has been committed. The computerised scanning of personal data held in different databases can help identify situations where the Ministry’s clients have not accurately informed the Ministry of changes in their circumstances that affect their benefit entitlements. Some examples of personal circumstances that clients can mislead the Ministry about, that data matching can help detect, include failure to disclose:
- hours worked in paid employment;
- amount of income earned; and
- personal relationship situations.
3.11
The Ministry has a centralised National Data Match Centre for running and managing its data-matching activities. Activities include regular data-matching scans, as well as some targeted matching.
3.12
The Ministry’s data-matching activities are extensive. For example, in the year to 30 June 2007, the National Data Match Centre compared more than 12 million records with other agencies. This resulted in 193,358 matches and 18,588 cases of overpayments. The total value of these overpayments was $19 million.
3.13
Figure 6 sets out in more detail the range and scale of the Ministry’s data-matching activities used for the purpose of benefit administration.
Figure 6
The Ministry of Social Development’s data-matching arrangements with other government agencies for benefit administration
| Agency | Frequency of match |
|---|---|
| Accident Compensation Corporation | weekly |
| Department of Corrections | daily |
| Department of Internal Affairs (births, deaths, and marriages) | weekly |
| Inland Revenue Department | |
| – benefits – students |
two-monthly monthly |
| New Zealand Customs Service | weekly |
| New Zealand Housing Corporation | weekly |
Source: Ministry of Social Development
Systems, policies, and procedures for using data-matching results
3.14
When a client’s details match those of clients of the other agencies, National Data Match Centre staff check the client’s details to ensure that their benefit entitlement is determined correctly. Centre staff liaise with Work and Income Case Managers if they are unable to confirm the correct entitlement. Unresolved concerns about a client’s benefit entitlement are forwarded to the Benefit Control Unit for investigation.
3.15
There are systems in place to ensure that data matching is appropriately managed. Comprehensive memoranda of understanding between the Ministry and other relevant public agencies state their data-matching arrangements. The Privacy Commissioner monitors the activities of the National Data Match Centre. The Privacy Commissioner’s 2007 annual report stated that all data-matching programmes involving the Ministry had generally been conducted in accordance with the Privacy Act 1993 and information-matching rules.
3.16
Ministry staff also have clear code of conduct requirements for maintaining legal compliance when handling personal information.
Review and evaluation of the Ministry’s data-matching activities
3.17
The Ministry had not formally evaluated its data-matching activities at the time of our audit. However, we were told that the Ministry is planning to review its data-matching activities. This review is intended to examine the timeliness of data matches and also evaluate the existing mix of data matches. In our view, it is important that the Ministry regularly evaluates its data-matching activities to ensure their ongoing effectiveness for detecting fraudulent activity. Cost effectiveness of different data-matching programmes should also be periodically reviewed.
| Recommendation 3 |
|---|
| We recommend that the Ministry of Social Development regularly and formally evaluate the effectiveness of its data-matching activities for detecting benefit fraud. |
3.18
We also consider that there is strong potential for the work of the Intelligence Unit to be included in the evaluation and review of data-matching activities. The Intelligence Unit has advanced data analysis and filtering programs that could be used to help the Ministry identify emerging fraud risk areas that may not be covered by existing data-matching arrangements.
3.19
The potential advantage of using the Intelligence Unit to help evaluate data matching is illustrated by the large multiple identity fraud detected in late 2006 (see Figure 5). This fraud was committed by an offender using fake birth certificates to obtain other forms of identification and create multiple separate identities. In response to the benefit fraud, in April 2007 the Ministry began matching its client records against birth records held by the Department of Internal Affairs. The earlier existence of this data matching could have identified the fraud much earlier. Strategic risk assessment of data-matching activities might have identified the lack of a birth record match as a potential benefit fraud risk.
| Recommendation 4 |
|---|
| We recommend that the Ministry of Social Development use fraud risk assessments of emerging benefit fraud risks to help evaluate and target its data-matching activities. |
Other benefit fraud detection activities
3.20
Other activities the Ministry uses to detect benefit fraud include comparing staff lists of major employers with client records and selective client reviews. Establishing the Intelligence Unit in mid-2007 has enabled greater detection of potential multiple identity fraud cases for investigation by regional Benefit Control Units.
Benefit fraud detection work with employers
3.21
People receiving benefits are obliged to inform Work and Income if they find a job or change the number of hours they work, because this can affect their benefit entitlements. The Ministry uses data matching with the Inland Revenue Department’s employer database as the main mechanism to detect clients who continue to receive benefit payments while working. However, Benefit Control Units also carry out some detection work with employers.
3.22
Under section 11A of the Social Security Act 1964, the Ministry has the power to obtain information for data-matching purposes from employers. The Benefit Control Units use this power to target higher-risk client groups, such as seasonal or casual workers. Major employers of target client groups are selected to provide information about the names, addresses, and IRD numbers of their employees. The employee information is matched against the Ministry’s client databases to identify any clients who may be receiving benefit overpayments.
3.23
There is also a prevention aspect to this work. The Ministry has an employer liaison programme to advise employers about its power to obtain employee information, and to get employers to encourage their staff to advise Work and Income when they start work.
3.24
In the year to 30 June 2007, the Ministry reviewed 1556 cases under this programme. It resulted in identifying 648 cases of substantiated overpayments.
Selective client reviews
3.25
Selective client reviews involve Technical Officers in Benefit Control Units reviewing a targeted sample of clients whose circumstances or benefit type are identified through either national or regional analysis as being at higher risk of entitlement anomalies. The aim is to identify clients whose circumstances may require further examination to ensure that they are getting their correct benefit entitlement.
3.26
Technical Officers write to clients to request confirmation and clarification of their current circumstances if the Technical Officers’ review of known information suggests the possibility of incorrect benefit payments. Cases can be referred to Investigators for formal investigation if clients’ responses to these requests do not sufficiently address the Technical Officers’ concerns.
3.27
A new workflow model introduced in Benefit Control Units in late 2007 made changes to the work of Technical Officers. Benefit Control Units we visited had recently suspended or reduced selective client review work while the Technical Officers took on new roles assisting Investigators with their investigations. We were unable to assess what effect this change in doing selective client reviews will have for the overall detection of benefit fraud. The Ministry was reviewing the future operation of selective client reviews at the time of our audit.
Targeting risk with employer and selective client review programmes
3.28
Ministry staff informally monitor and discuss perceived risk areas as the main way of classifying risk categories for national and regional selection of target groups for selective client reviews. A similar methodology is also used for deciding which employers to target for review.
3.29
In our view, the Ministry could improve this selection process by using its recently introduced Intelligence Unit to contribute to the identification of higher-risk client groups. The Unit has advanced data analysis and statistical modelling programs that could be used to help predict benefit types more vulnerable to fraud, as well as defining the characteristics that can make a client more likely to commit benefit fraud.
| Recommendation 5 |
|---|
| We recommend that the Ministry of Social Development use its Intelligence Unit to periodically analyse its client databases to ensure that detection programmes are targeting areas of risk. |
Detection work by the Intelligence Unit
3.30
The establishment of the Intelligence Unit in mid-2007 has improved the ability of the Ministry to detect cases of multiple identity fraud. This includes sophisticated computer analysis systems for creating graphical pictures of information stored on the Ministry's databases. These are used to automatically create links between clients and information they have provided to the Ministry, and help to see if links exist between different clients.
3.31
The Benefit Control Units we visited reported that they have been able to detect a few cases of multiple identity fraud as a result of using the Intelligence Unit and its more sophisticated detection resources.