Collecting card debt can be made more productive and less costly by capturing signals cardholders send when the account is in collections, and incorporating that information into a dynamic scoring model. Two academics studying collection data from one of the largest U.S. credit card issuers have published a paper showing collection results using their dynamic valuation model compared to the static models currently available to the issuer. Static models rely on logistical regression analytics and use factors including outstanding balance, mortgage status, past payment history, and credit score ...