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Call the Consortium: Puzzling out insurance fraud with collective data

If cracking an insurance fraud case is like assembling a jigsaw puzzle, then data points are the puzzle pieces. Insurer special investigative units (SIUs) work hard to put together the data at hand — the puzzle pieces — to see the complete picture. But just as missing crucial pieces of a puzzle can leave the picture incomplete, a lack of data can prevent investigators from understanding the full extent of criminal activity. 

As these counter-fraud professionals conduct desk research to explore connections between parties or the validity of a claim’s details, they’re generally limited to their own company’s claim data. Even when armed with increasingly robust technologies, one insurer’s data can only go so far. Working alone, one company’s fraud-fighting team may lack the history linked to a particular entity or may not be able to tell whether the claim that they are looking at is part of a greater criminal network. 

Enter the insurance fraud consortium, bringing many more puzzle pieces to the investigative table in the form of collective data. 

Seeing the full picture with the consortium 

Simply defined, an insurance consortium is typically a not-for-profit organization funded by its insurance company members. Member services may differ by the consortium’s nation of origin, but all have access to an industry-wide dataset of national or regional claim and policy information.  

Unlike its insurance company members acting in silos, the consortium has all the pieces of the puzzle. With its diverse and wide-spanning dataset, the consortium can highlight connections and find overarching patterns invisible to an individual insurer’s SIU.  

Consortiums can, for instance, pull together a complete claim history linked to a particular individual or address. Some consortiums also work to find new data, hosting tip lines to garner insurance fraud information from anonymous sources. 

Consortiums’ access to data allows them to lead the charge against fraud and financial crime, acting as valuable sources of information to many other organizations, including law enforcement. Some insurance fraud consortiums also help investigate crimes well beyond the typical definition of insurance fraud, including carjacking, kidnapping and murder. 

Deft data management saves the day 

With the vast amount of data consortiums find at their fingertips, they often face significant data management challenges. Structured and unstructured data from an array of member systems needs to be cleansed and standardized to ensure similarity in shape, quality and detail. Duplicates must be eliminated and consolidated to ensure information relating to the same entity is linked. This can be a complex and painstaking process, but these cleansing techniques are necessary to ensure the data can be analysed to its full potential and effectively mined for insights. 

Data management is so crucial, because it allows these collectives to create powerful network visualisations to render connections between various entities: individuals, addresses and more. Network analysis facilitates a much more comprehensive understanding of fraudsters and their tactics, revealing hidden connections within the data that might otherwise go undetected by a given insurer. Additional detection capabilities can be automated by an advanced analytics software platform, configured to flag suspicious behaviour and generate alerts.  

After the data has been mined for insights, intelligence uncovered by the consortium can be disseminated to its members. Now in the know, insurance companies’ SIUs can discover repeat offenders early – before a fraudulent claim is paid – and engage law enforcement when appropriate. The key is that consortium members can physically process and respond to the intelligence from the consortium. Without this, the consortium can only go so far in its efforts to stamp out insurance fraud. 

Accelerating with generative AI 

Whilst fraud detection platforms used by consortiums can leverage a range of analytical techniques — including the application of AI models — to find more fraud and keep false positives at bay, the landscape is changing at an unprecedented rate. Developments in technology, including the emergence of generative AI (GenAI), have given fraudsters a new arsenal of tools which they can exploit to carry out increasingly sophisticated attacks. It’s therefore essential that consortiums keep pace with this evolution and consider new and innovative technologies which can help counter AI-enabled risks.  

GenAI, although still in its infancy compared to other forms of AI and machine learning, could certainly have a part to play here. Software providers are already exploring the use of GenAI across different use cases, and therefore consortiums may soon be able to reduce the burden of manual tasks and expedite their investigations. Likely business uses include GenAI co-pilots being leveraged to help summarise case findings, identify key entities and initiate tasking to help reduce perceived intelligence gaps.  

The future of insurance fraud consortiums 

As criminals grow more sophisticated, a consortium approach to fraud detection and prevention can help insurers keep up – or even get a critical step or two ahead. 

Access to a rich, industry-wide dataset and advanced analytical platforms can empower insurance fraud consortiums to untangle increasingly complex and organized scams at a greater scale and scope – “solving the puzzle” of insurance fraud and related crimes over and over again. By pooling data and investing in powerful data management, AI and analytics, consortiums can leave fraudsters with no place to hide, protecting consumers and insurers from their reach today – and in years to come.

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This content is provided by an external author without editing by Finextra. It expresses the views and opinions of the author.

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