Spike in neighbourhood ID thefts blunted by smart fraud analysis

Postcode analysis of just one stretch of road hit by a sudden spike in ID thefts and related frauds, highlighted more than 20 detected incidents at a handful of homes in a neighbourhood, near Potters Bar, Hertfordshire.

But closer inspection of each of the victims’ addresses revealed remote mailboxes, installed away from their homes, often at the top of their drive, was a common feature throughout.

The mailboxes’ location was clearly offering relatively easy access for fraudsters to get their hands on residents’ personal mail.

It typifies how ID theft continues to be a nationwide challenge affecting customers from all parts of Britain.

The inner-cities of Birmingham, Leeds, Manchester and Glasgow, continue to be particularly vulnerable. Isolated pockets of fraud hot spots in the Highlands, Wales, Devon, Cornwall and Hampshire, all reflect the way ID thieves and ghost-brokers are using low-risk postcodes to illegally sell insurance are now being detected.

Third-party fraud continues to be biased towards wealthier suburban areas – as clearly shown on the Greater London map – with virtually every commuter town around the M25 having disproportionately high levels of third-party fraud.

Recent analysis of 10 addresses in and around the same area of leafy Warwickshire, also pointed to a suspected ghost-broking fraud. More than 60 suspicious insurance policy applications were detected as being made from just a handful of addresses – many from the same address but made by multiple applicants. But thanks to a combination of vigilance, analytics and technology, the fraudsters’ efforts were promptly shut down.

To find out more about emerging trends, spotting fraud networks, or the technology that can help you stay one step ahead of the fraudsters, simply click here.

We work closely with National Hunter and Insurance Hunter, the UK’s leading fraud prevention systems, operated by us 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.