The Role of AI in Detecting Insurance Fraud

Last week, the FCA launched its latest campaign to raise awareness of loan fee fraud. As households continue to grapple with the cost-of-living crisis, there is a rising risk of fraudsters targeting already vulnerable consumers looking to cover the cost of spending over the summer period.

Recent research from the FCA has found that over half of UK adults (55%) are more worried about personal finances this summer compared to last year. With the rising cost of living, many people are trying to save as much money as possible, and for some individuals, that also includes taking big risks with their insurance. As a result, cases of application fraud and ‘ghost broking’ have risen exponentially, with fraudsters capitalising on the desperation of consumers trying to keep costs down.

The surge in fraud cases also comes with an increase in sophistication and effectiveness, making cases harder to identify. Without investment in fraud prevention and operational cyber resilience, firms could potentially be putting their customers at risk of harm.

Use of AI to detect fraud

The task of identifying fraudulent activities can be a daunting one, but with the application of AI, firms can study previous records of deceptive claims to understand and recognise the patterns of fraud. The data can then be used when assessing new applications or claims, allowing firms to better identify potential fraud attempts and take necessary action where appropriate. Improving the analysis of data through AI also means that firms can be more proactive and prevent the risk of harm from spreading to customers.

The use of AI in other areas also has great potential to enhance product offerings and services, which could lead to better outcomes for consumers, firms, financial markets, and the wider economy. Implementation could also potentially improve operational efficiency, increase revenue, as well as drive innovation within the insurance sector, in relation to how risk data is calculated.

Application of AI technology does not come without its caveats, however, so it is important for firms not to rush headlong into adopting AI practices without first considering the pros and cons.

For instance, AI relies heavily on large quantities of data, which means there is also a greater risk of error in its processing and storage, resulting in data becoming incomplete or unrepresentative if left unmanaged. Poor management of data may potentially leave firms open to cyber threats if the software is unable to detect malicious content within its systems.

Staff should also remain vigilant in identifying fraud by utilising a wider range of data sources and advanced technology as well as their own knowledge and skillsets to report suspicious activity.

If you or another member of staff suspect fraudulent activity, then it must be reported to Action Fraud.


About the author

Jessica joined RWA in 2018, having graduated with a First Class Honours degree in Film Studies. Her role as a content designer involves developing new and engaging e-learning modules as well as assisting in the creation of articles for Insight. 

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