The Complete Guide to AI in Insurance Fraud Detection.

Author:Patel, Kumar

The insurance industry is rapidly evolving. Emerging technologies are breathing new life into daily operations; and artificial intelligence (AI) has the singular potential to pervade every facet of insurance processes with advanced analytics, powerful predictions, and more robust risk management strategies. It's no wonder that, according to a 2018 Accenture survey, four out of five insurance executives already believe that AI will work alongside their human employees within the next two years as a co-worker, collaborator, or trusted advisor.

The high amount of fraud in insurance, however, isn't changing. From stolen identity to false claims to exaggeration of damage, insurers lose astronomically large amounts of money due to fraud every year. In fact, the FBI reports that the total cost of insurance fraud is estimated to be over $40 billion per year, excluding medical insurance. This translates to a significant sum, added to the premium costs of every policy issued and negatively affecting both macroeconomic prospects and each individual customer. Scam expenses can cost an average US family up to $700 per year on increased premium fees.

AI has the potential to become a true watchdog of insurance, uncovering fraud and preventing it in the first place. The disruptive technology has the power to monitor an unlimited number of claims at the same time to find suspicious activities, unveil hidden relationships, and quickly identify behavioural patterns. With over half of life insurers witnessing a 30% rise in fraud, is AI the solution? If so, then how do we utilize its full potential?


Leveraging AI to detect suspicious activity is quickly becoming standard. 75% of the industry reported using an automated fraud detection technology in 2016, which is understandable as AI can be applied in several ways. Thoroughly analysing data from diverse sources can result in fraudulent causes being swiftly spotted - and with greater precision. AI also helps to uncover hidden correlations and discover new fraud schemes by mining information from both current and past claims.

Crunching mass amounts of past data and new data in real-time from various sources while identifying key connections is beyond human capability. AI systems can analyze social media accounts, communications, bank transfers, and websites such as eBay to look for listings that match stolen items. So if you were tagged in a Facebook photo of you dancing on a stolen table right...

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