I am interested to read the EC’s recent economic policy recommendations to individual Member States. They’re all about boosting growth, increasing competitiveness and creating jobs.
My interest lies in the value that effectively dealing with fraud can add to one of the key recommendations: to bring down debt.
Clearly, tax fraud is just one of many contributors to sovereign debt, and I’d be naive to suggest otherwise. But if bringing down debt is viewed by the EC as one of the requirements for strengthening conditions for sustainable growth, then we need to look at debt from every angle, including the impact of fraud.
In the UK, it is estimated that tax evasion (as opposed to avoidance) costs the government £5 billion a year. In Switzerland, the Geneva branch of the private banking arm of a well-known global bank is currently suspected of helping French citizens defraud France’s tax department of more than €4 billion. I could go on, but these two examples clearly illustrate my point that tax fraud – or rather tackling it – has the potential to make a dent in national debts.
I’m very much an advocate of using Big Data in this respect. The more a tax agency knows about a taxpayer, the better able it will be to assess whether the right income is being declared and the correct tax is being collected.
The ability to source, match and mine new data sources, including external and unstructured data sources (such as social media) is one of the attributes of Capgemini’s fraud and error solution Trouve. This helps to build a comprehensive picture of an individual or organization across multiple taxes. And it uses a range of analytics techniques to identify and group high risk cases, such as undeclared inheritance tax or rental income – all of which helps in the fight against fraud.
There’s a lot more information about Trouve and our work in tax and welfare on our website