Peer to peer (P2P) lending is a form of crowdfunding where anybody can lend money to a private person in an internet-based marketplace lending platform. Peer-to- peer lending is a part of the sharing economy where online based platform connects the end users of a service. P2P lending phenomenon can be compared to for example what Uber has done in the taxi services or Airbnb in the hotel industry – an user-friendly and cost-effective online service that connects the demand with supply quicker and easier than the traditional intermediaries. In the finance industry this development has led to peer to peer lending where people and companies lend money to each other in accordance with mutually agreed loan terms without a bank as a middleman.
Peer to peer investing and lending is based on centuries-old practices - those who have some extra money lend for those who are short of supply. Despite the long history, the digitalisation of society has enabled borrowers and lenders to find each other more efficiently online making investing in P2P loans efficiently on a larger scale: a task that has previously been an exclusive right of banks and financial companies. In peer-to-peer lending the main difference is that a borrower does not borrow money from a bank, but directly from other individuals and organizations. Simultaneously, a lender does not deposit his spare money to his bank account, so that the bank can lend the same money forward, but directly to the borrowers.
The credit risk is managed by ensuring the solvency of a borrower. To get a loan application accepted, the applicant can’t have a payment default remark. The borrower ability to repay his loan is also assessed by our statistical credit risk model which includes multiple variables. The model classifies the borrower into five different credit class ranging from one to five stars. Higher credit rating reflects lower risk to investors. The Microsoft Azure Machine Learning software is used to analyse the creditworthiness of the borrower and the credit risk policy and its prediction accuracy is continuously developed by analysing the prediction power of each variable and adding new ones. On the statistics page you can monitor the prediction accuracy of our model for each risk class. You can also find more specific borrower information on the borrower page.
We offer a safe, technologically advanced and large online marketplace for peer-to-peer lending. An investor can diversify his investment portfolio geographically into Danish, German, Swedish, Polish and Finnish peer to peer loans. Fellow Finance manages all the administration between parties involved.
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