Abstract: A merchant's mobility data from their mobile device and their purchase history from a wholesale supplier may be used for underwriting a business loan. The mobility data may be analyzed into several descriptive statistics, which may characterize, in a sense, the person's behavior patterns. A merchant's purchase history from a wholesale supplier may be analyzed to estimate several business performance statistics. The estimated performance statistics and the mobility statistics, when combined, may generate an insightful and very accurate profile of a borrower. A machine learning system may use statistics derived from purchasing history as well as mobility information to accurately calculate a confidence score, which may reflect a loan applicant's likelihood of fully repaying a loan. The confidence score may be compared to a threshold value to determine whether to grant or deny a loan. The threshold value may be dynamically updated to meet a loan portfolio's financial objectives.