From bogus claims to reputational damage, the ability of synthetic media to seemingly bend reality is an emerging menace with a far reach.
Mahi Sall, Advisor, Fintech-Bank Partnerships, Payments and Financial Inclusivity
January 25th, 2023
Mahi Sall is the CEO & Founder of FinXpair, a Berlin-based strategic advisory boutique firm focu[...]
Synthetic Media and Deepfakes: An insurance industry threat
Insurtech Insights | Sep 24, 2021
From bogus claims to reputational damage, the ability of synthetic media to seemingly bend reality is an emerging menace with a far reach.
If you are familiar with photo and video editing tools, then you have probably heard of deepfakes, an emerging breed of artificial intelligence-enhanced videos that have demonstrated the ability to blur reality in ways that are extremely difficult for humans or even machines to detect.
Unlike conventional video editing, deepfakes utilize artificial intelligence(AI) to alter or synthetically generate videos, bringing a new level of realism without the forensic traces present in edited digital media.
See: World Economic Forum (WEF) Warns of Cyberattack that will Collapse Existing Financial System
While these advanced fakes may sound like science fiction, many researchers have concluded it is only a matter of time before deepfakes become nearly undetectable to the human eye and subsequently undetectable even to elaborate forensic tools.
Earlier this year, the FBI sounded the alarm that deepfakes are a new cyberattack threat targeting businesses. As a result, many organizations are pondering strategies to mitigate the risks and potentially undesirable outcomes that may result.
Deepfakes or synthetic media can effectively be used to file fraudulent claims, create fraudulent inspection reports, and even establish the existence and condition of assets that do not exist.
Think claims for exaggerated damage from a nearby hurricane or tornado or claims for items that don’t even exist, i.e., a non-existent Rolex watch that got insured and mysteriously went missing.
Does this suggest going back to using human adjusters and inspectors for important claims? While taking a step backward to manual inspection might help to eliminate the deepfake threat, a layer of protection against the deepfakes in self-service processes would serve better without undoing years of digital transformation.
Read: How open-source software shapes AI policy
Moreover, with many claims processes moving to straight-through processing, with no human intervention required aside from exceptional cases, two in-line approaches are suggested for implementing a layer of defense:
- In-line detection: Using AI and rules-based models to detect deepfakes in all digital media submitted. Similar to the Deepfake Detection Challenge mentioned earlier, apply AI-based forensic analysis to every photo or video prior to processing a claim.
- In-line prevention: Digital authentication of photos/videos at the time of capture to “tamper-proof” the media at the point of capture. This could simply be as part of a secure app that prevents the insured from uploading their own photos, or even better, utilizing a blockchain or immutable ledger that protects against both inside and outside changes to the media by utilizing a global consensus model.
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