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Centrelink Fuzzy Matching Is Broken By Design

31 January 2017
Justin Warren
Eigen Magic

In today’s episode of the Centrelink #notmydebt tail of fail we will dig into how the data matching process Centrelink uses is broken by design.

The specific part we’re going to look at is the way the business name matching process works. My source information is the Centrelink whistleblower document [PDF] which details the fuzzy name matching algorithm, sources who have worked at Centrelink in the past, and the Department of Human Services itself.

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DHS seems to think that “oh, but it’s the same system as it was when it was manual” is somehow a defense. That they even try this is extremely worrying. It implies they know that automating the system creates a significantly different one and hope you don’t notice (i.e. you’re an idiot) or they don’t realise that automating a flawed system might be bad (i.e. they’re idiots).

Why? Because the automation has gone from 20,000 checks a year to over 200,000 in six months. That’s a 2000% increase. 20 times more. If the manual system makes mistakes—and as we’ve seen, it very much does—then you’re now making a lot more mistakes. Automatically.

Automating a bad system makes it worse, not better.

We’re still finding out how long it will take DHS to discover this is true and act accordingly. “Keep digging” is not a good strategy here.

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