Synthesizing user transactional data for de-identifying sensitive information

A method, comprising:

• at a computer system:
• identify transactional data of a plurality of users;
• cluster the plurality of users based on the transactional data, to form groups of users;
• generate synthesized transactional data for the users in at least one of the groups by:
• identifying a subset of the transactional data that corresponds to at least a portion of the users in the group,
• shuffling the transactional data in the subset across one or more of the users in the group, wherein the shuffling includes:
• constructing a pool of transactions from the subset of the transactional data,
• for one or more users in the group, sampling transactions from the pool where:
• a number of transactions sampled from the pool for the user matches the number of transactions in the subset of the transactional data that are associated with the user, or
• a number of transactions of a particular category sampled from the pool for the user in the group matches a number of transactions of the particular category in the subset of the transactional data that are associated with the user, and
• perturbing portions of the shuffled transactional data.

A system, comprising:

• a non-transitory memory storing instructions;
• and
• one or more processors in communication with the non-transitory memory that execute the instructions to:
• identify transactional data of a plurality of users;
• cluster the plurality of users based on the transactional data, to form groups of users;
• generate synthesized transactional data for the users in at least one of the groups by:
• identifying a subset of the transactional data that corresponds to at least a portion of the users in the group,
• shuffling the transactional data in the subset across one or more of the users in the group, wherein the shuffling includes:
• constructing a pool of transactions from the subset of the transactional data,
• for one or more users in the group, sampling transactions from the pool where:
• a number of transactions sampled from the pool for the user matches the number of transactions in the subset of the transactional data that are associated with the user, or
• a number of transactions of a particular category sampled from the pool for the user in the group matches a number of transactions of the particular category in the subset of the transactional data that are associated with the user, and
• perturbing portions of the shuffled transactional data.