Big Data Crime Stoppers: Catching Credit Card Fraud Before It Happens
Millions of people enjoy the convenience of having a credit card. But with a credit card comes a massive trail of data, and obtaining this data to use for their gain has become a way for fraudsters to turn your income into theirs. In 2017, CreditDonkey reported that, “46% of Americans have been victim to credit card fraud in the past five years.” That means that there’s an excellent chance that your credit card information has been stolen. So, what’s being done to stop these scams?
Law enforcement and financial institutions have found a powerful ally in the detection and prevention of credit card fraud. Big Data is now recognized for its analytical and predictive applications, and with the data that credit card transactions leave behind, big data is proving to be much needed support for law enforcement and financial institutions against fraudsters.
This article will take a look at how credit card fraud has impacted consumers, businesses, and law enforcement as well as how big data and machine learning is helping to stop it.
How Credit Card Fraud is Carried Out
Credit card fraud can happen to you, a consumer, in many ways — someone could physically take your card, gain your information by going through your trash, or through a good old-fashioned telephone scam. There is also credit card skimming — where fraudsters put in a fake transaction terminal at an ATM or gas pump for you to put your credit card into, giving that information straight to them.
In some instances, your PIN number can even be noted by a person looking over your shoulder as you make a withdrawal from the ATM. It is important to keep your credentials secure, as Panda Security puts it: “Most people still use passwords that are easy for cyber thieves to guess despite the devastating effects of identity theft.” However, sometimes it is out of your control how your credentials get stolen, but still will have devastating effects.
Credit card fraud hits businesses and financial institutions with the same — if not more — tenacity, but the end goal is the same. Customer credit card information can be obtained by hackers through massive data breaches. We have seen this with Equifax, where 143 million customers were subjected to having their personal information, including financial data, accessed by hackers.
This information can be used, just as the information above, to make purchases in your name for fraudsters. Businesses and financial institutions alike have made strides to protect customer information, but with each solution, hackers find a new way to obtain customer data illegally.
Law enforcement has their hands full keeping up with credit card fraud and the increasingly advanced ways hackers can get their hands on customer information. However, a good scammer can be almost impossible to catch if they cover their tracks well. That is, until big data analysis was discovered to uncover these tracks, as well as detect when a person’s credit card is being used without their permission to detect and prevent credit card fraud.
How Big Data Detects Credit Card Fraud
Ever gotten a text or call from your bank asking if you have made a recent big purchase? This call is big data stepping in to prevent a possible unauthorized transaction. Machine learning is at the forefront of detecting credit card fraud with self-learning algorithms to understand and predict your purchasing patterns.
Machine learning is fed the many points of data a transaction gives — how much you typically spend in a month, where you frequently make sales, as well as other telling purchase points, and can instantaneously determine that you probably aren’t out of the country on a tremendous shopping spree. Or, at the very least, it will notice that this behavior is out of the norm for you and will alert your bank. This will prompt your bank to double check the purchase with you. If it is not you, the bank will reject the sale, saving you a headache, your bank a fortune, and apprehend the scammer.
Your transactional data is very telling, and that’s why hackers and fraudsters can do so much with it. Using big data and predictive analytics like machine learning not only helps protect you, but financial institutions are now relieved to minimize or eliminate the damage, detecting and preventing credit card fraud in real time.
Big data is transforming industries with its many applications. Many people think that it leaves the door open for cyberattacks, but in the instance of detecting and preventing credit card fraud it is proving to be a valuable tool for consumers, businesses, law enforcement, and financial institutions.