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Peer to peer lending research paper

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Peer-to-peer P2P lending enables individuals to obtain loans directly from other individuals, cutting out the financial institution as the middleman. Websites that facilitate P2P lending have greatly increased its adoption as an alternative method of financing. P2P lending websites connect borrowers directly to investors. Each website sets the rates and the terms and enables the transaction. Most sites have a wide range of interest rates based on the creditworthiness of the applicant.
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What is a peer to peer loan? What is p2p lending?

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What is a peer to peer loan? What is p2p lending? • LendingMemo

Can peer-to-peer lending P2P crowdfunding disintermediate and mitigate information frictions in lending such that choices and outcomes for at least some borrowers and investors are improved? I offer a framing of issues and survey the nascent literature on P2P. On the investor side, P2P disintermediates an asset class of consumer loans, and investors seem to capture some rents associated with the removal of the cost of that financial intermediation. Risk and portfolio choice questions linger prior to any inference. However, social connections require costly certification skin in the game to inform credit risk.
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Best Peer-to-Peer Lending

P2P lending works differently from the financing you may have received in the past. You are not borrowing from a financial institution but rather from an individual or group of individuals who are willing to loan money to qualified applicants. P2P lending websites connect borrowers directly to investors , as these lenders are called. Each website sets the rates and the terms sometimes with investor input and enables the transaction.
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Contrary to the flat-world hypothesis, we find that peer-to-peer lending networks are moving away from flatness. Furthermore, decreasing flatness is strongly associated with multiple variables: relatively stable patterns in the difference in the per capita GDP between borrowing and lending nations, ongoing migration flows from borrowing to lending nations worldwide, and the existence of a tie as a historic colonial. Our regression analysis also indicates a spatial preference in lending for geographically proximal borrowers. To estimate the robustness for these patterns for future changes, we construct a network of borrower and lending nations based on the observed data. Then, to perturb the network, we stochastically simulate policy and event shocks e.
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