This paper discusses how the all-or-nothing model can disincentivize crowd investors to perform due diligence over the fraud or failure risks of a crowdfunding campaign. Specifically, the major upside of this model is that a project cannot be funded without a critical mass investing. If enough individuals in this critical mass of crowd investors perform their due diligence to check whether projects will become successful, then the model functions correctly; instead, this paper argues that this model incentivizes the crowd to produce noisy information that cannot be relied upon. In the all-or-nothing model, sequential investments encourage rational investors to not perform their due diligence because they relied on the self-interest of prior investors to perform their own due diligence while non-fully rational investors may rely on the belief that prior investors have better information than they might gather. Allowing campaigns to be overfunded can exacerbate some of the all-or-nothing model characteristics. This paper concludes by discussing how the platforms, campaign creators, and crowd investors can be incentivized to better filter projects - in order to assure that crowdfunding fulfills its potential.
Garry A. Gabison,
The Incentive Problems with the All-or-Nothing Crowdfunding Model,
12 Hastings Bus. L.J. 489
Available at: https://repository.uchastings.edu/hastings_business_law_journal/vol12/iss3/3