6 steps for end-to-end processing of fraud and corruption detection


Detecting malpractice and crime – whether it is fraud, people smuggling, avoiding customs or organised crime – is a complex process. Detection is all very well and a necessary step. But what are the outcomes that your organisation needs? And what workflows and triggers do you need in place to achieve those outcomes?

In my role at SAS, I’m fortunate to hear stories and experiences from across the UK public sector. Talking to colleagues, such as Peter Snelling and Colin Gray, I’ve learnt that the best means of detecting fraud and other forms of crime and then being able to quickly and effectively investigate suspicious cases is to use a variety of approaches and techniques. Here are the key traits:

1. Timeliness is king

When you detect a risk, you must flag it to investigators in time for them to either (and ideally) stop a criminal activity or – in the case of DWP, for example – stop any future payments and malpractice around claims. The alert must include all the information that the investigator needs to understand the nature of the risk and how best to proceed. As a mother, I believe that if quick access to all relevant information can save an investigator the time it takes to protect one vulnerable child, then it’s worth it.

2. Modern-day factory

Typically, you run all the data through business rules, network analysis and analytical models. But when it comes to using models and machine learning (SAS, Python, R or others), the real trick is to ensure you have a productive analytical factory – one that operates in a timely and integrated way to support the build, develop, test, deploy, evaluate and challenge stages of creating insight – to build the case. The value of any model isn’t measured in its accuracy or confidence limits. The real value comes when it is deployed and working to detect crime and malpractice. Models degrade over time, some rapidly, so deployment must be fast enough to ensure the model is still optimal. To ensure the best success rate, you must use the most optimal model. You need to have a feedback loop in place for continuous evaluation and champion-challenger assessment.

3. Robust case management

Unfortunately, too often case management tools fail to support the investigating officer. The real need for all investigators is to have all the data and intelligence that supports the investigation in one place. But typically, they must log into multiple systems to gather evidence, repeating a search yet again, and then copy and paste from one system to another. Over the last few years, the number of fines issued for prescription fraud has grown massively to just under 1 million per year, having an efficient means to manage all these cases. However, given that prescription fraud costs NHS England an estimated £250 million per year, it’s a problem well worth tackling.

Photo by Markus Spiske on Unsplash

4. Easy access to different techniques

You might need complex visualisations, such as maps, timelines or a network diagram. This means having to go to an analyst or data scientist to produce it, possibly in a different tool and format, which breaks your chain of thought, adds time and just slows down the investigation.  Having easy access to visualisations (including geospatial) to spot trends and linkages can help pinpoint criminal networks responsible for immigration breaches and people trafficking, for example.

5. Workflow & alerts

In a cohesive process across job functions, departments and even organisations, it is invaluable to have workflow managing the handoffs. Along with integrated alerting, this allows investigators to easily identify if any alerted risk is valid and move the investigation through to conclusion. Or if the risk is invalid, to feed that back to the model factory as discussed in No. 2, above. Such a feedback loop is essential to ensure continuous improvement, reduce false positives and improve efficiency all round.

6. Data, data, data

Finally, all the above hinges on investigators having seamless access to all relevant data. Everything begins with data (and ends with intelligence and information). Being able to easily integrate internal data with that from external sources – such as other departments, law enforcement agencies, watch lists and more – is crucial for a slick investigative process. Obviously, this data ingestion needs to happen with a secure framework in line with government guidelines, for example, this from the Home Office.

In summary, variety and velocity are key. Variety in the data and techniques available and the velocity of investigations undertaken. Using different techniques – depending on the nature of the case being investigated – and doing this at pace to quickly put interventions in place minimises loss and drives value for governments and citizens alike.

So how can we deliver these capabilities with efficiency and accuracy in a secure environment? Regardless of whether it’s cloud-first or cloud-smart, SAS provides everything you need in one end-to-end solution that you can use either to enhance an organisation’s current capabilities or drive the entire investigative operation. You don't have to waste any more time flitting backwards and forwards between information sources. All data, models, alert management and workflow are in one system that also enables insight sharing and collaboration between team members with ease.

Want to understand more about intelligence lead investigations? Take a look at our e-book Faster, Smarter Investigation Management.


About Author

Caroline S Payne

Having spent all my professional life working with data and numbers - I now work for SAS where we help organisations (large and small) across all sectors to gain intelligence from their vast sources of data and then deploy this insight help make the world a better place. I lead a team of domain and technical experts who work with UKI Public Sector organisations on a daily basis, advise government agencies on the use of technologies such as AI to drive better service delivery and outcomes for all citizens.

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