Many entities, such as merchants, advertisers, content providers, manufacturers, and more, are often greatly interested in finding out as much as they can about consumers. By learning more about consumers, these entities can often better target advertisements, offers, or other content to consumers, or better select consumers for receipt of specific content. As a result, these entities may try to obtain information on consumers as often as possible, and with as much detail included as possible. One such piece of information is transaction data associated with payment transactions involving a consumer. Such information may be useful for identifying a consumer's purchasing behavior and shopping trends.
However, consumers may be worried about the amount of information that advertisers and other such entities may possess about themselves, particularly when it comes to their shopping behavior. As a result, many regulations have been passed and/or adopted that may limit an entity's ability to gather and/or possess personally identifiable information associated with a particular consumer. Therefore, entities are now often in need for information about consumers that can provide valuable detail, while still maintaining a consumer's privacy as per regulations and requirements.
Thus, there is a need for a technical solution to provide behavioral scores for consumers based on transaction data while maintaining consumer privacy.