Credit Card Fraud: Prevention and Detection

What is Credit Card Fraud?

Credit card fraud is a type of financial crime in which a criminal steals someone’s credit card or credit card information and uses it to make unauthorized transactions. These transactions, withdrawals, and purchases are charged to the card-holder, which often leaves them in a financially debilitating situation.

Credit Card Fraud Detection using Machine Learning

Financial fraud is increasing in scale with time, and the digital revolution has given fraudsters more avenues than ever before to target individuals. A serious financial crime, like fraud, has far-reaching consequences for the financial industry.

Data mining has played a central role in the detection of credit card fraud through online transactions. The detection of credit card fraud is, essentially, a data mining issue. Therefore, it can be solved using Machine Learning implemented in technologies’ anti-fraud and anti-money laundering software.

The reason why ML is so successful in managing financial fraud is because it is an adaptive technology that addresses the main challenges of fraud detection.

The profiles of both normal and fraudulent behaviors are subject to constant change, and credit card fraud data sets are usually very skewed.

The sampling approach to the data set, selection of variables used, and the detection techniques used all play a major role in determining just how fraud detection programs will perform.

The main challenges involved in credit card fraud detection are:

  • Enormous amounts of data are processed every day and the model build must be fast enough to respond to the scam in a timely manner
  • Imbalanced Data – i.e., most of the transactions (99.8%) – are not fraudulent. This makes it hard to detect genuine cases of fraud
  • Data availability can be an issue, for this data is sensitive and mostly private
  • Misclassified Data can be another major issue, as not every fraudulent transaction is caught and reported
  • Scammers, too, can use adaptive techniques against the model

How to tackle these challenges?

  1. The model used must be simple, fast, and efficient enough to detect the anomaly and classify it as a fraudulent transaction as quickly as possible
  2. To protect the privacy of the user, the dimensionality of the data can be reduced
  3. A more trustworthy source must be taken that can double-check the data, especially while building the training model
  4. Make the model simple and interpretable, so, when a scammer adapts to it, with just some tweaks here and there, you can have a new model up and running to deploy

Credit Card Fraud Prevention Techniques

If you haven’t been subjected to credit card fraud yet, you are one of the lucky few. And, of course, we’re pretty sure you want to keep this lucky streak going and continue to stay safe from fraudsters.

To help you achieve this, knowing all of the precautions you can take to keep your account clean and your identity protected is a must. Protecting your private information online is the most important factor. Check your browser’s lock icon on the website bar to ensure you only use secure websites. Avoid sketchy emails to prevent falling prey to a phishing attack. Keep your anti-virus and spyware software up-to-date

Do your research on how to make the best of these integral tools. Follow password best practices at all times.

Key Highlights

  • Don’t share your login information
  • Don’t write your password down
  • Use a long password with a combination of upper- and lower-case letters, numbers, and special characters
  • Change your password regularly
  • These steps are key to avoiding fraud. A poorly protected account is as good as an unlocked front door when it comes to keeping your information safe
  • Be conscious while typing in your pin code when you are swiping your card in public or withdrawing money from a public ATM
  • Gas stations and ATMs are infamous for enabling credit card thieves, so be aware of your surroundings
  • Always save digital copies of your receipts for easy access and documentation in the event of credit card theft/fraud

A secure way to protect your payments, both online and in-person, is through the use of mobile wallets. Options such as Apple Pay and Google Pay offer a way to make secure payments from your smartphone or watch whether you’re in-store or at home. However, in recent times, these channels have also been used for money laundering and fraudulent activities.

How to Report Credit Card Fraud

Here are the steps to follow if you suspect you have been subjected to a credit card fraud attack:

  • Contact your card issuer/bank and inform them as soon as you notice suspicious activity on your account statement. Many banks have fraud departments who are equipped to handle the situation in a prompt manner.
  • If your card issuer confirms your suspicions of fraudulent activity, contact your national credit bureau
  • File a police report. The police have the resources and skill to track down financial criminals and fraudsters, and subsequently, bring them to justice

In the end, the most important factor when it comes to avoiding credit card fraud is your own vigilance and monitoring of your account. Checking your credit report and statements routinely will set you up for success and help you catch the problem in time in the event it occurs.

Unfortunately, history tells us that fraudsters will continue to find ways to scam people out of their hard-earned money. Yet, by being prepared and properly reviewing your transactions, a potential long-term nightmare may have a short-term solution.

 

References

https://medium.com/@palashshinde6/credit-card-fraud-detection-using-deep-learning-models-a8a918e29d4e

https://www.identityguard.com/news/credit-card-fraud-detection

https://ieeexplore.ieee.org/document/8123782

https://www.geeksforgeeks.org/ml-credit-card-fraud-detection/

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