This document discusses using a big data platform for real-time fraud detection through sequence mining. Hadoop is used to build a Markov chain model from transaction data to identify patterns. Storm then processes transactions in real-time, using the model to flag potentially fraudulent sequences. Redis is used as an input queue and to store the model and flagged transactions. The approach sequences transactions by customer to detect fraud patterns not found by analyzing individual transactions.