Our Mosaic classification system reveals a host of insights into which demographic groups within society are most targeted by fraudsters.
Unsurprisingly, the relatively cash-rich City Prosperity segment continues to be the most at-risk demographic when it comes to ID theft. Fraudsters favour targeting loans, savings and cards, all of which could offer thieves a quick financial win.
But very close behind are the less financially flush members of the Urban Cohesion, Rental Hubs and Municipal Challenge segments, highlighting how just indiscriminate third-party fraud is, with ID thieves willing to attempt fraud against any demographic group – irrespective of earning potential.
This trio of mid-tier at-risk segments represents more than one in seven of the UK’s population (15.4%). Clearly anyone living in densely populated, multi-occupancy homes, with shared or remote mailboxes and communal amenities continue to provide opportunities for determined identity thieves.
Current accounts, loans, cards, plus bogus insurance claims are particularly vulnerable within these segments, accounting for a disproportionately high volume of nearly half (45%) of all third-party fraud attempts currently being made.
Despite having low levels of consumer fraud, the Prestige Positions group – made up of affluent couples from prestigious residential areas – also continues to present a tantalising target for ID thieves, largely due to their relative high net-worth. Insurance policy fraud is particularly favoured by third-party fraudsters targeting this demographic, reflecting the potential level of ghost-broking or fronting opportunities low-risk postcodes can offer thieves.
Loans and savings are also vulnerable products within this segment. But the high-levels of detection are down to many institutions adopting multi-layered fraud strategies in tackling these types of fraud.
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Experian works closely with National Hunter and Insurance Hunter, the UK’s leading fraud prevention systems, operated by Experian on behalf of members. The systems enable financial institutions to cross-match applications against more than 100 million previous application records in order to spot commonalities and anomalies that are potentially indicative of fraud for further investigation.