How many of you have noticed those texts coming from your credit card companies to verify that a recent transaction is a valid one. Maybe, you were buying an item at a store you hadn't shopped at before or you traveled out of the state (or out of the country). Have you ever wondered how those machine learning algorithms are working in the background to help prevent credit card fraud. Wonder no more!

Here's an explanation on how the fraud detection takes place (From The Week):

A machine learning algorithm for fraud detection needs to be trained first by being fed the normal transaction data of lots and lots of cardholders. Transaction sequences are an example of this kind of training data. A person may typically pump gas one time a week, go grocery shopping every two weeks, and so on. The algorithm learns that this is a normal transaction sequence.

After this fine-tuning process, credit card transactions are run through the algorithm, ideally in real time. It then produces a probability number indicating the possibility of a transaction being fraudulent (for instance, 97 percent). If the fraud detection system is configured to block any transactions whose score is above, say, 95 percent, this assessment could immediately trigger a card rejection at the point of sale.

The algorithm considers many factors to qualify a transaction as fraudulent: trustworthiness of the vendor, a cardholder's purchasing behavior including time and location, IP addresses, etc. The more data points there are, the more accurate the decision becomes.

Questions for students after reading the article:

• What is the maximum liability if someone uses your credit card for a purchase you didn't authorize?
• In your own words, what is machine learning?
• How much are humans involved in this process of fraud detection?
• What factors would make you suspicious of a given credit card's activity? 

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Interested in more activities focused on identity theft? Check out this NGPF interactive "Have You Been Hacked?"

About the Author

Tim Ranzetta

Tim's saving habits started at seven when a neighbor with a broken hip gave him a dog walking job. Her recovery, which took almost a year, resulted in Tim getting to know the bank tellers quite well (and accumulating a savings account balance of over $300!). His recent entrepreneurial adventures have included driving a shredding truck, analyzing executive compensation packages for Fortune 500 companies and helping families make better college financing decisions. After volunteering in 2010 to create and teach a personal finance program at Eastside College Prep in East Palo Alto, Tim saw firsthand the impact of an engaging and activity-based curriculum, which inspired him to start a new non-profit, Next Gen Personal Finance.