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A CASE STUDY BY
THE FRAUD INTELLIGENCE NETWORK, AND
THE NATIONAL FRAUD INTELLIGENCE BUREAU
AVOIDING PAYMENT FRAUD WITHIN THE UK TRAVEL INDUSTRY
RISK FACTORS A case study to help eliminate credit card charge-backs
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Fraud Intelligence Network – Travel Fraud Case Study
CONTENTS
About This Case Study 3
Foreword 4
NFIB & PROFiT 5
Key Findings 6
Payment Fraud 7
Travel Fraud Case Study 8
The Case Study Results 9
How to Use the Case Study Results 18
Third Party Facts 19
About the FIN Intelligence Tool 20
About the NFIB 21
Contact us 22
© Copyright 2013
No part of this publication may be reproduced, transmitted, transcribed, stored in a retrieval system, nor translated into any human or computer language, in any form or by any means, electronic, mechanical, optical, chemical, manual or otherwise without the prior written consent of FI Network, 23 Wansbeck Court, Waverley Road, Middlesex. EN2 7BS.
Copyright © FI Network www.finetwork.co.uk
3
ABOUT THIS CASE STUDY This case study is based on over 50,000 booking records from 52 leading travel companies within the UK. The participants included accommodation providers, airlines, financial institutions, hotels, holiday lettings, online travel agencies, retail travel agencies, and tour operators. The study was carried out during November and December 2012 by F I Networks Ltd using the FIN counter fraud Intelligence Tool to analyse the data.
The data has been analysed in th is report , wi th detai led commentary. The key f indings are that t ravel f raud has moved onl ine and is most ef fect ively perpetrated remotely. Fraudsters are general ly wel l organised working col laborat ively and rarely at tacking a s ingle t ravel company at any one t ime so that businesses which share f raud data are in a bet ter posi t ion to resist at tack than those working alone. Common indicators exist in f raud bookings that ident ify h igh r isk factors these can be used to bui ld a ‘matr ix’ of threats which can be used to re ject attempted f raudulent bookings. Our expert ise a l lows us to provide t ravel companies with a pract ical and commercia l approach to protect ing revenue in the context of today’s chal lenging marketplace. This report expla ins the issues in a stra ightforward way to help you to f ind pragmat ic solut ions so that you can form an ef fect ive counter f raud strategy.
Financial Fraud Action UK
Payments made by credit and debit cards accounted for the vast majority of fraud transactions. During 2012 across the whole t ravel industry Financia l Fraud Act ion UK reported that domest ic f raud was more prevalent than cross border t ransact ions.
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Fraud Intelligence Network – Travel Fraud Case Study
FOREWORD
Very few frauds are chance actions; the vast majority are organised and carried out deliberately and systematically by people who make a career from cheating others. Many fraud case studies and reports have been published over the years; this is the first case study that looks within the travel industry in conjunction with the Police. This report looks at payment fraud within the travel industry. The cost to business because of fraud is growing both in terms of actual losses and the systems companies deploy to prevent fraud. Every company should identify the elements of high risk transactions so that they can recognise them and apply additional checks to avoid being caught. This snapshot of the UK travel industry has been made using the FIN Intelligence Tool and it shows how fraudsters will deploy the same elements against a number of different businesses. This allows companies to work together to pick up these repeated factors and defend against the attack. Sharing fraud data is essential if companies are to minimise successful fraud attacks, and it is clear that the parameters identified in this report will be a valuable resource to travel companies in their fight against payment fraud.
David Rose Operations Director and Owner FI Network Ltd
Find out more about the FIN Intelligence Tool and how you can take part in a case study on p20
Copyright © FI Network www.finetwork.co.uk
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Barry Gooch Chairman PROFiT Ltd www.profit.uk.com
Detective Superintendent David Clark Director of the NFIB
NFIB & PROFiT
National Fraud Intelligence Bureau
I am delighted that the travel industry and NFIB relationship is growing from strength to strength. Working alongside PROFiT and making best use of harvesting and sharing of intelligence between the FIN intelligence tool and the NFIB ‘Know Fraud’ database, marks significant progress in public private intelligence sharing for the greater good of protecting UK citizens and businesses from fraud. These ground breaking efforts make a giant step towards
making the UK a more hostile place to commit fraud, and a
safer place to live and conduct business, which has to be our
ultimate aim.
Prevention of Fraud in Travel
The travel industry is one of the largest sectors within the UK by turnover. Long ago fraudsters recognised the vulnerability of this vast industry to fraud. The move from shop transactions to remote ones has made companies more vulnerable and increased the value of successful fraud attempts.
Travel companies have invested in counter fraud software of the 3rd party verification type, and adopted 3D secure in order to tackle fraud. However many find that the only way of effectively reducing fraud is to set the rules for high risk transactions very high so that the company rejects a large number of good bookings causing loss of revenue. In many cases payment fraud experienced by the industry derives from Organised Crime Groups that are continually testing and probing company’s defences in order to find a way through. Once successful these groups share the knowledge with other groups.
Systematic sharing of fraud data is essential if the industry is to effectively tackle fraud as this case study demonstrates.
www.cityoflondon.police.uk/CityPolice/Departments/ECD/NFIB/
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Fraud Intelligence Network – Travel Fraud Case Study
KEY FINDINGS
76% of telephone
numbers linked to two or more
records
53% of payment
cards linked to two or more fraudulent
transactions
85% of Post Codes
used for fraud were in
London
99% of fraud
bookings were online
33% of IP addresses linked to two or more records
10% of fraudulent
email addresses
linked to two or more records
183 email
addresses were in three or more
fraudulent transactions
75% of domains
used for fraud were .com or
.co.uk
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PAYMENT FRAUD Payment fraud occurs when a company processes a payment from an
individual in return for a product or service but the ‘customer’ has no intention
of honouring the payment. The company provides the product or service but
the payment is rejected.
IDENTITY THEFT
Commonly payment fraud in travel occurs when a persons’ identity is taken over.
The true owner may have paid for something elsewhere and unknowingly had their
identity cloned. Alternatively they may have had their payment card stolen or
misused by someone who knows their identity. The fraudster who has taken on the
person’s identity uses it to make payments for travel using the true person’s identity.
3rd party verification tools help prevent this type of fraud, but are not fool proof.
DISHONEST INTENT
Another form of fraud that occurs within travel is where a group of individuals make
travel arrangements paying through one person’s credit card. When the group
returns from the holiday the payment is cancelled and received as a ‘charge back’ by
the travel company. The group will do exactly the same thing against other travel
companies with a different person within the group making the payment and ‘charge
back’ each time.
In this case the person making the payment is the legitimate owner of the identity
and payment method, but they never intend to pay for the product. No 3rd party
verification tool will pick this type of fraud up as they concentrate on the person
making the payment who in this case has no genuine intent to pay.
INTERNAL FRAUD
Where companies do not set up systems adequately, homeworkers and employees
are able to note down the payment card details of a consumer when taking or
processing payment and subsequently use the harvested details to commit fraud, or,
to sell them onto Organised Crime Groups for fraud use.
Perhaps the most difficult payment frauds to detect are those that occur within the
company and against the employer. This fraud arises because processes allow
payments and refunds to be made by the same employee. It is relatively common in
these circumstances to find that the employee will ‘refund’ passengers to their own
or a friend’s bank account. Similarly an employee may take a booking which is not
recorded on company systems requiring cash payment at ‘the door’.
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Fraud Intelligence Network – Travel Fraud Case Study
TRAVEL FRAUD CASE STUDY Participants provided records of payment fraud that arose during the previous 18
months. The data was loaded into the FIN Intelligence Tool which carried out the
detailed analysis that is the subject of this report. The data was ingested via the
FIN Intelligence Tool into the NFIB. All of the data was collected and processed
in accordance with the Data Protection Act and its principles.
Fraud data is not commercial data. The
results from this case study confirm that the
best way to tackle payment fraud in travel is
to work collaboratively with other
organisations and share data amongst each
other and the police.
The travel industry can do much to help itself
by working with the police through bodies
such as PROFiT, enforcement action
becomes a possibility.
The case study proves that fraudsters make
use of the same payment cards; IP
addresses; email addresses; and telephone
numbers to make multiple transactions
against different companies. Once this is
understood, the sharing of fraud data
amongst companies in order to thwart the
fraudsters makes sense.
The FIN Intelligence Tool used for this case
study has been designed and built to
process and analyse data for any industry
and to facilitate data sharing from sector to
sector.
FIN distinguishes between suspicious
activities and confirmed frauds and is set up
to automatically report confirmed frauds into
the NFIB taking data sharing beyond the
industry using it.
In addition to providing the findings for this
report; all of the fraud data gathered for this
case study has been ingested into the NFIB
and is being processed to identify Organised
Crime Groups that meet the criteria for
enforcement action.
Fraudsters share data, are organised and
persistent, their organisation and big money
mean that individual companies will find it
almost impossible to resist them indefinitely.
Typically Organised Crime Groups will
continually test a company’s systems,
unknown to the company, until they find a
way through. Once they find a way in they
will either go on to commit further fraud, or
more typically share the gateway path with
others.
This is why a travel company can trade
without fraud for a period of time, but when a
fraud does occur it is often accompanied by
several others.
The average booking value of a fraud
transaction identified in this study is £407.
But when accompanied by several others the
value will be several thousands.
Copyright © FI Network www.finetwork.co.uk
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TOP TIP:
Call centre bookings are usually reviewed by a sales
consultant during the booking process, so why not
apply the same checks to online bookings?
Review online and manually processed bookings
THE RESULTS
Set out on the following pages are the results of the case study classified by the following subjects:
Order Type; Payments; BIN Number; Destination & Departure Points; Emails and Domains;
Location; and Other Data.
Each section begins with a brief commentary setting out the salient facts whilst the majority of sections
list the top 10 entries within that category. Generally there will be a large number of records in each
category, but the report concentrates on the top 10 most prevalent records in their class.
The top 10 are ordered with the most prominent record at the top colour coded and identified by a letter
of the alphabet that together identify their corresponding representation on the accompanying ring
graph. The ring graph gives the reader an idea of the relative prevalence of each class within the top
10 to each other.
Every section also has a ‘TOP TIPS’ Card which has practical advice on measures to reduce the risk
from the respective element it is referring to.
ORDER TYPE Although there are signs that the traditional package holiday is
recovering in the marketplace, it is no surprise that flight only and
hotel only bookings make up 92% of overseas fraudulent bookings
in the case study. The FIN Intelligence Tool identified that 99% of
fraud bookings took place online.
• Hotel (Overseas) only booking: 64%
• Flight only booking: 29%
• Hotel (UK) only booking: 7%
• Car Hire booking: 0.2%
• Package Holiday booking: 0.05%
99% of fraud
bookings were online
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Fraud Intelligence Network – Travel Fraud Case Study
Flights
HotelsOverseas
Car Hire
Hotels (UK)
A
B
CD
E
F
G
HI J
TOP TIP:
When reviewing potential bookings as well as considering
the potential profit; remember that any chargeback will be
for the total value of the booking and not just the profit.
£100 profit on a £1000 booking sounds good, but a £1000
chargeback equals a bad decision
PAYMENTS The total value of fraudulent bookings identified by the FIN
Intelligence Tool in this study was £19,665,152.
The case study identified that:
• Average flight booking: £472.32
• Average hotel booking (overseas): £461.76
• Average car hire booking: £302.98
• Average hotel booking (UK): £124.52
The average fraudulent booking was £407.11
Over 1400 different BIN codes were associated with fraudulent
transactions by the FIN Intelligence Tool within the case study.
The top ten BIN codes were all from within the UK.
The top 10 BIN’ were:
A. 529930
B. 465943)
C. 492181
D. 454313
E. 465942
F. 542011
G. 446278
H. 543460
I. 518652
J. 412985
BANK IDENTIFICATION NUMBER (BIN)
Copyright © FI Network www.finetwork.co.uk
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A
B
CD
E
F
G
H
IJ
The top 10 Overseas BIN’s were:
A. 424631 (USA)
B. 426588 (Singapore)
C. 446272 (Gibraltar)
D. 515599 (USA)
E. 439225 (China)
F. 451297 (Singapore)
G. 456605 (Japan)
H. 517805 – (USA)
I. 458097 (Israel)
J. 513141 (France)
The FIN Intelligence Tool identified that the highest risk
came from UK payment cards with the top overseas
payment card originating from the USA (number 15 overall).
Top 5 Overseas BIN Origin Countries
• USA
• Singapore
• Japan
• Israel
• China
53% of payment
cards linked to two or more fraudulent
transactions
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Fraud Intelligence Network – Travel Fraud Case Study
A
B
CDE
F
G
HI J
A
B
CD
E
F
G
HI J
Over 185 different flight destinations were associated with
fraudulent transactions by the FIN Intelligence Tool.
The top 10 Overseas Flight Destinations were:
A. Tenerife
B. Dalaman
C. Antalya
D. Lanzarote
E. Banjul
F. Fuerteventura
G. Sharm El Sheikh
H. Gran Canaria
I. Hurghada
J. Tunisia
The top 10 Hotel Destinations were:
A. Egypt
B. Morocco
C. Turkey
D. Tunisia
E. Tenerife
F. Germany
G. Dubai
H. Spain
I. Cyprus
J. Ibiza
TOP TIP:
Analysis of the destinations of your fraudulent bookings
will show they reflect your top selling destinations, but
there will be some hotspots where vigilance is required,
consider flagging such bookings for review.
Consider flagging high risk destinations for review.
DESTINATIONS AND DEPARTURE POINTS
Copyright © FI Network www.finetwork.co.uk
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A
BC
D
E
FGH I J
A
BC
D
E
FGH I J
The top 10 UK Departure Points were:
A. Manchester
B. Gatwick
C. Glasgow
D. Birmingham
E. Newcastle
F. East Midlands
G. Bristol
H. Belfast
I. Cardiff
J. Stansted
EMAILS AND DOMAINS 999 unique domains were associated with fraudulent
transactions by the FIN Intelligence Tool of which 90% were
.com and .co.uk. 10% of the domains were based outside
the UK. 75% of domains were Yahoo, Hotmail or Google email
accounts.
The top 10 Domains were:
A. yahoo.com
B. hotmail.com
C. gmail.com
D. hotmail.co.uk
E. yahoo.co.uk
F. aol.com
G. yahoo.fr
H. btinternet.com
I. ymail.com
J. live.com
The most common
email address was found in
54 records
The Most Common Top Level Domains are:
• 35% - Yahoo – 44 million users in Europe
• 25% - Hotmail – 108 million uses in Europe
• 24% - Other
• 16% - Google – 75 million users in Europe
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Fraud Intelligence Network – Travel Fraud Case Study
A
B
CDEFGHIJ
The top 10 Top Level Domains were:
A. .com
B. .co.uk
C. .fr
D. .es
E. .it
F. .net
G. .de
H. .ca
I. .br
J. .org
TOP TIP:
10% of fraudulent email addresses were used in another
fraudulent booking making it clear that attention needs to
be paid to email addresses when reviewing a booking.
Have a system in place to monitor duplicate email addresses
against new bookings
LOCATION DATA When processing the data through the FIN Intelligence
Tool IP addresses originating in 88 different countries
were found, but 72% of them were linked to the USA and
UK. 64% of UK IP addresses originated from London.
The most common IP address was found in 46
records.
66 IP addresses were found in 5 or more records
185 IP addresses were found in 3 or more records.
33% of IP addresses linked to two or more records
Copyright © FI Network www.finetwork.co.uk
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A
B
CD
EFGHI J
A
B
CDEFGHIJ
The top 10 UK IP Addresses were:
A. London
B. Maidenhead
C. Manchester
D. Birmingham
E. Ipswich
F. Newbury
G. Ilford
H. Northampton
I. Berkshire
J. Leicester
TOP TIP:
Cross reference location data such as Post Codes,
IP addresses and Bank Identification Numbers (BIN).
UK Post Code + Spanish IP address + USA BIN = High
Risk Booking
The top 10 IP Address Countries were:
A. United States of America
B. United Kingdom
C. Mexico
D. Netherlands
E. Malaysia
F. Spain
G. South Africa
H. Canada
I. France
J. Indonesia
The FIN Intelligence Tool confirmed that UK Post Codes are the most frequently used for
travel fraud. In the case study UK Post Codes accounted for 94% of records with 17 of
the 20 most frequently occurring Post Codes/Zip Codes being in the London Area.
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Fraud Intelligence Network – Travel Fraud Case Study
A
B
C
DE
F
G
H
IJ
A
B
C
DE
F
G
H
IJ
The top 10 Post Codes/Zip Codes were:
A. Stratford – E15
B. South Woodford – E18
C. Harlesden – NW10
D. Kidderminster – DY12
E. New Cross – SE14
F. Sleaford – NG34
G. Streatham – SW16
H. Archway – N19
I. Barking – IG11
J. Broxbourne – NW19
The top 10 UK Post Code Areas were:
A. East London
B. Birmingham
C. North London
D. South East London
E. Manchester
F. Glasgow
G. North East London
H. Nottingham
I. South West London
J. North West London
OTHER DATA The time lag between the booking and the fraudster actually
taking the service is the booking lead time.
• The Average booking lead time was 3.5 days
• Flight only booking lead time was 10.5 days
• Hotel (Overseas) booking lead time was 5.5 days
• Car Hire booking lead time was 5 days
• Hotel (UK) booking lead time was 2.5 days
85% of Post Codes
used for fraud were in
London
Copyright © FI Network www.finetwork.co.uk
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TOP TIP:
With the trend of fraud booking being booked last
minute establish a system to review such bookings.
Identify and check last minute bookings
Fraudsters will often vary their IP address and email address to hide who they are but
they tend to use the same telephone number.
• 90% of records were for mobile telephones
• 10% of records were linked to landline telephones
• 76% of telephone numbers were linked to 2 or more records
• The most common telephone number was found in 57 records
TOP TIP:
Fraudsters tend to use the same telephone number
repeatedly
Have a system in place to identify duplicate telephone
numbers
76% of telephone
numbers linked to two or more
records
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Fraud Intelligence Network – Travel Fraud Case Study
HOW TO USE THE CASE STUDY
The FIN Intelligence Tool has identified a number of parameters that were found to be
connected to fraud in data from 52 unconnected businesses within the travel sector.
Time and again the same piece of data was repeated in other companies records
related to a fraud. This shows how organised and methodical the attacks on business
really are. So how do you make use of that information?
Every company needs to be aware that it is
under attack in relation to payment fraud.
The results from this case study confirm that the
best way to tackle payment fraud in travel is to
work collaboratively with other organisations and
share data amongst themselves and the police.
However as well as sharing the fraud data with
other travel companies and the police,
businesses can take a number of steps
themselves to defend themselves. The good
news is that these steps need not cost much
money to implement.
The first thing every company should do is to
carry out regular fraud audits on its transactional
data. Specifically, companies should try and
identify unusual transactions such as a number
of repayments to a single payment card.
Use the fraud audit to identify fraudulent
bookings and to analyse each one to see
whether any of the parameters we have used
show up. For travel companies the case study
data can be used to supplement this information.
Company policies should ensure that no single
staff member can make payments and also
process bookings. All staff that deal with money
should be properly managed and supervised.
Use the parameters we have identified to identify
what a high risk is booking. Make sure you are
then reviewing high risk bookings to recognise
potential frauds.
Do not take unnecessary risks. The profit
margin on a booking is less than the cost of a
fraud.
Use the same parameters that we have to
identify the areas that you should monitor and
share with the police and industry partners.
Use 3rd party verification tools to help you
identify genuine customers from fraudsters. Do
not place over reliance on this technology as
there is no single solution to payment fraud.
Report all fraud to the police using Action Fraud
via www.actionfraud.police.uk. If you do not
report it, the police cannot see the complete
picture of fraud activity and identify the major
crime networks and organised crime gangs.
Make sure you are joined up to a free fraud alert
service. www.profit.uk.com offers free alerts
which are used by organisations worldwide.
Train your staff to identify fraudulent activity and
high risk transactions.
Copyright © FI Network www.finetwork.co.uk
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THIRD PARTY FACTS
“£87 billion was spent online during
2012, representing a 14% increase
year on year.”
Marketing Week
“48% of people that booked an
overseas holiday during 2012
booked it as a package holiday.”
ABTA
“Slough was the ID fraud hotspot in
the UK during 2012, with residents
being four times more likely to be
targeted by fraudsters than the national
average.”
Experian
“During 2012 total fraud losses
on UK cards was £388 million, of
which £245 million related to
card holder not present (CNP)
fraud”
UK Card Association
“In 2012 UK residents made 50.3
million visits abroad.”
Office of National Statistics
“65% of all fraud cases reported in
2012 by CIFAS members required
ID theft to enable them.”
CIFAS
“During 2012, 7p in every £100 was
lost to fraud as a proportion of the
amount spent on cards during 2012”
UK Card Association
“The total fraud loss in the UK
during 2012 was £73 billion”
National Fraud Authority
“Between April 2011 and September
2012 77% of reported fraud related
to banking and payment fraud.”
NFIB
“4.5% of UK Card owners were
victims of credit card fraud during
the year ended September 2012.”
Crime Survey for England & Wales
“Cybercrime could cost small
UK firms £785 million a year”
Federation of Small Businesses
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Fraud Intelligence Network – Travel Fraud Case Study
ABOUT THE FIN TOOL
Most counter fraud tools on the UK market rely upon third party data of
varying quality. The FIN Intelligence Tool is a true intelligence tool which
ingests information and then applies analytical processes to identify
fraudulent data. Designed to handle payment data and much more besides
FIN has been specifically built to be the hub into the NFIB for any industry.
Existing fraud detection services typically use only a small subset of the information available from a multitude of sources to combat fraud. FIN is capable of analysing all data in real time. The most effective counter-fraud approach relies on the largest possible reporting community providing a known standard of data that can be relied upon 100%. The FIN counter fraud tool is a true intelligence tool which has a number of unique features making it the only truly ‘next generation’ solution to fraud and crime. This tool is now available to protect your organisation. To find out how FIN can help you contact us at: newbusiness@fraudintelnet.co.uk
FIN works to the same intelligence gathering standards as the Police and can automatically report crime directly into Police systems. In addition it is compatible with the architecture of the National Fraud Intelligence Bureau (NFIB). Within the tool is a secure community environment where users can seek help from other users and explore unusual patterns of events in confidence. The system features very secure links between the systems and users and also the National Fraud Intelligence Bureau. All users are trained to ensure integrity and security is maintained. As a true intelligence tool FIN is capable of acting as a secure hub for any industry sector. This means that organisations can work cooperatively using the FIN tool to protect their industry sector safe in the knowledge that they will obtain advance notice of issues arising in other sectors.
NETW ORKS
SECURITY
INDUSTRY HUB
UK POLICING
Copyright © FI Network www.finetwork.co.uk
21
ABOUT THE NFIB
The National Fraud Intelligence Bureau (NFIB) is the national fraud intelligence
hub which accepts fraud data from a wide range of private and public sector
sources, police forces and the public. This data is processed using data
analytics and a skilled team of data analysts who generate a wide range of
outputs used for prevention and enforcement.
The NFIB’s purpose is to:
• Make effective us of intelligence from fraud victims across the UK (be they
individuals, businesses or the public purse) – exploiting such information to
help; alert, educate, and protect; find new and effective ways to engineer out
the threat from fraud; and positively influence the UK’s limited enforcement
resources to tackle fraud crime.
• Harvest, process and analyse fraud data to provide actionable intelligence to
the UK counter fraud community, promoting a better understanding of fraud,
including themes and trends in order to inform more focussed, collaborative
prevention and disruption.
• Develop and allocate crime packages to facilitate local, regional and national
police functions and other law enforcement agencies’ investigations into the
most harmful instances of fraud-linked criminal activity.
• Achieve an improved and effective response to organised fraudsters by
adding value to the knowledge and understanding of organised crime groups
directly and indirectly related to fraud crime through its connectivity with the
Organised Crime Co-ordination Centre.
Since its inception in 2008, the NFIB has achieved much but will now be looking to
improve relationships with existing data providers, improve constraints written into
original data provider contracts and reform it’s business processes. The aim is to
generate an even richer fraud intelligence picture, more effective prevention
disruption activity and a higher return on investment.
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Fraud Intelligence Network – Travel Fraud Case Study
Contacts
National Fraud Intelligence Bureau (NFIB) Url: www.nfib.police.uk
Fraud Intelligence Network (FIN) Email: newbusiness@fraudintelnet.co.uk Url: www.finetwork.co.uk
Prevention of Fraud in Travel (PROFiT) Email: contactus@profit.uk.com Url: www.profit.uk.com
TO REPORT A FRAUD
Action Fraud Url: www.actionfraud.police.uk Telephone: 0300 123 2040 Phone lines are open: Mon to Fri – 8am to 9pm Sat to Sun – 9am to 5pm Closed Bank Holidays Calls charged at local rate (0300 phone numbers cost the same as a call to local landline numbers, even from a mobile phone).
© Copyright 2013
No part of this publication may be reproduced, transmitted, transcribed, stored in a retrieval system, nor translated into any human or computer language, in any form or by any means, electronic, mechanical, optical, chemical, manual or otherwise without the prior written consent of FI Network, 23 Wansbeck Court, Waverley Road, Middlesex. EN2 7BS.
Cover image credit: <a href='http://www.123rf.com/photo_3804474_2d-illustration-of-a-flat-world-map-hovering-over-a-wireframe-globe-with-navigational-markings-aroun.html'>norebbo / 123RF Stock Photo</a> Aircraft Image credit: <a href='http://www.123rf.com/photo_13553590_airplane-lifting-up-on-the-runway-with-white-sky.html'>fabian19 / 123RF Stock Photo</a>
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