For as long as there have been taxes there has been a tax gap, with tax inspectors responsible for reducing the difference between what the state collects and what it is owed. Tax is a great non-negotiable in a world where, as Benjamin Franklin famously noted in 1789, ‘nothing can be said to be certain’, but tax avoidance and evasion are constants too, and evolve to exploit the system’s ever-changing rules and weaknesses.
In 2012, five years into a financial crisis which has been compared by many leading economists to the Great Depression of the 1930s, politicians and commentators from both ends of the political spectrum are striving to outdo each other in their condemnation of tax evasion and (mostly legal) avoidance, which by reducing tax yield compromise a government’s ability to fund effective public services and reduce deficits. In the UK, Chancellor George Osborne described tax avoidance as ‘morally repugnant’ in March’s budget speech, and recently tasked HMRC’s Chief Executive Lin Homer with bringing in an additional £17bn of revenue in the year ahead.
Tax agencies face major challenges in achieving goals like these. As austerity dictates reduced government spending in many developed economies, most are being asked to deliver better results more efficiently. The resources they can devote to tackling compliance on a case by case basis are necessarily limited. The demands they face for better customer service often appear difficult to reconcile with the enormous complexity of a government’s evolving tax policies, and the depth of expertise required to resolve complex tax queries from any kind of organisation or individual.
From the point of view of technology, the main obstacle to combating fraud is being able to make use of the huge volume of data which a tax agency collects and analyse it smartly to reveal where avoidance and evasion might be taking place. Agencies need technology systems that can assess citizens’ and businesses’ tax affairs automatically, and flag up specific kinds of cases for investigation by experts. The workload can then be focused on the highest-value cases where risk and return appear greatest.
Two technology trends make this goal more and more achievable. Firstly, developed countries continue to move towards online in public services. This means that tax returns and financial information are increasingly digitised. Secondly, the business intelligence and analytics products which allow agencies to exploit this information are becoming more sophisticated.
Tax agencies taking advantage of both trends are benefiting from year-on-year improvements in compliance and yield. Only a few years ago the lack of interoperability across rigid departmental systems made uncovering fraud a very labour-intensive task. The architecture was determined more by the boundaries between tax regimes than customer groupings or behaviour. Now, it’s now possible to develop solutions which quickly interrogate billions of data items from different sources and systems, showing anomalies, and tracing the relationships between the parties responsible for them.
HMRC’s Connect tool, implemented by Capgemini and underpinned by cutting edge technology from Detica and SAS, illustrates what can be achieved through business analytics and intelligent use of risk profiling. It has delivered a £1.3bn increase in yield so far with 40% fewer risk and compliance staff to tackle cases, and by bringing together data from across tax regimes makes it easier for HMRC to form multi-disciplinary units to tackle specific risk profiles.
Whatever the economic outlook, the logic and efficiency of systems like Connect mean that governments will increasingly come to depend on them to fund our public services.