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Wise up women or get scammed silly online!

Wise up women or get scammed silly online!

The type of person most likely to get scammed online has been revealed. Do you fit the description?

Robert Powell

Rights, Scams and Politics

Robert Powell
Updated on 19 November 2010

Online fraud is a significant threat at this time of year for us all, but it appears that for certain people, it may be an even bigger problem all year round.

New research by knowthenet.org.uk has found that professional women aged 25-34 are most likely to fall victim to online scams. They’ve even created an e-fit image of the type of person they think is more susceptible to online fraud than anyone else (the image on the left).

Now I know what all you cynics out there are thinking; how can anyone deduce this kind of stuff? So with that in mind, let’s take a closer look at the research and find out whether you could be a prime target for scammers.

The research

The research was carried out using an online test that was taken by 2000 people to measure their ability to spot and respond appropriately to online scam scenarios. Typical scenarios included identification of fake Facebook pages and bank e-mails, as well as decision-making tasks aimed at distinguishing counterfeit goods from real goods. You can even take the fraud test at threattest.knowthenet.org.uk and find out how prone to online scammers you are.

The results show that, in six of the seven tests, women were most likely to fail – with the age group of women most likely to fall for the scam being those between 25 and 34.

The test was also able to distinguish different types of victims;

  • ‘The Mark’ – Female, 25–34 in full time employment in the North of England. This type of person will fall for all the scams. Christmas come early for the fraudsters!
  • ‘Phisherman’s Friend’ – The same demographic as ‘The Mark’ but based in the South. This type of person will give away credit cards details or passwords to fake sources.
  • ‘The Competitor’ – Younger than ‘The Mark’, but still female. ‘The Competitor’ will send away personal details in an attempt to win a prize – which won't really exist, of course!
  • ‘The Good Samaritan’ – Male, 35–44, married and based in the North. This type of person is an honest do-gooder who’ll get tricked into helping a fake person in distress.
  • ‘Bargain Bidder’ – Female, over 55 and based in the North. This type of person will always be on the look of for a good deal and hence may fall for fake auction scams.
  • ‘Fashion Victim’ – Same social group as the ‘Bargain Bidder’, but the ‘Fashion Victim’ will be after expensive brands at low prices – a prime target for counterfeit goods traders.

So there you have it – which group do you fall into?

Follow these top tips to protect yourself against ID fraud

How accurate?

While this research is useful in distinguishing common characteristics among possible fraud victims – it’s definitely worth taking it with a pinch of salt. Obviously the stats have been interpreted in a very general, social-demographic way – and this doesn’t really allow for any individual variations.

I won’t need to tell anyone that categorically stating that any person who resembles the e-fit photo you can see above will definitely fall for a scam is as ridiculous a statement as saying that an 18 year old man from Portsmouth will never ever be affected by online fraud. But I don’t believe that’s what knowthenet.org.uk are really trying to say with this study.

It’s also important to remember the context that the research was carried out in. If you knowingly took part in a test designed to identify the groups of people most susceptible to online fraud it’s pretty likely that you’d be on the lookout for anything suspicious. You may not be so vigilant if a phishing e-mail came through on a Sunday afternoon requesting that you update your bank account details.

A big problem

Cynicism aside, if people are still falling for scams presented to them as part of a fraud test, it shows how dangerous the problem is and reinforces the need for constant vigilance when shopping online.

What’s worse is that fraudsters are constantly cooking up new, sneakier ways to separate you from your hard-earned cash. A recent scam involving the sale of phony gig tickets has cost the economy £12 million already. Yet many people are not reporting being defrauded, as the scammers are encouraging victims to claim back the money lost on the fake ticket from their credit card company – using the section 75 insurance rules guaranteeing spending protection. To find out more about this sneaky scam read John Fitzsimons article Scammers exploiting protection meant for you!

Don’t be scammed! Emma Roberts reveals some dangerous scams that are circulating the web

Credit report damage

Overall, online fraud affects 1.8 million people every year and costs the economy £2.7 billion – not to mention the personal grief and hassle it can cause if you’re scammed. If someone steals your identity by obtaining personal details online it can also completely mess up your credit rating and affect your ability to get a mortgage or credit card.

Research carried out by CPP estimates that 900,000 Brits have had their credit rating unfairly damaged by fraudsters. What’s more, half of them said it cost them financially – with the monetary repercussions averaging out at over £7,000 each. On average it also takes nearly 14 months to bring a damaged credit report back to full health after a scammer has had their way with it.

Head over to New online threat that will wreck your Christmas to read about how you can protect yourself from online scammers this festive season.

Finally, to find out more about different types of scams both online and offline read Rachel Wait's run down of The five most common types of fraud.

What do you think?

Do you feel more prone to fraud because of your age group or general honest demeanour? Is it possible to distinguish a certain type of person who’s most likely to be scammed? Or is research like this just scare-mongering rubbish?

Let us know your thoughts in the comment box below.

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