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Using fuzzy logic to identify insurance fraud in claims. Fuzzy logic is an artificial intelligence method that solves problems using qualitative (fuzzy) data to produce quantitative (measurable) results. (Photo: Africa Studio/Shutterstock.com)

Tackling fraud has never been more critical or difficult. What’s more, the COVID-19 pandemic has undoubtedly shifted the fraud landscape. Fraudsters are becoming increasingly sophisticated with the arrival of new technologies.

According to insurance experts, fraud increases during times of economic hardship. For example, in a survey conducted after the economic crisis of 2008, fraud bureaus reported the number of referrals and cases opened, on average, increased in all 15 categories of fraud included in the survey. The pandemic caused similar disruptions to our economy and ushered in a wave of behavioral and procedural changes in nearly every aspect of business and government operations and daily life. The changes have presented scammers with new avenues for exploitation, as evidenced by the historic DOJ takedown of 351 suspects allegedly responsible for $6B in fraud — with $4.5 billion attributed to telemedicine schemes. It is easy to see how these uncertain times could be a catalyst for increased levels of fraud.

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