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Current Filter: Security>>>>>> Tackling the fraudsters Editorial Type: Opinion Date: 11-2013 Views: 3211 Key Topics: Security Cybercrime Fraud detection Big Data Key Companies: IBM Key Products: Key Industries: Insurance | |||
| Fraud is on the rise. Wherever you surf, tweet or otherwise go online, it rears its devious and lucrative head. Computing Security has been talking to Shaun Hipgrave, an intelligence analytics executive with IBM, about the implications of fraud and what can be done to counteract it Call it a 'scam', 'rip-off', 'cheat' or 'sting', but, whatever you call it, the impact of fraud hits businesses equally hard. And the bad news is that the number of fraud cases is not falling - but, in fact, rising. This June, the National Fraud Authority reported in its 2013 Annual Fraud Indicator that the loss to the UK economy from fraud stood at £52 billion. This figure can be further broken down into a cost of £20.6 billion to the public sector, £15.9 billion to the private sector, £9.1 billion to individuals and £147.3 million to charities. "Coupled with these eye-watering potential losses, there is also the threat of possible incoming legislation businesses will need to contend with," says Shaun Hipgrave, an intelligence analytics executive with IBM. "Under current proposals floated by the UK Serious Fraud Office (SFO), companies will potentially be liable for failing to prevent fraud or theft by their employees. This would make it easier for the SFO to prosecute companies, as well as individuals."
COUNTERACTING CRIME "So the pressure is on for companies to find effective solutions to detect and prevent fraud, which can cause significant harm to businesses and society as a whole," states Hipgrave. "To counter the risk of attack from increasingly sophisticated fraudsters, organisations need to tackle fraud in a smarter way." There are three aspects of smarter fraud investigations that are worth investigating through the eyes of Hipgrave: smarter technology, improved data visualisation and better internal communication.
SMARTER TECHNOLOGY By using Big Data Intelligence analytics technology to combat fraud, businesses can identify fraud risk earlier, and easily uncover trends and patterns in large amounts of data, both structured and unstructured, and thus not only solve investigations, but also prevent crime. "An example of a company using technology to investigate and prevent crime is Griffins, the insolvency and forensic services company. Griffins have one of the largest teams of dedicated investigators covering insolvency and financial investigations in the UK. Griffins also provide services for creditors, debtors and professional advisors. "Many of the cases Griffins handles are tracing the proceeds of crime, which involves analysing structured and unstructured data sources, such as bank statements, pdf files, emails, invoices and spreadsheets, establishing patterns and relationships, and making non-obvious connections between disparate sources of data." The IBM technology has moved Griffins from struggling with huge amounts of information stored in spreadsheets (in excess of 10 Terabytes) to a faster, more accurate, intelligence-led approach that helps solve cases related to money laundering, missing trader fraud and theft of company assets, Hipgrave points out. As Stephen Hunt, insolvency practitioner at Griffins, has said: "… the IBM technology has a lot of future potential for our business as a critical support tool, because of its ability to do the thinking for us. The speed by which we are now able to accurately present and demonstrate the results of investigations is remarkable." Technology is also key for the public sector, and a lack of smart fraud detection and prevention solutions can have expensive consequences, advises Hipgrave. "The student loans fraud scandal, widely reported in the media earlier this year, is a good example. Two fraudsters cheated the Student Loans Company out of £370,000 by submitting false applications. They supplied fake A-Level exam certificates for people who didn't have the qualifications they needed to get into university. In total, 174 requests were submitted, some using the same fake identities. But the supporting technology used by the Student Loans Company was unable to detect duplicates and the fraudulent activity went undetected for some time." With smart fraud detection and prevention solutions, however, each interaction leaves a trail and therefore an opportunity to identify fraudulent activity.
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