CREDIT CARD FRAUD DETECTION
“Fraud detection is a set of activities that are taken to prevent money or property from being obtained through false pretenses.”
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Machine Learning-based Fraud Detection:
- Detecting fraud automatically
- Real-time streaming
- Less time needed for verification methods
- Identifying hidden correlations in data
Credit Card Fraud Detection with Machine Learning is a process of data investigation by a Data Science team and the development of a model that will provide the best results in revealing and preventing fraudulent transactions. This is achieved through bringing together all meaningful features of card users’ transactions, such as Date, User Zone, Product Category, Amount, Provider, Client’s Behavioral Patterns, etc. The information is then run through a subtly trained model that finds patterns and rules so that it can classify whether a transaction is fraudulent or is legitimate. All big banks like RBI(Reserve bank of India) use fraud monitoring and detection systems.
How credit card fraud happen?
Credit card fraud is usually caused either by card owner’s negligence with his data or by a breach in a website’s security. Here are some examples:
- A consumer reveals his credit card number to unfamiliar individuals.
- A card is lost or stolen and someone else uses it.
- Mail is stolen from the intended recipient and used by criminals.
- Business employees copy cards or card numbers of its owner.
- Making a counterfeit credit card.
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