Traditional lenders, i.e. banks, usually find it difficult to match the agility and granular understanding that P2P Lending players have. Banks’ credit evaluation and origination platforms are often industrial-age processes with a large quantum of human intervention. The operational and statistical models are based on predictability of borrowers’ behaviors across a large enough population set. While most practitioners in consumer and business lending in banks fully appreciate the rapidity with which change is happening, legacy investments in technology and the historical “bank-hall” mindset make transformation a challenge. New models & methods based on the new technology solution – Machine Learning will help the lenders better assess the Credit Risk assessment, which can provide more accurate information and hence protect the investors’ interest. The emerging knowledge will boost the P2P lenders to be capable of offering better service where banks are not offering.
Peer-to-peer (P2P) lending represents a growing market that has gained traction with investors. P2P platforms create a market place for investors to lend money directly to borrowers. In return, investors receive an attractive yield – provided the borrower does not default.
This article lists 5 reasons to consider P2P lending. Firstly, traditional saving accounts offer low interest rates, causing the value of money to be easily eroded by inflation. Secondly, P2P generally offers attractive returns that beat inflation. Thirdly, P2P provides investors with the opportunity to diversify their investments. Fourthly, P2P platforms are becoming increasingly accessible to investors. Lastly, P2P helps support the economy by providing startups and SMEs with adequate working capital to grow their businesses.