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Fighting fraud using data analysis

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Modern day fraud investigations involve a truly vast amount of data. For investigators, trying to spot patterns and make links can be like looking for a needle in a haystack. Keeping up-to-date with the latest technological advances can make all the difference.

What is data?

Rather than the traditional image of combing a physical crime scene for tangible clues or forensic traces, investigations cover any research and analysis that works with qualitative and quantitative data to make links, provide evidence, deliver key information, or identify risk.

Where once ‘data’ meant tables of names and numbers, it now covers all manner of digital content: from social media posts, to emails, blogs, news articles and websites. Consider that anyone with access to a computer or phone can be a content creator, and you start to get an idea of the quantity – and variety – of data available to explore.

Data analysis – a weak link?

For investigators engaged in manually analysing this data, the sheer quantity of content available is more hindrance than help. Swamped with information across various domains and formats, in some cases even the most dedicated investigator could take years to amalgamate these data, convert them into a readable format, analyse them for patterns and links, and draw conclusions from this analysis. Add to this the pressures of deadlines from courts and investors, as well as limited human resource, and it’s understandable why data analysis is often considered the weak link in the investigatory chain.

Fraudsters are happy to take advantage of this weak link, exploiting ignorance about, or lack of, new technology to evade the investigator. Take cryptocurrency, for example. As a sector that’s still in its infancy, and with less regulation and legislative oversight than traditional financial markets, it remains a popular breeding ground for fraudulent activity. Without the right skill set, investigators working in the crypto space have little chance to identify criminals or trace stolen assets. Click here for an article by Mikhail Lastovskiy and Emily Drake which further examines digital asset tracing and its challenges.

Advancements in data analysis technology

The advancement in data collation and analysis technology is arguably one of the most exciting and useful areas for investigative teams to harness. If investigators can keep on top of technological advances and upgrade their digital skills, it can be a gamechanger. The Panama Papers investigation, for example, used node relationship graphs to plot out social media and business relationships – a join-the-dots exercise that helped link some of the world’s biggest names to financial fraud and tax evasion.

Natural Language Processing technology is another tool that helps investigators comb large quantities and varieties of text for sentiment – particularly useful when you consider the number of tweets, texts, DMs and articles that are uploaded to the digital space every second. This technology can also help distinguish between text created by a real person, and ‘bot’ text, thus helping to separate the ‘wheat from the chaff’ on platforms such as Twitter, where fake accounts and automatised posts abound.

Making the most of these powerful technologies requires some knowledge in programming language, which is why it is advisable to work with an investigative business that specialises in data analytics and digital asset tracing. This is one of the most effective and efficient ways to turn your collection of data into the evidence that you need. New technology can be daunting, but harnessed properly, is one of the greatest weapons we have in the fight against fraud.