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Understanding Credit Card Frauds

Understanding Credit Card Frauds
Understanding Credit Card Frauds


Credit Card Fraud is one of the biggest threats to business establishments today.
However, to combat the fraud effectively, it is important to first understand the
mechanisms of executing a fraud. Credit card fraudsters employ a large number of
modus operandi to commit fraud. In simple terms, Credit Card Fraud is defined as:
When an individual uses another individuals’ credit card for personal reasons while the
owner of the card and the card issuer are not aware of the fact that the card is being
used. Further, the individual using the card has no connection with the cardholder or
issuer, and has no intention of either contacting the owner of the card or making
repayments for the purchases made.

Credit card frauds are committed in the following ways:
?? An act of criminal deception (mislead with intent) by use of unauthorized account
and/or personal information
?? Illegal or unauthorized use of account for personal gain
?? Misrepresentation of account information to obtain goods and/or services.
Contrary to popular belief, merchants are far more at risk from credit card fraud than the
cardholders. While consumers may face trouble trying to get a fraudulent charge
reversed, merchants lose the cost of the product sold, pay chargeback fees, and fear
from the risk of having their merchant account closed.

Increasingly, the card not present scenario, such as shopping on the internet poses a
greater threat as the merchant (the web site) is no longer protected with advantages of
physical verification such as signature check, photo identification, etc. In fact, it is almost
impossible to perform any of the ‘physical world’ checks necessary to detect who is at the
other end of the transaction. This makes the internet extremely attractive to fraud
perpetrators. According to a recent survey, the rate at which internet fraud occurs is 12
to 15 times higher than ‘physical world’ fraud. However, recent technical developments
are showing some promise to check fraud in the card not present scenario.

Purpose of this Paper

The purpose of this white paper is to study:
State of the credit card industry,
Different types of frauds,
How fraudsters attempt to take advantage of loopholes,
Impact of credit card fraud on card holders, merchants, issuers,
How a comprehensive fraud detection system could help maintain the cost of
detecting fraud, and
Losses due to fraud, i.e., the total cost of fraud, under manageable levels.
While the focus of the document will be mostly on Visa and MasterCard type transactions,
the concepts and ideas generally prove valid with other credit cards such as American

Express and Discover also.

Current State of the Industry

While the exact amount of losses due to fraudulent activities on cards is unknown,
various research analyst reports concur that the figure for year 2002 probably exceeds
$2.5 billion. Further, as the overall e-commerce volumes continue to grow and fraudsters
adopt more complex schemes, the projected figure for losses to internet merchants in the
US alone is expected to be in the range of $5–15 billion by the year 20051. This again is
dependent on how rapidly fraud prevention technology will be adopted by the industry.
The incidence of fraud for credit card transactions taking place over the internet is
according to Garner G22, nearly 15 times higher than face-to-face transactions.

The increased likelihood of fraud, in conjunction with the full economic liability for fraud
losses makes risk management one of the most important challenges for Internet
merchants worldwide.

How Fraud is Committed Worldwide?
While lost or stolen card is the most common type of fraud, others include identity theft,
skimming, counterfeit card, mail intercept fraud and others. Table 1 summarises the
modus operandi for credit card frauds and their percentage of occurrence.

Method Percentage
Lost or stolen card 48%
Identity theft 15%
Skimming (or cloning) 14%
Counterfeit card 12%
Mail intercept fraud 6%
Other 5%

Table 1: Methods of Credit Card Fraud and their percentage of occurrence
Source: Celent Communications, January 2003

Amongst the high risk countries facing Credit Card Fraud menace, Ukraine tops the list
with staggering 19% fraud rate closely followed by Indonesia at 18.3% fraud rate. Also in
the list of high risk countries are Yugoslavia (17.8%), Turkey (9%) and Malaysia (5.9%).
Surprisingly United States, with its high number Credit Card transactions, has a minimum
fraud rate.

Over the last few years, the credit card industry in UK was subjected to maximum threat
from increasing fraud losses. Table 2 shows the worrying trend in volume of credit card
frauds in UK over the last few years.

Fraud Category 2000 2001 % Change
Counterfeit 107.1 160.3 +50
Card-not-present 72.9 95.7 +31
Lost/stolen card 101.9 114.0 +12
Intercepted in post 17.7 26.7 +51
Fraudulent application 10.5 6.6 +37
Other 6.9 8.0 +15
Totals 317.0 411.4 +30
Losses as % of turnover 0.162 0.183 +13

Table 2: Trend of fraud categories in UK for 2000–2001 (in Pound Sterling millions)
Source: APACS, March 2002
Stolen and counterfeit cards together contribute to more than 60% of fraud losses
according to figures published by both MasterCard and Visa in Figure 1.

Figure 1: Visa & MasterCard accounts by fraud types for year 2001 (January to May)
Source: APACS, March 2002


As indicated above, there are many ways in which fraudsters execute a credit card fraud.
As technology changes, so do the technology of fraudsters, and thus the way in which
they go about carrying out fraudulent activities. Frauds can be broadly classified into
three categories, i.e., traditional card related frauds, merchant related frauds and
internet frauds. The different types of methods for committing credit card frauds are
described below:

Card Related Frauds

This type of fraud occurs when a person falsifies an application to acquire a credit card.
Application fraud can be committed in three ways:
?? Assumed identity, where an individual illegally obtains personal information of
another individual and opens accounts in his or her name, using partially legitimate
?? Financial fraud, where an individual provides false information about his or her
financial status to acquire credit.
?? Not-received items (NRIs) also called postal intercepts occur when a card is stolen
from the postal service before it reaches its owner’s destination.

A card is lost/stolen when a legitimate account holder receives a card and loses it or
someone steals the card for criminal purposes. This type of fraud is in essence the easiest
way for a fraudster to get hold of other individual’s credit cards without investment in
technology. It is also perhaps the hardest form of traditional credit card fraud to tackle.

This type of fraud occurs when a fraudster illegally obtains a valid customers’ personal
information. The fraudster takes control of (takeover) a legitimate account by either
providing the customers account number or the card number. The fraudster then contacts
the card issuer, masquerading as the genuine cardholder, to ask that mail be redirected
to a new address. The fraudster reports card lost and asks for a replacement to be sent.

The creation of counterfeit cards, together with lost / stolen cards pose highest threat in
credit card frauds. Fraudsters are constantly finding new and more innovative ways to
create counterfeit cards. Some of the techniques used for creating false and counterfeit
cards are listed below:

1. Erasing the magnetic strip: A fraudster can tamper an existing card that has been
acquired illegally by erasing the metallic strip with a powerful electro-magnet. The
fraudster then tampers with the details on the card so that they match the details of a
valid card, which they may have attained, e.g., from a stolen till roll. When the
fraudster begins to use the card, the cashier will swipe the card through the terminal
several times, before realizing that the metallic strip does not work. The cashier will
then proceed to manually input the card details into the terminal.
This form of fraud has high risk because the cashier will be looking at the card closely
to read the numbers. Doctored cards are, as with many of the traditional methods of
credit card fraud, becoming an outdated method of illicit accumulation of either funds
or goods.

2. Creating a fake card: A fraudster can create a fake card from scratch using
sophisticated machines. This is the most common type of fraud though fake cards
require a lot of effort and skill to produce. Modern cards have many security features
all designed to make it difficult for fraudsters to make good quality forgeries.
Holograms have been introduced in almost all credit cards and are very difficult to

forge effectively. Embossing holograms onto the card itself is another problem for
card forgers.

3. Altering card details: A fraudster can alter cards by either re-embossing them — by
applying heat and pressure to the information originally embossed on the card by a
legitimate card manufacturer or by re-encoding them using computer software that
encodes the magnetic stripe data on the card.

4. Skimming: Most cases of counterfeit fraud involve skimming, a process where
genuine data on a card’s magnetic stripe is electronically copied onto another.
Skimming is fast emerging as the most popular form of credit card fraud.
Employees/cashiers of business establishments have been found to carry pocket
skimming devices, a battery-operated electronic magnetic stripe reader, with which
they swipe customer’s cards to get hold of customer’s card details. The fraudster does
this whilst the customer is waiting for the transaction to be validated through the card
terminal. Skimming takes place unknown to the cardholder and is thus very difficult,
if not impossible to trace. In other cases, the details obtained by skimming are used
to carry out fraudulent card-not-present transactions by fraudsters. Often, the
cardholder is unaware of the fraud until a statement arrives showing purchases they
did not make.

5. White plastic: A white plastic is a card-size piece of plastic of any color that a
fraudster creates and encodes with legitimate magnetic stripe data for illegal
transactions. This card looks like a hotel room key but contains legitimate magnetic
stripe data that fraudsters can use at POS terminals that do not require card
validation or verification (for example, petrol pumps and ATMs).

Merchant Related Frauds
Merchant related frauds are initiated either by owners of the merchant establishment or
their employees. The types of frauds initiated by merchants are described below:

This type of fraud occurs when merchant owners and/or their employees conspire to
commit fraud using their customers’ (cardholder) accounts and/or personal information.
Merchant owners and/or their employees pass on the information about cardholders to

The fraudster in this type of fraud operates from a web site. Goods are offered at heavily
discounted rates and are also shipped before payment. The fraudulent site appears to be
a legitimate auction or a traditional sales site. The customer while placing orders online
provides information such as name, address and valid credit card details to the site. Once
fraudsters receive these details, they order goods from a legitimate site using stolen
credit card details. The fraudster then goes on to purchase other goods using the credit
card numbers of the customer. This process is designed to cause a great deal of initial
confusion, and the fraudulent internet company in this manner can operate long enough
to accumulate vast amount of goods purchased with stolen credit card numbers.

Internet Related Frauds
The Internet has provided an ideal ground for fraudsters to commit credit card fraud in
an easy manner. Fraudsters have recently begun to operate on a truly transnational

level. With the expansion of trans-border or ‘global’ social, economic and political spaces,
the internet has become a New World market, capturing consumers from most countries
around the world. The most commonly used techniques in internet fraud are described

1. Site cloning: Site cloning is where fraudsters clone an entire site or just the pages
from which you place your order. Customers have no reason to believe they are not
dealing with the company that they wished to purchase goods or services from
because the pages that they are viewing are identical to those of the real site. The
cloned or spoofed site will receive these details and send the customer a receipt of
the transaction via email just as the real company would. The consumer suspects
nothing, whilst the fraudsters have all the details they need to commit credit card

2. False merchant sites: These sites often offer the customer an extremely cheap
service. The site requests a customer’s complete credit card details such as name and
address in return for access to the content of the site. Most of these sites claim to be
free, but require a valid credit card number to verify an individuals age. These sites
are set up to accumulate as many credit card numbers as possible. The sites
themselves never charge individuals for the services they provide. The sites are
usually part of a larger criminal network that either uses the details it collects to raise
revenues or sells valid credit card details to small fraudsters.

3. Credit card generators: Credit card number generators are computer programs that
generate valid credit card numbers and expiry dates. These generators work by
generating lists of credit card account numbers from a single account number. The
software works by using the mathematical Luhn algorithm that card issuers use to
generate other valid card number combinations. The generators allow users to
illegally generate as many numbers as the user desires, in the form of any of the
credit card formats, whether it be American Express, Visa or MasterCard.


Unfortunately, occurrences of credit card frauds have only shown an upward trend so far.
The fraudulent activity on a card affects everybody, i.e., the cardholder, the merchant,
the acquirer as well as the issuer. This section analyses the impact that credit card frauds
have on all the players involved in transacting business through credit cards.
Impact of Fraud on Cardholders
It’s interesting to note that cardholders are the least impacted party due to fraud in credit
card transactions as consumer liability is limited for credit card transactions by the
legislation prevailing in most countries. This is true for both card-present as well as cardnot-
present scenarios. Many banks even have their own standards that limit the
consumer’s liability to a greater extent. They also have a cardholder protection policy in
place that covers for most losses of the cardholder. The cardholder has to just report
suspicious charges to the issuing bank, which in turn investigates the issue with the
acquirer and merchant, and processes chargeback for the disputed amount.

Impact of Fraud on Merchants
Merchants are the most affected party in a credit card fraud, particularly more in the
card-not-present transactions, as they have to accept full liability for losses due to fraud.
Whenever a legitimate cardholder disputes a credit card charge, the card-issuing bank
will send a chargeback to the merchant (through the acquirer), reversing the credit for
the transaction. In case, the merchant does not have any physical evidence (e.g. delivery
signature) available to challenge the cardholder’s dispute, it is almost impossible to
reverse the chargeback. Therefore, the merchant will have to completely absorb the cost
of the fraudulent transaction. In fact, this cost consists of several components, which
could add up to a significant amount. The cost of a fraudulent transaction consists of:

1. Cost of goods sold: Since it is unlikely that the merchandise will be recovered in a
case of fraud, the merchant will have to write off the value of goods involved in a
fraudulent transaction. The impact of this loss will be highest for low-margin

2. Shipping cost: More relevant in a card-not-present scenario. Since the shipping cost
is usually bundled in the value of the order, the merchant will also need to absorb the
cost of shipping for goods sold in a fraudulent transaction. Furthermore, fraudsters
typically request high-priority shipping for their orders to enable rapid completion of
the fraud, resulting in high shipping costs.

3. Card association fees: Visa and MasterCard have put in place fairly strict programs
that penalize merchants generating excessive chargebacks. Typically, if a merchant
exceeds established chargeback rates for any three-month period (e.g. 1% of all
transactions or 2.5% of the total dollar volume), the merchant could be penalized
with a fee for every chargeback. In extreme cases, the merchant’s contract to accept
cards could be terminated.

4. Merchant bank fees: In addition to the penalties charged by card associations, the
merchant has to pay an additional processing fee to the acquiring bank for every

5. Administrative cost: Every transaction that generates a chargeback requires
significant administrative costs for the merchant. On average, each chargeback
requires one to two hours to process. This is because processing a chargeback
requires the merchant to receive and research the claim, contact the consumer, and
respond to the acquiring bank or issuer with adequate documentation.

6. Loss of Reputation: Maintaining reputation and goodwill is very important for
merchants as excessive chargebacks and fraud monitoring could both drive
cardholders away from transacting business with a merchant.

Impact of Fraud on Banks (Issuer/Acquirer)
Based on the scheme rules defined by both MasterCard and Visa, it is sometimes possible
that the Issuer/Acquirer bears the costs of fraud. Even in cases when the Issuer/Acquirer
is not bearing the direct cost of the fraud, there are some indirect costs that will finally be
borne by them. Like in the case of chargebacks issued to the merchant, there are
administrative and manpower costs that the bank has to incur.
The issuers and acquirers also have to make huge investments in preventing frauds by
deploying sophisticated IT systems for detection of fraudulent transactions.

With all the negative impacts of fraudulent credit card activities – financial and product
losses, fines, loss of reputation, etc, and technological advancements in perpetrating
fraud – it’s easy for merchants to feel victimized and helpless. However, technological
advancements in preventing fraud have started showing some promise to combat fraud.
Merchants and Acquirers & Issuers are creating innovative solutions to bring down on
fraudulent transactions and lower merchant chargeback rates.
One of the main challenges with fraud prevention is the long time lag between the time a
fraudulent transaction occurs and the time when it gets detected, i.e., the cardholder
initiates a chargeback. Analysis shows that the average lag between the transaction date
and the chargeback notification could be as high as 72 days. This means that, if no fraud
prevention is in place, one or more fraudsters could easily generate significant damage to
a business before the affected stakeholders even realize the problem.

Fraud Prevention Technologies
While fraudsters are using sophisticated methods to gain access to credit card
information and perpetrate fraud, new technologies are available to help merchants to
detect and prevent fraudulent transactions. Fraud detection technologies enable
merchants and banks to perform highly automated and sophisticated screenings of
incoming transactions and flagging suspicious transactions.
While none of the tools and technologies presented here can by itself eliminate fraud,
each technique provides incremental value in terms of detection ability. As it will be
discussed later, the best practice implementations often utilize several of these fraud
prevention techniques, if not all of the tools discussed here.
The various fraud prevention techniques are discussed below:

This method consists of reviewing every transaction manually for signs of fraudulent
activity and involves a exceedingly high level of human intervention. This can prove to be
very expensive, as well as time consuming. Moreover, manual review is unable to detect
some of the more prevalent patterns of fraud, such as use of a single credit card multiple
times on multiple locations (physical or web sites) in a short span.

This technique is applicable in card-not-present scenarios. Address Verification System
(AVS) matches the first few digits of the street address and the ZIP code information
given for delivering/billing the purchase to the corresponding information on record with
the card issuers. A code representing the level of match between these addresses is
returned to the merchant. AVS is not much useful in case of international transactions.

The Card Verification Method3 (CVM) consists of a 3- or 4-digit numeric code printed on
the card but is not embossed on the card and is not available in the magnetic stripe. The
merchant can request the cardholder to provide this numeric code in case of card-notpresent
transaction and submit it with authorization. The purpose of CVM is to ensure
that the person submitting the transaction is in possession of the actual card, since the
code cannot be copied from receipts or skimmed from magnetic stripe. Although CVM
provides some protection for the merchant, it doesn’t protect them from transactions
placed on physically stolen cards. Furthermore, fraudsters who have temporary
possession of a card could, in principle, read and copy the CVM code.

A negative list is a database used to identify high-risk transactions based on specific data
fields. An example of a negative list would be a file containing all the card numbers that
have produced chargebacks in the past, used to avoid further fraud from repeat
offenders. Similarly a merchant can build negative lists based on billing names, street
addresses, emails and internet protocols (IPs) that have resulted in fraud or attempted
fraud, effectively blocking any further attempts. A merchant/acquirer could create and
maintain a list of high-risk countries and decide to review or restrict orders originating
from those countries.

Another popular example of negative list is the SAFE file distributed by MasterCard to
merchants and member banks. This list contains card numbers, which could be
potentially used by fraudsters, e.g., cards that have been reported as lost or stolen in the
immediate recent past.

Positive files are typically used to recognize trusted customers, perhaps by their card
number or email address, and therefore bypass certain checks. Positive files represent an
important tool to prevent unnecessary delays in processing valid orders.

Payer authentication is an emerging technology that promises to bring in a new level of
security to business-to-consumer internet commerce. The first implementation of this
type of service is the Verified by Visa (VbV) or Visa Payer Authentication Service (VPAS)
program, launched worldwide by Visa in 2002. The program is based on a Personal
Identification Number (PIN) associated with the card, similar to those used with ATM
cards, and a secure direct authentication channel between the consumer and the issuing
bank. The PIN is issued by the bank when the cardholder enrolls the card with the
program and will be used exclusively to authorize online transactions.
When registered cardholders check out at a participating merchant’s site, they will be
prompted by their issuing bank to provide their password. Once the password is verified,
the merchant may complete the transaction and send the verification information on to
their acquirer.

3 Various card issuers use different names to indicate this security feature: CVV2 for VISA, CVC2 for Master Card and CID for
American Express.

Automatic card number generators represent one of the new technological tools
frequently utilized by fraudsters. These programs, easily downloadable from the Web, are
able to generate thousands of ‘valid’ credit card numbers. The traits of frauds initiated by
a card number generator are the following:
• Multiple transactions with similar card numbers (e.g. same Bank Identification
Number (BIN))
• A large number of declines
Acquiring banks/merchant sites can put in place prevention mechanisms specifically
designed to detect number generator attacks.

Both MasterCard and Visa publish a list of merchants who have been known for being
involved in fraudulent transactions in the past. These lists (NMAS – from Visa and MATCH
– from MasterCard) could provide useful information to acquirers right at the time of
merchant recruitment preventing potential fraudulent transactions.

Recent Developments in Fraud Management
The technology for detecting credit card frauds is advancing at a rapid pace – rules based
systems, neural networks, chip cards and biometrics are some of the popular techniques
employed by Issuing and Acquiring banks these days.
Apart from technological advances, another trend which has emerged during the recent
years is that fraud prevention is moving from back-office transaction processing systems
to front-office authorisation systems to prevent committing of potentially fraudulent
transactions. However, this is a challenging trade-off between the response time for
processing an authorisation request and extent of screening that should be carried out.

Simple rule systems involve the creation of ‘if…then’ criteria to filter incoming
authorisations/transactions. Rule-based systems rely on a set of expert rules designed to
identify specific types of high-risk transactions. Rules are created using the knowledge of
what characterizes fraudulent transactions. For instance, a rule could look like – If
transaction amount is > $5000 and card acceptance location = Casino and Country = ‘a
high-risk country’.

Fraud rules enable to automate the screening processes leveraging the knowledge gained
over time regarding the characteristics of both fraudulent and legitimate transactions.
Typically, the effectiveness of a rule-based system will increase over time, as more rules
are added to the system. It should be clear, however, that ultimately the effectiveness of
the system depends on the knowledge and expertise of the person designing the rules.
The disadvantage of this solution is that it can increase the probability of throwing many
valid transactions as exceptions, however, there are ways by which this limitation can be
overcome to some extent by prioritising the rules and fixing limits on number of filtered

Risk scoring tools are based on statistical models designed to recognize fraudulent
transactions, based on a number of indicators derived from the transaction
characteristics. Typically, these tools generate a numeric score indicating the likelihood of
a transaction being fraudulent: the higher the score, the more suspicious the order.
Risk scoring systems provide one of the most effective fraud prevention tools available.
The primary advantage of risk scoring is the comprehensive evaluation of a transaction
being captured by a single number. While individual fraud rules typically evaluate a few
simultaneous conditions, a risk-scoring system arrives at the final score by weighting
several dozens of fraud indicators, derived from the current transaction attributes as well
as cardholder historical activities. E.g., transaction amounts more that three times the
average transaction amount for the cardholder in the last one year.

The second advantage of risk scoring is that, while a fraud rule would either flag or not
flag a transaction, the actual score indicates the degree of suspicion on each transaction.
Thus, transactions can be prioritized based on the risk score and given a limited capacity
for manual review, only those with the highest score would be reviewed.

Neural networks are an extension of risk scoring techniques. They are based on the
‘statistical knowledge’ contained in extensive databases of historical transactions, and
fraudulent ones in particular. These neural network models are basically ‘trained’ by
using examples of both legitimate and fraudulent transactions and are able to correlate
and weigh various fraud indicators (e.g., unusual transaction amount, card history, etc)
to the occurrence of fraud.

A neural network is a computerized system that sorts data logically by performing the
following tasks:
?? Identifies cardholder’s buying and fraudulent activity patterns.
?? Processes data by trial and elimination (excluding data that is not relevant to the
?? Finds relationships in the patterns and current transaction data.
The principles of neural networking are motivated by the functions of the brain –
especially pattern recognition and associative memory. The neural network recognizes
similar patterns, predicting future values or events based upon the associative memory of
the patterns it has learned.

The advantages neural networks offer over other techniques are that these models are
able to learn from the past and thus, improve results as time passes. They can also
extract rules and predict future activity based on the current situation. By employing
neural networks effectively, banks can detect fraudulent use of a card, faster and more

Biometrics is the name given to a fraud prevention technique that records a unique
characteristic of the cardholder like, a fingerprint or how he/she sign his/her name, so

that it can be read by a computer. The computer can then compare the stored
characteristic with that of the person presenting the card to make sure that the right
person has the right card.

Biometrics, which provides a means to identify an individual through the verification of
unique physical or behavioral characteristics, seems to supercede PIN as a basis for the
next generation of personal identity verification systems.
There are many types of biometrics systems under development such as finger print
verification, hand based verification, retinal and iris scanning and dynamic signature

To define in the simplest terms, a smart card is a credit card with some intelligence in the
form of an embedded CPU. This card-computer can be programmed to perform tasks and
store information, but the intelligence is limited – meaning that the smart card’s power
falls far short of a desktop computer.

Smart credit cards operate in the same way as their magnetic counterparts, the only
difference being that an electronic chip is embedded in the card. These smart chips add
extra security to the card. Smart credit cards contain 32-kilobyte microprocessors, which
is capable of generating 72 quadrillion or more possible encryption keys and thus making
it practically impossible to fraudulently decode information in the chip.
The smart chip has made credit cards a lot more secure; however, the technology is still
being run alongside the magnetic strip technology due to a slow uptake of smart card
reading terminals in the world market.

Smart cards have evolved significantly over the past decade and offer several advantages
compared to a general-purpose magnetic stripe card. The advantages are listed below:
?? Stores many times more information than a magnetic stripe card.
?? Reliable and harder to tamper with than a magnetic stripe card.
?? Performs multiple functions in a wide range of industries.
?? Compatible with portable electronic devices such as phones and personal digital
assistants (PDAs), and with PCs.
?? Stores highly sensitive data such as signing or encryption keys in a highly secure
?? Performs certain sensitive operations using signing or encryption keys in a secure

A consortium of Europay MasterCard and Visa (EMV) recently issued a set of
specifications for embedding chips in credit cards and processing transactions from such
cards. MasterCard and Visa have also issued deadlines for compliance with these
specifications indicating that banks will have to bear a large portion of fraud losses if they
do not comply with EMV specifications. However, the market response has been slow so
far due to large investments needed in implementing the EMV compliant programs.

Managing the Total Cost of Fraud
An efficient fraud management solution is one that minimizes the total cost of fraud,
which includes the financial loss due to fraud as well as the cost of fraud prevention
systems. Too often success is mistakenly measured exclusively by one metric –the
monthly chargeback rate (Chargeback rate is defined as the percentage of chargeback
amount with regard to the net transaction amount). The question is what is the optimal
level of review that would keep fraud losses under control?

To minimize the actual total cost of fraud, an optimal balance needs to be achieved
between reducing fraud losses and overheads associated with review of transactions.
Reviewing the appropriate number of transactions is the key to achieve this optimal
balance. Figure 2 illustrates this trade-off between fraud reduction and the cost of
achieving that reduction.

The graph depicts the total cost of fraud as the sum of the actual fraud losses plus the
cost of review, which is typically proportional to the volume of transactions being
reviewed. The column on the left shows a scenario where fraud losses dominate the total
cost, because insufficient screening and review is applied. In this example, fraud loss
account for 1% of total value of processed transactions while only 2% of the transactions
are being reviewed.

The column on the right shows the opposite extreme – 30% of the processed transactions
are being reviewed and fraud losses are down to 0.06% of the total value of processed
transactions. In this case, however, the cost of review drives up the total cost of fraud.
While fraud losses are no longer an issue, the cost of achieving this result is not
acceptable. Finally, the column in the middle shows the optimal scenario; minimized total
cost with acceptable review cost and ‘manageable’ fraud losses.
As can be seen above, one of the major components of the ‘total cost of fraud’ is the
review of incoming transactions. Review of incoming transactions has both direct and
indirect costs associated with it. The direct aspect is the cost of human resources
Figure 2:

dedicated to the review. This cost is directly proportional to the volume of transactions
being subject to the review. The indirect costs, which are typically more difficult to
quantify, include the cost of other resources such as computer hardware, delay in
processing of transactions, etc.

The key to minimize the cost of review is to be able to segment transactions, products
and cardholders in order to determine the profile of potentially fraudulent transactions.
The risk of fraud is never the same for every single transaction. Indeed, there are many
factors that help determine the risk associated with a particular transaction. By
leveraging these factors, a bank can begin to isolate the problem and identify a relatively
small segment of the incoming transactions where review activity needs to be

As card business transactions increase, so too do frauds. Clearly, global networking
presents as many new opportunities for criminals as it does for businesses. While offering
numerous advantages and opening up new channels for transaction business, the
internet has also brought in increased probability of fraud in credit card transactions.
The good news is that technology for preventing credit card frauds is also improving
many folds with passage of time. Reducing cost of computing is helping in introducing
complex systems, which can analyse a fraudulent transaction in a matter of fraction of a

It is equally important to identify the right segment of transactions, which should be
subject to review, as every transaction does not have the same amount of risk associated
with it. Finding the optimally balanced ‘total cost of fraud’ and other measures outlined in
this article can assist acquiring and issuing banks in combating frauds more efficiently.



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  1. The offers are enticing. For a few hundred dollars, or sometimes more, firms offer to erase bad entries from your credit report. But if it were that easy, wouldn’t more people be doing it?


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