Credit and the career fraudster: the data behind repeat offenders

Over the past five years, analysis by Synectics Solutions of fraud data across UK banks and finance providers has revealed that credit card fraud – primarily application fraud - carries the highest rate of repeat offending among all financial products.

What’s more, journey analysis shows that fraudsters increasingly follow a deliberate “career path” across financial products - often moving from current accounts to credit cards, and later into savings or investment products to store illicit gains.

These insights from National SIRA - the UK’s largest shared intelligence consortium covering confirmed fraud, suspicious activity, and genuine customers - underline the urgent need for cross-product and cross-organisation data sharing to detect and disrupt offenders before they transition between institutions.

Key findings

Credit Cards Lead the Repeat-Offending League Table

• 23% of people who commit fraud relating to credit cards go on to offend again.
• This figure has risen from 17% to 23% over the past five years - a 35% increase.
• Over the past 5 years, credit card related fraud has the highest repeat offending rate of any financial product.

The Fraudster’s ‘Career Path’

Analysis of offender journey data shows a distinct career progression pattern among repeat offenders:

• Stage 1: Most begin with current accounts, using them as testing grounds for false applications or synthetic identities.
• Stage 2: Typically, they then apply for credit cards, where higher limits and transactional flexibility offer greater rewards.
• Stage 3: Many then transition into savings accounts or other investment products, often to launder or store fraudulent proceeds.

Notably, credit cards are also the second most common starting point - highlighting their dual role as both entry-level and mid-stage fraud products.

Chris Lewis - Director, Strategic Solutions & Analytics at Synectics - comments: “This data is clearly a concern. The challenge banks and other credit service providers face is also compounded by the fact that repeat offenders aren’t exactly fans of brand loyalty. They are now hitting 50% more financial institutions than they were 5 years ago. We saw a 10% increase since last year alone. It’s an important detail which shows just how essential shared intelligence is to stopping career fraudsters.”

False Identity: The Signature Offence

• The most common offence among repeat fraudsters is False ID, with synthetic IDs being a key issue for all financial service providers.
• Synectics notes an increase in one subcategory of synthetic ID creation where fraudsters hijack real IDs by making very minor changes to slip through cracks. ID details listed on publicly available sources, for instance Companies House, are particularly at risk of ‘fractional deviation fraud’
• 50% of all false identity filings are linked to individuals who have filed at least one other false identity.

Chris Lewis - Director, Strategic Solutions & Analytics at Synectics - comments: “When 50% of all false identity filings are tied to an individual with a history of creating multiple fake IDs, this is no longer just a case of ‘one-off’ application fraud - it's a sign of organised, repeatable schemes designed to evade detection. Combine this with the fact that synthetic identities are quickly becoming the dominant vehicle for fraud, and it's clear that traditional, siloed checks are not enough.

 “Fraud strategy needs to evolve. Onboarding checks will always be crucial, with conditional friction particularly advisable where IDs are at high risk of hijacking, but our data shows there is a clear need to supplement this with dynamic identity verification throughout the customer lifecycle. Without this, for example, spotting the point at which a ‘good ID turns bad’ becomes extremely difficult.”

 “Most importantly, we must tap into cross-institution intelligence and data sharing. Only by pooling information can we uncover the hidden links and patterns of synthetic ID fraud that no single institution can detect alone.”