The problem faced by the payment service provider company was the high volume of daily transactions (more than half a million) and the need to identify and block fraudulent transactions reported by card users. The challenge was that the proportion of fraudulent transactions was very low (0.004%), making it difficult to create a generalized solution. The requirement was to develop a predictive model that could quickly identify and block fraudulent transactions in real time without compromising the user experience, considering the low occurrence of fraudulent activities.

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