Many data brokers offer companies scores to predict trends and the behavior of their customers. Companies are using predictive scores for a variety of purposes, ranging from identity verification and fraud prevention to marketing and advertising.
For example, companies are using scores to predict the likelihood that a person has committed identity fraud; the likelihood that a certain transaction will result in fraud; the credit risk associated with certain mortgage loan applications; whether contacting a consumer by mail or phone will lead to successful debt collection; whether sending a catalog to a certain address will result in an in-store or online purchase; the likelihood that an individual is taking his or her medication; a person’s presence on the Internet and his or her influence over others; or whether a customer is pregnant, and if so, when the baby is due.
According to media reports, these scores are determining whether transactions trigger further scrutiny. Consumers are largely unaware of these scores, and have little to no access to the underlying data that comprises the scores. As a result, these predictive scores raise a variety of potential privacy concerns and questions.
