Barbados AI Fraud Detection Hackathon
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Helping Barbados
2 000 BBD
Completed (~1 year ago)
Classification
30 joined
27 active
Start
May 10, 25
Close
May 10, 25
Reveal
May 10, 25
About
You are provided with anonymized transaction data, including key attributes that can help distinguish between legitimate and suspicious activity. Your task will be to create a predictive model that can flag fraud as early as possible, minimizing false positives while catching as many fraudulent transactions as possible.
This dataset includes a sample of approximately 140,000 transactions that occurred between 15 November 2018 and 15 March 2019.
Files
Description
Files
Is an example of what your submission file should look like. The order of the rows does not matter, but the names of the TransactionId must be correct. The value in FraudResult will be 1 for is a Fraud and 0 for is not a fraud.
Transactions from 15 November 2018 to 13 February 2019, including whether or not each transaction is fraudulent. You will use this file to train your model.
Transactions from 13 February 2019 to 14 March 2019, not including whether or not each transaction is fraudulent. You will test your model on this file.
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