How Outsourced Payment Processing Helps to Prevent Frauds?

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Welcome To Loginworks Softwares
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How Outsourced Payment Processing Helps to
Prevent Frauds?

• Payments in an organization are a business
  critical phenomenon that must be processed with
  high security. Frauds that are a common
  occurrence in the payment system for any business
  usually take up a huge amount of time and energy
  to be identified and sorted.
• An estimated 63 of businesses worldwide have
  experienced some form of online payment
  processing fraud in the last one year. This is a
  significant number and is the 1 concern of
  E-Commerce sites. The online commercial market is
  global and the volume of frauds has shown a
  greater incidence in international transactions.

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5 Steps of outsourcing

• Thats why many big sites have outsourced payment
  processing to help prevent frauds. The additional
  expense is justified by the amount of money they
  save due to predictive analysis and prevention
  techniques. Outsourcing payment processing has
  not just helped in the prevention of frauds but
  also lowering down various other costs for a
  business. On the one hand, it is improving
  internal controls for an organization while on
  the other hand, it is also improving vendor
  relationships.

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Professional payment processing companies have
access to Big Data and the best Data Analytics
algorithms that can predict and prevent payment
frauds. To understand how this works, it is first
prudent to know what are the different types of
frauds are

Cards fraud

This is the most common kind of fraud that
affects online E-Commerce sites. As the online
retailers cannot see the credit cards physically,
their systems are not designed to detect fake or
stolen cards. Retailers do put in authentication
measures like one-time-passwords (OTPs), mobile
number or billing address verification, card
verification value (CVV) which is a 3-digit
number on the back of the card, etc. But these
measures are not foolproof and an expert hacker
can get this information very easily.
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Return fraud

• This has unfortunately been initiated by online
  retailers themselves by offering an easy return
  and full refund policy for some products.
  Fraudsters take advantage of this by using a
  product for a while and then either claiming they
  never received it or returning it saying it was
  damaged on receipt. E-Commerce sites are more
  susceptible to such frauds than shop sellers.
  They may have put in measures like confirmation
  of delivery, extra fees for returns, etc. but
  again, these methods have not been 100
  successful in preventing frauds.

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Identity theft

E-Commerce sites who have not outsourced their
payment process are also vulnerable to identity
theft. Hackers can steal the personal information
of the clients that they had entered during the
online transaction, like bank details, credit
card numbers, mobile phone numbers (needed for
the OTP), and other credentials. Online retailers
have their own ways of tracking customer
behavior, their preferences, their ordering
patterns, shipping addresses, contact details, to
try and eliminate identity fraud. But these
measures havent shown 100 success in preventing
frauds.
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How Outsourced Payment Processing Helps to
Prevent Frauds

• When the payment processing of online retailers
  is outsourced to professionals, they use advanced
  Data Analytics tools to detect suspicious
  patterns in online transactions. Their algorithms
  are designed to track online payment activities,
  compare the fresh data with historical data and
  check for similarities with previous fraudulent
  transactions. Therefore, there is no doubt that
  pattern analysis is the key factor that
  outsourced payment processing companies use to
  detect fraud. The algorithms look for patterns in

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1. A sudden large volume of purchases that do not
fit into the behavioral pattern of that customer.

2. Usage of a card that has been reported as
stolen.

3. Fake wire transfers.

4. Insufficient balance while using the debit
card online.

5. Mismatch of personal information like mobile
number and CVV.
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The Business Intelligence algorithms employed by
outsourced payment processing systems also look
for recognizable attack patterns when fraudsters
usually attack online retail sites. Some of them
are

Timing patterns

These activities are found to be most common
during festival or marriage seasons when the
volume of online business is very high. The
tax-filing season is also a time when fraudsters
can access personal details of online
transactions. But the predictive analysis tools
used by the outsourced payment processing
companies are designed to anticipate and abort
such activities before a fraud takes place.

Collaborative patterns

In some cases, apparently legitimate customers of
the online retailer may be partnering with known
criminals to attack online payment processing
systems. Data Analytics tools are designed to
track relationships between suspicious activities
between two individual entities. The most common
pattern is when purchases are made just below the
credit limit of the customer. By tracking the
history of such transactions, the algorithm can
intelligently detect if a particular transaction
is fraudulent.
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Prevention of Fraud

Data Analytics tools work very fast and provide
solutions in seconds. The faster a fraud is
detected, the better are the chances that it will
be prevented in time. It has to be an
instantaneous process so that there is no
monetary loss. It is not possible to apprehend
the crook because the person cannot be seen by
the online retailer. So prevention is the only
solution. The machine learning model employed by
outsourced payment processing companies is
capable of handling Big Data and millions of
simultaneous transaction and prevent fraudulent
ones at the same time.

Data analytics

Big Data is first categorized by the Data
Analytics tools used by outsourced payment
processing companies in order to analyze it. The
algorithms are first tested against the full data
to identify fraud patterns and to set the
parameters that will form the rules for fraud
detection. The machine learning model is also set
to seek out new fraud patterns to add to the list
of existing patterns. The algorithms must prevent
or minimize false positive customer behaviors at
the same time by speeding up the online payment
process.
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But how would a Data Analytics tool detect return
fraud? For Artificial Intelligence nothing is
impossible! The tool is already tracking customer
behavior on social media networks. The tools also
analyze images of products sold online with the
full knowledge of all the major E-Commerce sites.
When the social media images match the online
retailers images but the customer claims not to
have received the product or returns it claiming
that it is damaged, it is an obvious case of
return fraud.
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Real-time
detection

Real-time detection is another method used by
outsourced payment processing companies. They
track transaction patterns in real-time against
existing data warehouses, preset fraud rules,
card authorization patterns, etc. to not only
detect frauds but to also prevent them before the
transaction goes through. To do this, the machine
learning model will use and analyze data streams
simultaneously coming from the customers
smartphone apps and its location, customers
social media news feeds, purchase history,
retailers weblogs, and other sources of Big Data
to prevent fraudulent transactions.

As Artificial Intelligence tools can analyze
historical data dating back to days, weeks,
months, and even years, identifying fraud
patterns in real-time is not a difficult task.
The algorithms are capable of handling hundreds
and thousands of fraud-detection parameters
simultaneously to identify and prevent online
payment frauds.

The DA algorithms are also designed to process
streaming data by tracking movement and location
of high-value products. This will tell the
retailer when and where the product was delivered
to the customer. This process is essential for
preventing return frauds.
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Behavior analysis tools

• Behavior analysis is another major part of the
  fraud detection process that the DA tools of
  outsourced payment processing companies use. This
  involves a process of visually analyzing data to
  get insights even if the data is streaming in
  real-time from different geographical locations.
  The machine learning model will identify those
  regions, cities, localities, types of customers,
  usual products etc. that shows a high rate of
  fraudulent payments.
• This helps the retailer to allocate money
  accordingly for fraud prevention. As the
  incidents of fraud reduce, the time spent in
  reviewing every order is minimized. The algorithm
  can accurately predict and graphically present
  the probability of fraud for each online
  transaction. The DA tool is usually designed to
  send instantaneous red-alerts by email and SMS to
  the retailer for probable escalation.

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Advantages of outsourcing
payment processing

Cost reduction switching from cash mode of
payments to E- payments save time and money and
by outsourcing it, human resources can be focused
on other tasks and reduce the lead time.

Increased Security securing financial
information internally requires more security and
protocols and also place a burden on the finance
department. There, by outsourcing it, the third
party will secure all the financial information
from cyber theft and reduce the burden and saves
time.

Lessened fraud risk Outsourcing payment
processing actually improves internal controls of
the firm. Using a trusted third party provider
keeps important financial tasks separated and
therefore help reduce or eliminate fraud.

Improved vendor relation Streamlining the
payment system means faster and more accurate
payment processing. Since everyones happier when
they get paid on time and without any hassle,
that improves relationships with vendors.

Flexible payment solutions payment process
called Next Process allows the company to keep
the vendors in a payment loop so that the vendors
will receive a clear notification about the next
payment and makes them to choose the payment
option that is suitable for them and monitor the
status of the payment in real time.
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Conclusion

Today, the customer relationship is not limited
to just selling products and delivering them at
the right place on time. Considering the fierce
competition that online retailers have to face,
getting an edge over ones competitors by
providing the best customer experience is vital
for a business.
Customers are extremely sensitive about their
financial information and personal details being
misused by frauds. Therefore, part of the
customer satisfaction process also involves the
assurance that their online payment process is
both secure and super-fast. This assurance also
means a better conversion rate, more profits,
long-term customer retention, and the creation of
brand value for the retailer.

Therefore, more and more retailers and E-Commerce
sites are using outsourced payment processing
companies to help prevent frauds. Their machine
learning tools have parameters that track
patterns to detect probable frauds and to abort
the transactions before money is lost.
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