Centrelink has revealed data-matching activities using Medicare data to flag more instances of suspected welfare fraud, but says the activity has been running for some time.

The activity is detailed in a data protocol published by Centrelink on Friday and first noticed by Darren O’Donovan, a senior lecturer in administrative law at La Trobe University.

The data-matching program targets identity, employment or income-based welfare fraud, the protocol states, noting that combining multiple datasets could be more effective than current methods.

“The data-matching program is designed to detect false, manipulated and assumed identities used by customers in submitting multiple claims,” Centrelink said in the protocol [pdf].

“It is also designed to detect false information provided by customers relating to employment, medical eligibility and relationship circumstances.

“A key objective of the data-matching program is to make more comprehensive and strategic use of Medicare data, where matches are used to add intelligence value to cases suspected of being fraudulent.”

The program attempts to match “identities and details” held in Centrelink and Medicare records.

It specifically looks for “individuals who are not recorded as having experienced a series of expected ‘life events’ across both programs.”

“Where expected life events have not occurred this may highlight high-risk identities and the need for further analysis to determine possible fraudulent behaviour and/or record correctness,” Centrelink said.

Centrelink said that “high-risk” individuals are investigated by a fraud team.

If nothing is found in the investigation, the exercise is simply treated as a “data cleansing activity”, whereby Centrelink is able to update its data holdings on that person.

However, in instances where fraud is still suspected, the case can be referred to prosecutors or result in a debt and/or suspension or cancellation of benefits.

Centrelink said it currently bases fraud assessments either on “individual risk indicators”, on tip-offs phoned in anonymously or on “staff referrals”.

“However, DHS [the Department of Human Services] cannot rely on tip-offs from members of the public and staff referrals alone to detect identity fraud,” the agency said.

“This data-matching program aims to build on existing fraud detection methods and current data-matching capabilities by extending the range of information on which investigations are based.

“Information is being sought outside current data-matching programs and will enable a more informed assessment of potential persons of interest and individual circumstances and how this information may relate to the risk of fraudulent behaviour.

“The combination of Medicare registration and usage dates, with Centrelink held ‘life event’ data, provides a unique insight to the use of a claimed identity over time, which cannot be otherwise replicated.”

While an earlier version of this story indicated the protocol was new, it appears that the protocol - and the data-matching activity - has been in place for some time.

How long it has been active for is still unclear. Clarification was being sought by iTnews.

What is new is the decision by the department to publish details of the exercise and protocol, which Department of Human Services general manager Hank Jongen said was taken in association with the Office of the Australian Information Commissioner (OAIC).

"This process is not new. We are enhancing the already established data sharing arrangements between Centrelink and Medicare to better protect people from identity crime," Jongen said in a statement to iTnews.

"The misuse of identity information for fraud and criminal purposes causes substantial harm to the economy and individuals each year.

"This is just one of the tools we can use to detect potential fraud and matches with community expectations in allowing our two systems to ‘talk’ to each other.

" We voluntarily published these protocols in the interest of being transparent and to meet recommendations from the OAIC."

Jongen said that "sensitive information, such as the nature of people’s medical services, is excluded from this process" of data-matching.

He claimed that one of the uses of the data-matching was to protect welfare recipients.

"One example of how this works is that we can identify attempted identity takeovers through our channels," Jongen said.

"We would then take action to prevent the customer from becoming the victim of identity fraud.

He added: "Where vulnerable or potentially exploited customers are identified the department will conduct further inquiries to ensure the customer’s wellbeing."

The Department of Human Services has relied in data-matching with Australian Taxation Office data to fuel its controversial robodebt program of welfare clawbacks over the past several years.

The robodebt scheme was this year revealed to have cost the government almost as much as it recovered.