Using data to tell a genuine mistake from outright evasion

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While the constant talk about budget cuts might have the feel of a scratched record, we can’t escape the reality of today’s straitened economic circumstances. But there is something that tax and welfare agencies can do to lessen the impact. A bold statement perhaps, but nonetheless accurate. With an increasing need to fund the welfare […]

While the constant talk about budget cuts might have the feel of a scratched record, we can’t escape the reality of today’s straitened economic circumstances. But there is something that tax and welfare agencies can do to lessen the impact. A bold statement perhaps, but nonetheless accurate.

With an increasing need to fund the welfare state in G20 countries, we know that cutting costs is no longer enough. Governments must protect their revenue streams. Tax avoidance and error costs 145 countries, representing over 98% of world GDP, more than US$3.1 trillion annually. Only last weekend the finance ministers of Britain, France, Germany, Italy, Poland and Spain met to deliberate how to improve the targeting of tax evasion in the EU. No small feat when statistics show that the EU is losing €1 trillion through tax evasion.

However, we’re already seeing a number of tax agencies getting to grips with this situation. How? By using data to enhance their ability to identify tax evaders and tell the difference between genuine error and criminal attack.

At its simplest level, let’s consider a taxpayer who declares an income of $40,000 a year. With the right technology and processes in place, it’s possible to match his tax return against data from other government agencies, credit reference agencies, or publically available registries. These might provide us with lifestyle indicators suggesting that he possesses properties abroad and a high-spec car – way beyond the reach of a $40,000 salary.

This has become a reality in the UK where tax agency HM Revenue & Customs (HMRC) is among those already turning analytics into a tax yield success.

Capgemini delivered HMRC’s award-winning strategic risking system “Connect”, which takes information from 30 different data sources, cross-matches one billion internal and third party data items, and uncovers hidden relationships across organisations, customers and their associated data links (bank interest, lifestyle indicators and stated tax liability). The solution, which includes data analysis and data mining products and tools from SAS, underpins HMRC’s ability to focus skilled resources on businesses, individuals and sectors that pose the highest risk of error, fraud and criminal activity.

And the result? HMRC has already recovered over £1.4bn in additional tax yield using Connect. That’s surely an eye opener for other agencies seeking to deliver new capabilities that protect tax yield and reduce welfare benefit evasion.

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