In February 2016, Lord Turner (former Chairman of the Financial Services Authority) in an interview argued that “the losses on peer-to-peer lending which will emerge within the next five to 10 years will make the worst banks look like absolute lending geniuses”. His argument is based on the fact that the crowds underperform because (1) they have limited budget and resources including expertise and capabilities to perform due diligence as well as (2) “limited” incentives due to low stake holding to expend effort in screening borrowers. We try to assess Mr. Turner’s statement in our recent working paper (Mohammadi and Shafi, 2016): we ask whether peer-to-peer lenders are able to assess the risks of loans correctly. To do so, we benchmark the lending performance of crowd to institutional investors in these markets.
Background of Lending-based Crowdfunding. Crowdfunding markets are growing rapidly; an industry report estimated that crowdfunding raise $34 billion in 2015 (Massolution Report, 2015). Among different models, lending-based crowdfunding – also known as peer-to-peer lending – had the largest global market share of about $25 billion in 2015. Within the lending-based crowdfunding, peer-to- business lending remains the largest model by volume in 2015 according to the latest report of Nesta (2016), which investigates the online alternative finance market of the UK. Peer-to-business lending (excluding real estate lending) supplied the equivalent of 13.9% of new bank loans to small businesses in the UK in 2015 (based on BBA’s 2014 baseline figure of £6.34 billion). Given the unprecedented growth of crowdfunding markets and their emerging potential for financing businesses as evidenced by preceding numbers, it remains unclear the extent to which individual investors (crowds) in these markets have the ability to select investment opportunities successfully.
Methodology. Empirical analysis of the opening question of this article is complicated since it requires finding suitable benchmark for evaluating ability of peer-to-peer lenders. For example, if we compare the loans offered by banks with loans available to the peer-to-peer lending platforms, we might be comparing oranges with apples because borrowers that apply for bank loans might systematically differ from borrowers in peer-to-peer lending platforms. Hence, the result that we observe might not reflect the ability of peer-to-peer lenders relative to banks but the unobserved differences between borrowers. Therefore, comparing peer-to-peer lending with banks can raise the issue of selection bias (for example, high-quality borrowers choose banks and low-quality borrowers choose peer-to-peer platforms).
To avoid selection bias, we assess the ability of peer-to-peer lenders compared with institutional investors in screening borrowers in one market: the UK peer-to-business lending market of FundingCircle. in FundingCircle platforms loans are randomly assigned to institutional investors or crowds (random assignment removes selection bias). In addition, institutional investors are supposedly expert and sophisticated in screening loans as well as free of “limited” financial incentive faced by the crowds. Furthermore, institutional investors purchase entire loans (“whole loans”), instead of pieces of loans that appeal to the crowds with more limited budgets. Having this setting, we are able test the ability of peer-to-peer lenders in assessing the risks posed by borrowers.
Institutionalisation of Crowdfunding. The institutional demand – so-called “institutionalisation of crowdfunding” (Nesta, 2016) – has indeed marked a pivot point for the growth of peer-to-peer lending industry (Financial Times, 2013). The fraction of institutional investors such as hedge funds and pension companies, or funds investing on behalf of individuals in peer-to-peer platforms, has skyrocketed since the creation of “whole loan” programs, surpassing the share of individuals in the total loan volumes on platforms adopting this practice including market leaders such as LendingClub.com, Prosper.com, or FundingCircle.com. Figure 1 plots the growth of loan volume in British Pounds in Funding Circle for institutional investors vis-à-vis the crowds. While institutional investors entered Funding Circle in the 2nd quarter of 2014, the institutional investors loan volume surpasses the crowds in the 4th quarter of 2015.
Results. Our empirical analysis shows that crowds underperform institutions in screening borrowers, thereby asking for lower interest rates for very similar loans. The crowds relative to institutional investors demand 40 basis points lower in interest rate for very similar loans. While this effect might not seem large, this is equal to 10% of monthly average salary in the UK (The UK average salary in 2014 was £26,500) considering the average amount requested is £57,000. This also means in around 10,000 loans that the crowds financed prior to September 2015, they have lost £2.5 Million annually. Moreover, the underperformance gap of crowd compared with institutions widens with risky and small loans, suggesting that crowd lack the expertise to assess the risks or the incentive to expend resources to perform due diligence. Finally, even though crowd request lower interest rate compared with institutions, there is no evidence that loans funded by crowd fail more than institutions.
Mohammadi and Shafi, 2016, How Wise Are Crowd? A Comparative Study of Crowd and Institutions in Peer-to-Business Online Lending Markets (link: )
Massolution 2015, Crowdfunding Industry Report.
Nesta 2016, Pushing boundaries: the 2015 UK alternative finance industry report (link: )
Author: Kourosh Shafi
Kourosh is a visiting student at London Business School. He previously graduated with a PhD in Management, Economics and Industrial Engineering, Cum Laude from Politechnico di Milano, and holds a Master’s degree, Mechanical Engineering from Ecole polytechnique fédérale de Lausanne. He speaks fluently English, Persian, French and Italian.