cyber 4 - Top 3 Must-Know Fraud Detection and Prevention Advances
December 13, 2019

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Cases
of identity theft and fraud are still at a widespread. In fact, the intensity
of damages they bring about to victims are becoming graver, now with small
businesses and clueless civilians being their main targets. 
Cyber Security

In
a recent Identity Fraud Study
conducted by Javelin, victims of fraud hit a record high of 16.7 million in
2017 but decreased to 14.4 million later in 2018. The catch here, though, is
that while the number of victims fell down by millions, the damages incurred
managed to reach $1.7 billion. This accounts to double the amount of losses
recorded in 2016.
Not
frightening enough?
Then
how about these findings in the 
Global Economic Crime and Fraud Survey done by PwC in UK. The organization
gathered 7,000 respondents who revealed:


·        Around
49 percent of the global organization respondents claimed to be a victim of
fraud. This is 13 percent higher than the recorded instances in 2016 which
accounts to 36 percent. This value doesn’t even include organizations that
aren’t aware that they already fell victim to such crime.
·  At
least 64% of the respondents said that the most disruptive fraud that happened
to them could’ve incurred up to $1 million in losses.
·     Unfortunately,
52% of all detected frauds were initiated by internal members of the attacked
organization.
These
statistics only mean that fraudsters are becoming wiser in their methods. They
know who the easy targets are and how to attack them. In fact, recent reports
pointed out how they shifted focus from big enterprises to smaller financial
accounts like rewards programs. They know very well that these accounts are
rarely wrapped with sophisticated cyber security tech and can be easily
infiltrated.
The
present generation is highly tech driven and even cyber criminals leverage
innovations to make fraud undetectable. The society and different firms then
need a stringent fraud detection system to, at least, minimize the attacks.
The
world isn’t going down without a fight. The battle against this crime has
evolved as new advances in fraud detection technologies arise. More controls
are being implemented to detect fraud in its earliest stages rather than after
the attack has been done.
Employment of Machine
Learning in Fraud Detection
Machine
learning is a form of
artificial intelligence
that most enterprises use for continuously learning data, and improving this
learning in an autonomous way. In the same fashion, machine learning is used in
fraud detection to continuously dig into the methods used by cyber criminals in
committing fraud. Hence, anyone using this tech becomes updated whenever a new
trend in fraud comes up. Consequently, they are able to revise their preventive
strategies to counter these newer trends. 
What’s
good about Machine Learning is that it never stops working. It digs into data
day and night, making it almost impossible to miss out any attempts of fraud in
the system. The machine compares all transactions with what it recorded as
normal behavior, and when a suspicious change happens, it alerts its owners of
a possible fraud. 
This
isn’t new, though. Machine learning has been used in the past years by
insurance companies and similar financial firms to protect them from any modus.
However, the difference comes with the analyzation and judgment of fraud
attempts.
In
the past, Machine Learning flags incidents for review by human. These days, it
has grown smarter that it can replicate human decision making through an
algorithm called Neural Networks. Amazingly, Machine Learning is now able to
make logical decisions, sometimes better than the judgment of humans.
How
does this benefit firms?
Even
before humans feel the damage caused by fraud, Machine Learning has already
finished detecting, reviewing, and stopping the crime. So the only way for a
criminal to carry on fraud is for him to outsmart Machine Learning. 
Big Analytics in
Improving Fraud Detection
Big
Analytics, like Machine Learning is used in analyzing data. However, Big
Analytics is only used to see trends and can’t do its own decision making.
However,
this technology can be used in fraud prevention and detection.
One
form of fraud usually committed in shopping centers is taking advantage of
their return programs. 
One
benefit of your big data analytics can be fraud prevention. As big data
analytics uses complex applications like what-if analysis and predictive
models, it is quite hard to trick the system. The data it gathers then serves
as a reference for you to detect unusual activities, and from there point out
attempts of fraud. 
Another
way to up your fraud detection game using big analytics is by connecting it as
an integral part of your machine learning system. While machine learning
already has its own detection capabilities, its scope can be broaden further
through big data analytics, making it highly accurate in gathering trends.
However,
these advance technologies are far from the reach of the common society. They
aren’t available for individual use and investing on them requires some serious
funds.
So
how can they detect and protect themselves from fraud attempts?
Prevention Before
Detection Techniques
As
mentioned earlier, small businesses as well as civilians are easy targets in
fraud. Most of them neglect the availability of anti-fraud and fraud detection
technologies, making them highly vulnerable to attacks.
A
simple antivirus no longer works in blocking cyber criminals who plan phishing
URLs online and on documents as well as text messages. There’s even a new form
of fraud called deepfake audio where criminals use
deepfake technology to alter their voice, making them
sound like they are an executive of a company. Being unaware of the presence of
these kinds of modus, a lot of people fall into the traps set by fraudsters and
it’s already too late when they realize that they have been robbed.
Most
antivirus companies already developed anti-fraud software including AVG
CloudCalre, Avast Business, and Eset Endpoint Security. These fraud prevention
software promise to deliver at least 99.7 percent stronger protection compared
to normal antiviruses. 
Their
functions include detecting new phishing trends that are usually the start of
identity theft and fraud.  There’s also a
content filtering option which allows systems to track and block websites being
opened on computers. Spam monitoring activities have been doubled too. The most
advanced anti-fraud software, though, have data encryption functions as well as
data loss prevention. 
Detection
features are also present. However, instead of pinpointing fraud attempts, they
alert users instead about suspicious websites, links, and attachments that can
open a window of opportunity for criminals to steal data and use them to carry
out fraud.
Final Words
Data
is the main weapon used by fraudsters in carrying out crimes. So apart from
investing on fraud detection technologies, businesses should also focus on
strengthening their preventive measures. All these solutions may sound
expensive for the common society, but antivirus software are just worth a few
dollars. 
Make
sure that the devices where you store information and save your financial
account credentials are well protected by firewalls and strong antivirus.
It
pays to have a tool in finding the root of fraud attacks, but it pays more to
prevent them even before they happen.
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