Federal Trade Commission Holding Alternative Scoring Conference; WPF Speaking
Pam Dixon will be speaking at the Federal Trade Commission’s conference on Alternative Scoring on March 19, 2014, discussing consumer aspects of alternative scoring. Scoring is a data broker issue that few know about yet. This conference is among the first to look closely at scoring products and legal frameworks, and the impacts on consumers.
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, the kind of special offers that companies make to certain individuals (and those they don’t), and even whether the customer should speak to a high-ranking customer service agent at a company.
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. The panel will discuss questions such as:
- What are the current types of predictive scores available to companies and what scores can we expect data brokers to offer in the future?
- How are companies utilizing these predictive scores?
- How accurate are these scores and the underlying data used to create them?
- How can consumers benefit from the availability and use of these scores?
- What are the privacy concerns surrounding the use of predictive scoring?
- What legal protections currently exist for consumers regarding the use of predictive scoring, both in the United States and internationally?
- What consumer protections should be provided; for example, should consumers have access to these scores and the underlying data used to create them? Should some of these scores be considered eligibility determinations that should be scrutinized under the Fair Credit Reporting Act?