A healthy intelligence mix for the public sector: Artificial and natural

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Two or three years ago, "digital transformation" was just a phrase. Today it is a reality. Across industries, including the financial sector and health care, obsolete and inefficient structures are being replaced. Services have become noticeably faster, less complicated and more available. But what about services provided by public sector organisations? There may be a lot going on, but there is still plenty of room for improvement.

Hidden Insights: A healthy intelligence mix for the public sector artificial and natural

A healthy intelligence mix for the public sector: Artificial and natural.

Personnel structure and legal requirements: Drivers of public digitisation

Anyone who has ever applied for a new passport will agree with that statement. Applications are often associated with significant waiting times. Faster service means going in person and waiting to pick up the passport. This level of inconvenience is increasingly met with incomprehension from citizens. Why am I paying through my taxes and in fees for this, when companies and service providers increasingly work flexibly around the clock using smart devices?

But the public sector is finally changing. Artificial intelligence is gradually finding its way into its administrative structures. This is mainly because of two drivers. The first is an acute staff shortage in many government organisations, which automatically leads to bottlenecks. Without algorithms, tax administration would actually need 20% more employees, or far more efficient automatic operations. The second point is “homemade”: The legal requirements at the state, federal and European level are often difficult or even impossible to implement without digital solutions.

Virtual agency and early fraud detection

But which solutions, exactly, are being used? For example, what can passport offices use to shorten the queues? The answer is chatbots. Although this sounds surprising, these have long been part of the standard customer service portfolio of service companies. These digital agents are available around the clock, never in a bad mood, and can respond to simple requests quickly and easily. Some systems even have the ability to check and process applications.

But AI in government agencies saves more than time. It can also make a contribution to the purse of the taxpayer by reducing fraud. In 2017, organised fraud related to benefits in Germany resulted in a loss of 50 million euros. The actual number of cases of fraud for all social benefits is likely to be much higher. Investigations require huge levels of human resources, and an increase in efficiency is expensive. To detect just 1% more fraud cases requires an investment of 400 million euros. One possible solution is to use a hybrid analytics model that compares locally collected data directly with a database held in the cloud. This will quickly identify patterns and anomalies and prevent fraud.

Border management and migration: A job for the digital civil servant

AI is also being used to improve border security. The legal requirements for cross-border movement place requirements on federal agencies. For example, the German air traffic safety regulations require information such as contact and payment details for all passengers to be forwarded to the Federal Criminal Police Office. In 2018, a total of 244.3 million passengers travelled through German airports. For agencies to use these data to identify suspicious connections and patterns, they need AI.

There are plenty of opportunities for AI to be used in the public sector. However, implementation is often slow. To accelerate this development, two main barriers must be removed. First, we need simpler software tools. Useful AI-supported solutions need to give each employee a quick and easy way to improve the algorithm through feedback, even when there is no data expert to hand.

The #PublicSector is finally changing. #AI is gradually finding its way into #administrative structures. This is mainly because of two drivers ... Click To Tweet

The second barrier to implementation is the administrative structure of public authorities. The early responses to the SAS Innovation at Scale study from government agencies suggest that the culture may be a crucial reason why innovation fails. Driving change from the top is essential in a bureaucratic structure, but many top managers do not really understand why AI is important. Without the "commercial incentive," it is also harder to make the case for change.

Ideally, governments need a model that links information about individuals across institutional boundaries. The resulting database would provide even better AI results and would be an important foundation for all areas of public administration – whether counterterrorism or just a new passport.

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About Author

Robert Ruf

Solutions Architect

Robert Ruf ist seit 2004 bei SAS und beschäftigt sich mit den Themen Business Intelligence, Data Warehousing, Business Analytics sowie Big Data. Als Experte für BI Lösungen, berät er Unternehmen in der DACH Region und teilt sein Wissen in Vorträgen und als Dozent an der Dualen Hochschule Baden-Württemberg. Robert Ruf hat in Mannheim Wirtschaftsinformatik studiert und zusätzlich einen MBA-Titel im Bereich „Information and Performance Management“ erlangt. Robert Ruf is advising companies on Big Data and Business Analytics. He is also a lecturer on modern BI.

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