Banking Fraud Case Study

Banking fraud covers a wide range of areas that include cheque, credit card and online banking fraud. All areas are susceptible to fraudsters; some more likely than others for example online fraud is more popular than phone banking fraud due to technology advancements in the last decade.
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In 2013, £450.4 million was lost to credit card fraud which is an increase from 2012 by 16 per cent which totalled £388.3 million (UK Card Association, 2014). 2011 saw a total loss of £341 million (MoneySuperMarket, 2011). However, in 2008 saw credit card fraud at its highest, £610 million, since then figures have dropped (MoneySuperMarket, 2011). Appendix 1A shows the decrease of fraud since 2008.
MoneySuperMarket is a website that is known for helping

The figures are unlikely to be accurate from HMRC as in recent years they have announced that they have made an error in the processing of some applications. They either have to give back money to tax payers or either demand that taxpayers give back money that they are owed. If they can’t calculate correctly how much people owe or are owed, then how likely is it that they’re going to be able to correctly estimate fraud statistics.

Benefit Fraud

Twice a year, the government release estimates of fraud and error in the benefit system. These estimates come from the Department of Work and Pensions, DWP. Figures released for 2013/14, suggest by the DWP that only 0.7% of welfare spending is accounted for benefit fraud (West. B, 2014, DWP, 2014). This equates to £1.2 billion pounds of the £164 billion spent on benefits (DWP, 2014). Appendix 2 shows how much the Government spent on benefits and then how much of the benefits was fraudulent or an error. Benefit fraud compared with claimant/official error is behind by one billion pounds and shows us that claimant/official error seems to be more of a problem than benefit fraud. The previous year’s statistics, 2012/13 remained the same at £1.2 billion (Department of Work and Pensions, 2013). Viewing these figures from the government, fraud is a minor estimate that contributes to the overall spending on

Upon further research it seems that the NFA have misinterpreted both ABI and IFB. £1.3 billion was recorded to have cost this much, but they believe that a further £2.1 billion could still be undetected (Insurance Fraud Bureau, 2014). ABI and IFB have both reported the same statistics in their reports along with other websites, which makes them more credible unlike NFA which have reported incorrect statistics. Therefore, there may be other statistics that might be incorrect in NFA’s report.

Mortgage Fraud

In 2012 the rate of mortgage fraud increased to 38 in every
10,000 applications which has risen from 35 in every 10,000 in 2011. (Eaves. D, 2013). In 2013, applications significantly increased to 82 out of every 10,000 mortgage applications were found to be fraudulent, compared with 2014 mortgage applications that were fraudulent dropped to 79 in 10,000 (Experian, 2014). These applications have been blamed for the rise of mortgage fraud. Experian, a credit referencing website, produced a report in 2013 to show that mortgage fraud has been on the rise for the past 6 years (Experian, 2013).

Experian is an independent company that helps the government to produce reports on different types of fraud. As it is independent, they are less likely to fabricate statistics as they will not benefit from formulating data. Therefore this makes the data from this particular source more likely to be accurate and