underwrite.io applies biologically inspired machine learning approaches to credit modeling. Working with data from conventional bureau or subprime bureaus like Clarity, FactorTrust, MicroBilt we can score applications using our proprietary MetaScore which correlates to loan default at a much higher rate than currently available algorithms. Unlike traditional models of underwriting which focus on only a handful of credit attributes from a major credit bureau; we combine the results of a consumer inquiry with hundreds of other attributes that allow you to accurately model risk for traditional borrowers and the unbanked at all levels of risk from deep subprime to A+. We accurately return a probability of default for your potential borrowers using only a small set of inputs, primarily name, address, SSN and email. Because we are using biologically based machine learning techniques applied to your own portfolio; we model the expertise of your underwriters and the past performance of your loans to return an automated decision typically in less than 5 seconds. If you have no portfolio data, we have models based upon large quantities of publicly available datasets covering everything from home mortgage and automobile to peer to peer lending and cash advance. Your organization can leverage the latest advanced in credit analytics without capital investment or build time.