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Fraud Spotlight: ID fraud now hardest to spot, say insurance leaders
Identity fraud was named as the fraud typology most difficult to detect, according to the 2024 Insurance Post Fraud Survey: 72% of respondents to the survey, sponsored by LexisNexis Risk Solutions, ranked it in their top three, compared with 23% in 2023, when it placed third.
This was ahead of professional/organised claims fraud (53%) and opportunistic fraud (44%), both of which were up from 38% last year.
QBE Europe’s special investigations unit claims manager, Charlotte Gray, said that the ability to falsify documentation is only a click away.
The risk to fraudsters from using AI to create synthetic identities is minimal; if the identity fails, it has no link to them, so they just try again until they get it right.
Fiona Reeve, head of fraud at Ageas UK
She said: “Post-Covid and then with the cost-of-living crisis, an uplift in digital fraud has been observed. The organised fraudsters had the physical opportunity reduced or removed to stage falls in football grounds and slam on brakes in vehicles and this has accelerated the movement into number spoofing, shallowfakes, push payment fraud, and cyber crime.
“It is difficult to detect certain aspects of digital fraud types as they are not always obvious and manual detection cannot be relied upon.
Fiona Reeve, head of fraud at Ageas UK, said that, since the introduction of ChatGPT, there has been a surge in phishing emails, coupled with the increasing threat of cyber-attacks, so consumers need to be far more vigilant in protecting their identity than ever before.
She said: “The risk to fraudsters from using AI to create synthetic identities is minimal; if the identity fails, it has no link to them, so they just try again until they get it right. They are willing to use emergent technology unethically and are learning how to use it faster than those using it ethically, so we need to follow fast in our understanding of the technology to continue combatting these fraud types.”
Synthetic ID fraud
Synthetic ID fraud, which involves stealing a real person’s information and combining it with fabricated details to create a new fake identify, is on the rise with two-thirds (66.7%) of respondents describing the threat as very or extremely significant.
They said this was because it is “extremely difficult” to detect, leading to financial losses for the insurer, and repercussions for the victims of the synthetic ID fraud.
More than 70% of respondents rated it as very or extremely difficult to detect, which was broadly in line with last year’s results.
In addition, the challenge lies in distinguishing between legitimate and synthetic identities, with many “deepfakes” being described as “so convincing”, as well as keeping up with the technologies being used and training staff to spot it.
Another issue raised by survey respondents was that vulnerable customers are often slow to spot anything being wrong. By the time they discover something amiss, a lot of damage has already been done.
Furthermore, with AI fraud becoming more intricate and easier to pull off, coupled with the detail that people share on social media, it has become far simpler to create a synthetic ID from existing data that is freely available online.
Charlotte Gray said that it was very difficult to corroborate, validate, and challenge someone who isn’t a real person.
She added: “The insurance industry has worked tirelessly to ensure that fraudsters are punished for their actions. It is impossible to effectively litigate against someone who does not exist.”
Playing catch-up
Another critical factor was that much of the technology used by fraudsters was “way ahead” of that used by investigators. This included the sophistication of software used, for both photo recognition and voice recognition.
Survey respondents also reported that some of the standard detection or validation methods are no longer as effective as they once were.
This is particularly the case in instances where people have been patient to develop profiles over time, ahead of presenting information for policy or claims data.
Charlotte Gray noted that synthetic identity fraud is a problem that is growing in sophistication and frequency.
She said: “The fraudster will fabricate credentials and create an identity that does not match with a living human. Fraudsters may create synthetic identities using potentially valid social security numbers with accompanying false personally identifiable information.”
Gray pointed to examples where innocent individuals’ addresses have been used, saying that it is not unusual for the fraudster to target the most vulnerable.
“Synthetic ID fraud is more appealing to organised fraud groups and its emergence has been the catalyst for change in the fraud detection areas,” she added.
Fiona Reeve also highlighted the heavy toll on innocent victims: “The impact for the genuine identity holder is significant, for example they can have debt or fraud markers against their name, and they may only become aware when they are declined credit, challenged by their insurer on their claims history, or sent a fine from the police for speeding, and so on.”
ID fraud victims are in a reactive position of trying to prove their genuine identity and not the fraudulent version of themselves, Reeve explained.
“Once an identity has been stolen it can be used multiple times by the fraudsters, with some victims having hundreds of uses of their identity for insurance fraud, obtaining credit or goods, even taking over their accounts, in very short periods of time before they are even aware, and this can then go on for years. This is obviously extremely upsetting.”
Furthermore, the blend of legitimate and fake data often passes through initial screening processes, complicating detection efforts.
Not enough communication between other companies with the same issues was also named by survey respondents as a factor.
In addition, despite synthetic ID fraud being a growing threat, there are “less established playbooks” to tackle it, the survey found, as well as a lack of resource to research the synthetic ID.
Problems getting board-level support for integrating additional data validation through using AI was also reported as an issue.
Kat Cunningham, senior development manager at Aviva, said that the insurer was “working with a number of external partners to further enhance our capability in this space to protect our genuine customers and detect fraudsters”.
Fiona Reeve added that Ageas had developed an accurate and effective ID theft model, enabling it to differentiate genuine customers from those using a stolen identity.
She said: “We are constantly looking at the development of this successful model as working with our technology partners to understand what they can do to support us in this area. As with any area of fraud, this is a process of evolution, and we can’t afford to stand still.”
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