Can anyone suggest me the latest dataset for Credit Card Fraud Detection ?

Here are a few suggestions:

Kaggle: While the "Credit Card Fraud Detection" dataset may not be the most recent, Kaggle often hosts competitions and provides access to various datasets related to finance and fraud detection. You can explore the platform to see if there are any new datasets or competitions relevant to your project.

UCI Machine Learning Repository: The UCI Machine Learning Repository is a valuable resource for various datasets, including those related to credit card fraud detection. While the repository may not have the most up-to-date datasets, it's worth checking for any new additions or updates.

Fraud Detection Datasets from Financial Institutions: Some financial institutions may release anonymized datasets for research purposes. Contacting financial institutions or searching their research publications may lead you to relevant datasets for credit card fraud detection.

Data Marketplaces: There are specialized data marketplaces that offer datasets for specific purposes, including fraud detection. You can explore platforms like Data.world, Data.gov, or other similar marketplaces to see if there are any datasets that meet your requirements.

Research Papers and Publications: Academic research papers often include details about the datasets used in their studies. Exploring recent papers on credit card fraud detection or related topics may lead you to new datasets or sources of data.

Remember to carefully review and preprocess any dataset you choose, ensuring it meets your project requirements and adheres to data privacy regulations. Additionally, consider the imbalance between fraud and non-fraud cases in the dataset and employ appropriate techniques such as oversampling, undersampling, or using algorithmic methods designed for imbalanced data.

Mohammad Mamun

One commonly used dataset for credit card fraud detection is the Credit Card Fraud Detection Dataset available on Kaggle, which contains transactions made by credit cards in September 2013 by European cardholders. This dataset encompasses transactions over a two-day period, including 492 frauds out of 284,807 transactions, making it imbalanced but reflective of real-world scenarios. Additionally, the IEEE-CIS Fraud Detection Dataset on Kaggle offers a more extensive set of real-world features for transactional data, suitable for advanced machine learning models. For cases where real-world data is limited or sensitive, synthetic datasets like the Credit Card Fraud Detection Synthetic Dataset on Kaggle provide an alternative. As with any dataset, it's crucial to understand its limitations, potential biases, and preprocessing requirements while adhering to proper citation and usage protocols.

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