Fraud in Lancashire: Exploring Victim Reported Incidents to Action Fraud

Abstract

Whilst fraud is a large and persistent crime, one of the main issues in responding to the crime
is lack of measurement and ownership (Button & Tunley, 2015). Fraud is frequently relabelled
as error, a civil dispute, or a consumer issue, meaning that records may be limited or
inaccurate. This subsequently leads to the blurring of definitions and categorisation, which
means that statistics are unable to grasp the full expanse of the issue (Correia, 2019). This
may result in less police preparedness and insufficient dedicated resources (Bossler et al.,
2020).

Therefore, the aim of the report was to analyse victim reported fraud in the Lancashire
Constabulary force area. This was to gain insight into the overall prevalence of fraud, in
addition to providing more specific victim profiles.

Data were provided to Lancashire Constabulary by Action Fraud. The sample of victim
reported frauds ranged from 1st January 2019 to 28th February 2021. There were 11,124 cases
of fraud between the sample dates; however, the data contained sections of missing data.
This meant that the reported total lost to fraud across the sample dates (£58,252,850)
represented an under-report due to missing data. Annually, this total financial loss to fraud
was made up of a £38,014,276 loss in 2019; £17,703,087 loss in 2020; and a £2,535,487 loss
at the beginning of 2021.

Due to their frequency six fraud categories that contained the largest counts were the focus
of this report. These categories were:
Fraud Category Frequency (n) Percentage (%)
NFIB3 - Consumer and Retail Fraud 4,798 45.3
NFIB90 - Other 2,493 23.5
NFIB1 - Advance Fee Payments 1,345 12.7
NFIB5 - Banking and Credit Industry Fraud 916 8.6
NFIB52 - Hacking 585 5.5
NFIB2 - Financial Investments 464 4.4
Total 10,601 100.00

They were examined specifically because the total number of cases within these six categories
totalled n = 10,601 cases (meaning the six categories represented 95.30% of all victim
reported fraud in Lancashire). The total financial loss represented by the six most frequent
fraud categories (focus of this report) was £55,152,283.

The analysis managed to identify different victim profiles across the fraud types:
1) When compared against the benchmark of NFIB3: Consumer and Credit Card Fraud,
Asian victims were more likely to be victims of NFIB2: Financial Investment Fraud in
comparison to White victims. When visually examining the finding there appeared to
be a large proportion of younger Asian victims losing over £200 to financial investment
fraud. Whilst not included within the statistical model as an interaction term, the
visualisation suggested that younger Asian victims appeared be at risk of financial
investment fraud, up until the approximate age of 50, where older White victims
became the dominant demographic.
2) Using NFIB3: Consumer and Credit Card Fraud as a comparator highlighted that there
were statistically significant differences in age across the fraud categories. In
comparison to NFIB3, NFIB1 (Advance Fee Payments), NFIB2 (Financial Investments),
and NFIB90 (other) presented an older victim demographic, NFIB52 (Hacking)
presented a slightly younger victim demographic, and NFIB5 (Banking and Credit
Industry Fraud) did not present a statistically significant difference.
3) When examining payment to fraudsters, NFIB2: Financial Investments were
associated with greater payments (med = £4,615, IQR = £19,500). NFIB1 (med = £148,
IQR = £1,000), NFIB3 (med = £200, IQR = £550) and NFIB5 (med = £330, IQR = £2,370)
all had similar trends, but on average had much lower payments than financial
investments. NFIB52: Hacking rarely involved payments of money (med = £0, IQR =
£0), suggesting that other losses may have been experienced by the victim, such as
the theft of data without a direct monetary value.

In summary, the results appear largely complimentary with existing literature and analyses
conducted within other force areas. Overall, the report aligns with the conclusion of Correia
(2019), who explained that victimology data is largely insufficient to inform an effective
vulnerability assessment. Building further on Correia’s (2019) recommendations, therefore,
critical future research is needed to improve knowledge into key areas of fraud, including:
o Improvements in data collection and processing to aid local and national
forces;
o Victim heterogeneity to be considered, both at local and national levels;
o Better knowledge of vulnerability, including repeat victimisation;
o The proportion and reasons behind no-loss reports, in order to provide a
victim-focused response that captures victim-impacts beyond financial loss.

Findings are interpreted in the context and with the sensitivity that policing is largely not
prepared in handling complex cases of fraud (Akdemir et al., 2020), that it is a crime where
no single agency or unit takes ‘ownership’ of cases (Aplin, 2021), and that prevention
campaigns currently contain ‘white noise’ (Prenzler, 2020) in relation to the need for
information sharing and increased awareness of what constitutes an offence.

Overall, whilst this report makes a similar conclusion to Correia (2019), it does highlight some
key findings and recommendation that would be useful when considering prevention efforts
for Lancashire Constabulary.