• Earlier this month SAS Principal Business Solutions Manager, Risk, Fraud & Compliance, Nick Feast spoke at a conference on the topic of AI’s role in insurance.
• The manager highlighted that AI and data scientists are linked and AI shouldn’t be seen as a replacement.
• Feast also highlighted how collaboration is vital in combatting fraud committed with AI tools.

Earlier this month SAS and the Insurance Crime Bureau held a conference where Nick Feast, Principal Business Solutions manager, Risk, Fraud & Compliance at SAS spoke on the concerns many in the insurance sector have.

As we outlined earlier this week, artificial intelligence is a growing concern for insurers as cybercriminals and dishonest individuals leverage the technology to defraud insurers. Momentum Insure warns that insurers must work together and invest in AI to combat fraud and Feast appears to agree, while also highlighting that humans are still a core part of fighting fraud.

“Skilled and talented people are still the most valuable resource when it comes to combating fraud. They have logic and reasoning which AI cannot provide,” states the manager.

While insurance firms may be tempted to replace costly data scientists with an algorithm that sniffs out fraud, that is a bad idea. Not only is AI costly to train and run at scale (more on this in a moment), as we’ve mentioned in the past, AI implementation requires a lot of work and presents a significant security risk to any business. In the insurance industry where sensitive data is part of everyday business, this means AI deployment needs to be approached with an abundance of caution.

According to Feast, SAS is hoping to solve the scale problem through generative AI initiatives.

“SAS is currently focusing on a number of initiatives around GenAI, including synthetic data generation, which can provide organisations with an increased volume of data to use in model building, whilst protecting the integrity and security of the organisation’s own data. We are also focusing on co-pilots to make daily tasks easier, including in specific aspects of the analytics lifecycle, as well in more business-level tasks, including investigation,” the manager says.

AI has been a part of the insurance industry for a long while and as such, insurers are well placed to drive development of the technology forward. However, the success of AI in this sector and especially for insurers alone is how good the data is that the AI is being fed. Data scientists are essential in making that determination as well as insuring that the outputs from the AI are valid.

“I have seen some insurers here that have good in-house data science teams in place to assess claims and spot fraud throughout the insurance lifecycle. They are doing good work and are drawing on AI capabilities to spot fraud as early as possible. While SAS has extensive analytics capabilities and an environment in place that can automate much of this, there has to be a combination of both technology and human resources,” says Feast.

The manager also noted that collaboration is a key ingredient in fighting the malicious use of AI.

“Working alone, one insurer’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. This is where industry players working together and consortiums are so important,” he told the conference.

“An insurance 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 special investigations unit. Consortiums can 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,” he concluded.

[Image – Elchinator from Pixabay]