AVOIDING PAYMENT FRAUD WITHIN THE UK TRAVEL INDUSTRY … · 2013-09-04 · Many fraud case studies and reports have been published over the years; this is the first case study that

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

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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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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


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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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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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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.


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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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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)


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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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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


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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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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


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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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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


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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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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.


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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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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: [email protected]

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


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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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Contacts

National Fraud Intelligence Bureau (NFIB) Url: www.nfib.police.uk

Fraud Intelligence Network (FIN) Email: [email protected] Url: www.finetwork.co.uk

Prevention of Fraud in Travel (PROFiT) Email: [email protected] 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>

Documents

AVOIDING PAYMENT FRAUD WITHIN THE UK TRAVEL INDUSTRY … · 2013-09-04 · Many fraud case studies and reports have been published over the years; this is the first case study that