Peer-to-peer (P2P) lending platforms facilitate digital, online loans by matching lenders with borrowers. Instead of a bank acting as the lender, the platform connects a multitude of lenders with numerous borrowers, such as consumers or small businesses. The lenders who could be private individuals seeking to invest their money, rather than licensed creditor providers. For the process to work, P2P platforms naturally need to process a lot of data, and this is where big data holds considerable potential for P2P lending. Big data, AI, and machine learning could further accelerate P2P lending, giving it a truly disruptive power and transforming the lending environment for borrowers and lenders. With this in mind, here are four main ways big data is already impacting P2P lending. 1. Complete, in-depth borrower profilesP2P loans are by nature unsecured; hence the importance of a comprehensive approval process. Banks and other traditional lenders, given their bureaucratic approach, may be more likely to exclude certain types of borrowers, including “safe” ones who are actually likely to repay. This offers an opportunity for non-traditional lenders, especially investors who lend through P2P platforms. Big data enables P2P lenders or investors to become more specific and local when assessing borrowers. Depending ...
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