The welfare state loses revenues that are too good to let go

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The welfare state loses revenues without fraud prevention

Too Good To Go has made it possible to reduce food waste by bringing customers and the business community together on a shared platform.

The startup Too Good To Go dreams of a world where food is eaten and not thrown away. Its popular app will benefit businesses, customers and the environment. The businesses will earn extra revenue on what was previously wasted, the consumers will get a good meal at a much lower price and the environmental impact will be significantly less due to the reduced carbon footprint. With a simple app, Too Good To Go has made it possible to reduce food waste by bringing customers and the business community together on a shared platform where overproduction is converted into something that benefits everyone.

Could we apply the same idea to our welfare state?  It is becoming increasingly stressed by budget challenges, not least due to the growing requirements for public services and new tasks resulting from a globalised world. This includes increased pressure to find labour so that our economy can grow faster.

It is becoming more and more difficult to find out how to increase revenues to cover the rising investment needs and growing requirements for public services. In a recent study, McKinsey has pointed out that, on average, our welfare state loses 20 percent of its revenues – a significant amount – as a result of missing tax payments, unwarranted payments and fraud involving public funds. This is a waste of society's resources which, it would be fair to say, are too good to let go. Maybe it's time for us to put a massive focus on reducing this waste of resources and thereby increase the resources we have available to improve our opportunities for better service levels and growth.

The good news

We have never before had so many opportunities for analysing large amounts of data quickly and effectively. It has become cheaper to store data, and it has become easier for the welfare state to compare and decode potentially damaging social behaviour involving missing payments and/or fraud with public funds. This is because with our high degree of digital communication with the welfare state, including digital access to public services as citizens and companies, we leave a lot more digital traces than previously.

It has been SAS’ experience that applying big data, AI and machine learning to this data has shown that it is possible to improve the welfare state's ability to reduce this waste of our public resources significantly by finding and preventing unwarranted payments, tax fraud and other noncompliant behaviour that leads to loss of revenue.

Our welfare state is well on its way to reducing waste with new legislation in Denmark. From the start of 2018, it will be possible for the Danish Business Authority to compare its own data from the CVR business register with data from SKAT (the Danish tax authority) and external data from the internet. On 14 December 2017, Department Head Carsten Ingerslev from the Danish Business Authority provided the newspaper Politiken with an example of how data sharing between agencies and AI can be used to prevent tax and VAT fraud.

Financial criminals often insert vulnerable individuals to act as straw men in their companies and use them to create several fictional businesses with significant equity, later using them for tax and VAT fraud. This can be prevented through the use of AI and algorithms that can find this behaviour and stop it before revenues are lost.

At SAS we have a great deal of experience with preventing resources from being wasted, and we have helped a lot of governments through a systematic use of AI and machine learning with public data that can both reveal and prevent fraud involving public resources. Over the course of many years, we have gained a great deal of knowledge about how criminals typically behave, but also about how systematic controls can significantly reduce the amount of money that is disbursed in error.

Finacial crime and fraud can be prevented through the use of #AI and algorithms that can find noncompliant behaviour and stop it before revenues are lost. #fraud Click To Tweet

Here at SAS, we think that this waste of resources is too good to let go. Just as Too Good To Go helps to reduce food waste, we can have an impact by reducing further losses of revenue. As good examples of areas where an effort might be needed, and where there are great societal gains to be made, we can mention:

  • Student grants disbursed in error or due to fraud
  • Tax and VAT evasion
  • Welfare benefits disbursed in error
  • Unemployment benefits disbursed in error
  • Fraud involving public purchasing

SAS offers an interconnected technological platform that combines data mining with a comprehensive collection of algorithms to effectively shed light on criminal networks, potential fraud and damaging social behaviour. Read more about our public sector solutions here.

If you should have any questions concerning the above, we here at SAS are of course ready to discuss how we might be able to help.

The first version of this blog was published in Danish here.

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About Author

Lasse Skydstofte

Head of Nordic Government Advisory Services at SAS

Lasse Skydstofte is a highly accomplished senior business manager with more than 20 years of experience in multiple industries. His expertise is to provide consultation on business optimisation and strategy, including integrating key principles such as customer intelligence, business intelligence, balanced scorecard modelling, and activity-based costing to bring core focus to business activities, generate value, and reduce excess. Lasse is adept at guiding development and integration of innovative new software designed to provide customers with the tools needed to understand their markets.

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