Data scientists are hot property. That’s not exclusive to the insurance world. But thanks to their ability to uncover all kinds of insight and combat fraud, they’re a particularly valuable asset to insurers.
In order for them to be as valuable as they can be, however, data scientists need to have the right tools and working relationships with the fraud team to turn that insight into something productive.
Data scientists are hot property. That’s not exclusive to the insurance world. But thanks to their ability to uncover all kinds of insight and combat fraud, they’re a particularly valuable asset to insurers.
In order for them to be as valuable as they can be, however, data scientists need to have the right tools and working relationships with the fraud team to turn that insight into something productive.
In this insurance insights report, we explain how insurers can maximise the effectiveness of counter-fraud teams by combining in-house data science expertise with commercial solutions that provide:
With all the hype about data science, it would be tempting to think of this brave new discipline as a cure for all ills, causing your fraud rates to plummet. Maybe you thought your team would be able to fight fraud efficiently and keep your organisation protected from criminal activity, while serving all the other parts of the business too.
But the agile, enigmatic nature of modern fraud means that’s not enough. It demands focus, time, resources and expertise, and that is not always achievable with a finite resource.
Perhaps you’ve already had discussions with your data scientists about this, though. Some might have been keen to hear more. But others might have pushed back, insisting they’re fine with what they have developed in house. However, an isolated approach sometimes misses industry learnings, third party experience and shared intelligence on fraud modus operandi (MOs) that are available outside.
In fact, adding an advanced fraud analytics platform can augment your data scientists and provide them with a complementary counter-fraud solution that will support them, not replace them. The following pages details reasons why.
By embracing a commercial analytics platform to tackle fraud, your team doesn’t just get an advanced new tool. They’ll also gain access to the combined experience and expertise of a third party that has developed that platform. And, in a nod to that old cliché – two heads are better than one – that gives your data scientists the power to be more effective.
No-one’s disputing your team’s forensic expertise around your data assets. They have the access, knowledge and understanding of nuance that an external vendor might struggle to match. But, by adopting a commercial fraud detection solution able to build machine learnt models, your team can leverage the breadth of counter-fraud expertise that a specialist partner offers.
Your data scientists are pulled in a number of directions. They’re asked to support various parts of the business – with duties including marketing, product optimisation, pricing and underwriting. Counter-fraud isn’t always their number one focus.
These competing priorities make it tough for data scientists to give fraud the attention it warrants. But, with a dedicated counter fraud solution capable of advanced analytics on-board, the burden of monotonous manual data sampling and wrangling is significantly reduced.
That means data scientists can use their time more efficiently and concentrate on the most valuable output – creating models that support Specialist Intelligence Units (SIUs).
With the power of a commercial analytics platform, your data science team will be able to join policy and claim data, bringing it into a centralised analytics environment and ultimately getting it in front of investigators faster. Advanced analysis tools support your team across the entire lifecycle of the customer journey, allowing investigators to triage specific cases and repudiate or block certain claims.
Finally, the global expertise and strategic focus of leading commercial fraud detection solution vendors give your data scientists broader insight into what is working across the globe. By understanding the behaviour of fraudsters across different territories, insurers can keep up with (and ultimately outpace) them.
Commercial analytics platforms help your data science team to function at its maximum. That not only means you can identify and eliminate fraud more effectively – you’ll also be able to shorten the time to value from your fraud fighting initiatives.
With the current shortage of data scientists, by embracing a commercial analytics platform you’re not only enabling your team to remain productive – you’re also gaining access to world-renowned experts. By working with BAE Systems, you’ll be joining an organisation with a critical mass – one that can attract the best scientists from across the globe, and apply leading-edge techniques and processes to fuel your counter-fraud mission.
BAE Systems insurance fraud solutions enable insurers to identify and prevent fraud fast – from policy inception through to claims – while minimising the impact on genuine customers. We can help you if you’re looking to:
With a proven combination of predictive analytics, social network analysis and machine learning, our advanced tools can uncover otherwise hard-to-detect suspicious behaviour. We’ll improve your detection accuracy too, by producing a single of view of your customers, which helps to reduce false positives and protect genuine claimants.
Our deep industry experience and domain knowledge enables sophisticated analytics to be presented to business users in a way that makes decisions easier. You’ll also be able to identify emerging fraud by helping Special Investigation Units (SIUs) to discover anomalies and patterns in fraud behaviours.
We can help you to minimise investigator workload, increase overall efficiency and reduce pay-outs on fraudulent claims. With integrated alerts and case management, convenient workflows enable improved collaboration and accelerated investigations.
Mark Rayner leads the Consulting Practice within the Financial Services division of BAE Systems Applied Intelligence. He helps banks, insurers and other financial services clients get the most value from the information they hold whilst also protecting themselves from internal and external threats.
Mark specialises in transformation and working with multi-disciplinary teams to mitigate cyber risk, deliver business change and leverage data to transform operations. His experience spans policy and governance, risk and control assessments, data classification and management, business intelligence and analytics.
BAE Systems insurance fraud solutions enable insurers to identify and prevent fraud fast – from policy inception through to claims – while minimising the impact on genuine customers. We can help you if you’re looking to:
With a proven combination of predictive analytics, social network analysis and machine learning, our advanced tools can uncover otherwise hard-to-detect suspicious behaviour. We’ll improve your detection accuracy too, by producing a single of view of your customers, which helps to reduce false positives and protect genuine claimants.
Our deep industry experience and domain knowledge enables sophisticated analytics to be presented to business users in a way that makes decisions easier. You’ll also be able to identify emerging fraud by helping Special Investigation Units (SIUs) to discover anomalies and patterns in fraud behaviours.
We can help you to minimise investigator workload, increase overall efficiency and reduce pay-outs on fraudulent claims. With integrated alerts and case management, convenient workflows enable improved collaboration and accelerated investigations.
Mark Rayner leads the Consulting Practice within the Financial Services division of BAE Systems Applied Intelligence. He helps banks, insurers and other financial services clients get the most value from the information they hold whilst also protecting themselves from internal and external threats.
Mark specialises in transformation and working with multi-disciplinary teams to mitigate cyber risk, deliver business change and leverage data to transform operations. His experience spans policy and governance, risk and control assessments, data classification and management, business intelligence and analytics.