Copperlane

Loan officers spend significant time chasing borrowers for documents like paystubs, bank statements, W-2s, and tax returns, with back-and-forth questions about start dates and employment history. Borrowers often abandon applications due to confusing forms, repeated data entry, and waiting for callbacks to get answers about loan terms or requirements. Operations teams must manually review documents for authenticity and flag issues like large deposits before files reach underwriting, and loan officers lack a single view of their pipeline across multiple tabs and systems.

Copperlane provides an AI assistant called Penny that collects documents, asks borrowers the right questions, and auto-fills application forms from uploaded documents like W-2s and bank statements. Forms adapt dynamically, showing only relevant fields based on loan type and borrower situation, such as hiding VA sections for conventional loans or self-employment questions when not applicable. The platform pre-verifies documents for authenticity and account holder match, flagging issues like large deposits before they reach underwriting. A loan officer dashboard shows the full pipeline with document status and flags per borrower. Penny also integrates into internal tools like Slack or Teams to answer questions and create tickets, and supports multilingual voice conversations with borrowers in 13 languages including English, Mandarin, and Spanish.