Credit Card Fraud Detection

•The company want to develop a machine learning model to detect fraudulent transactions based on the historical transactional data of customers with a pool of merchants.

• They want to analyze the business impact of these fraudulent transactions and recommend the optimal ways that the bank can adopt to mitigate the fraud risks and the benefit of the model using cost benefit analysis.

• Build the most accurate model to detect the maximum credit card fraud transaction so as to reduce the fraud transaction.
• Identifying the driver variables and understand their significance which are strong indicators of fraud transaction.
• Identify the outliers, if any, in the dataset and justify the same
• Check and fix the imbalance and skewness in the data.
• Consider both technical and business aspects while building the model.
• Summarizing the fraud detection predictions by using evaluation metrics like accuracy, sensitivity, specificity and precision. And also performing the cost benefit analysis check business impact of the fraud transactions.

Detailed Video Presentation Link : https://youtu.be/CzwvOFdiyUs