Suppose that you are on the fraud-prevention team at an online payment processor such as Stripe. When a transaction is initiated, the software systems that your team oversees will provide a score in the range 0 to 1 that represents the probability that the transaction is fraudulent. You have a considerable amount of possibly relevant data at your disposal to make the decision, including: Payment history associated with the card Payment history associated with the merchant Timestamp Name of cardholder Street address of cardholder ZIP code of cardholder City of cardholder State of cardholder IP address of device used to initiate transaction Device ID of mobile device used to initiate transaction You are also able to acquire third-party datasets, including: The Experian identity graph with associated credit data Public voting records Location data associated with the mobile device Select 3 of the bullet points above and answer the following questions: What are some of the possible benefits associated with using this kind of data for fraud prevention? What are some possible concerns associated with using this kind of data related to privacy, laws and regulations, or security? How might you mitigate the concerns you have identified? For your submission:. You may submit your responses either in a document or as a succinct video