This paper investigates whether language and associated message framing (low-cost signal) can provide a solution to the risks generated by asymmetric information in P2P lending, drawing on the signalling and message-framing theories. First, it examines the extent to which message framing is associated with funding outcomes in the context of P2P lending; second, it investigates whether positive message framing reinforces the positive impact of credit ratings (high-cost signal) on funding outcomes. Our analysis is conducted on a dataset of 33,028 listings of potential borrowers from a Chinese P2P lending platform using the Heckman selection models. We find that the use of positively framed messages is positively associated with positive funding outcomes and enhances the positive impact of the credit ratings on funding outcomes. Our results contribute to the literature on the effectiveness of low-cost signals in of Internet-based interactions while highlighting complementarities between different types of signals in P2P lending.