P2P Lending is mostly anonymous and loans are unsecured. To make the risks of lending to a stranger acceptable for lenders, p2p lending services had to provide models for the lenders to judge the dimension of the risk of not getting paid back.
The initial estimation of the risk-level could not come from the platform itself as it had no track record and could not build a model that “calculated” the level of risk involved for the lender. The consistent consequence was that nearly all p2p lenders relied on established third party providers for credit history data and credit scores. Prosper for example showed Experian data on default levels to be expected depending on credit grade.
Over the time it became obvious that the actual default levels at Prosper were much higher than the expected default levels based on Experian data. We don’t actually need to argue here what led to this (be it financial development of the economy, be it that p2p lending attracted bad risks, be it a poor validation process), but the result was that since defaults were much higher than expected, lender ROIs were much lower than expected at the time of the investment.
And this is not Prosper specific. Several other p2p lending services show clear signs that default levels will (or have) surpassed the initially published percentages of defaults to be expected based on external data.
Boober failed due to default levels, on Smava levels are higher than the Schufa percentages fore-casted, same is likely for Auxmoney defaults which will be higher then Schufa and Arvato Infoscore data suggested. The one exception from the rule is Zopa UK, which successfully manages to keep defaults low, as CEO Giles Andrews rightly points out.