Collective intelligence applied to credit implies that a group makes more intelligent investment decisions than isolated individuals. Although such an assumption remains debatable, platform economics is based on the simple idea that the group is a reliable risk assessment (source of especially concerning restaurants, hotels, operators).
In crowd-lending, the question of the role of the group is even more relevant due to the involvement of an expert, the borrower's accountant, who holds important information concerning their client's creditworthiness. Crowding implies new forms of direct intermediation between crowds and project leaders. A number of studies have looked into such a model through the principle of co-dependence between the crowd-funding platform, crowd and project creator. This model has found real expression via the platforms that have taken up the collective intelligence challenge. The two co-authors focus on one such platform.
The platform studied in the article, "PeerUnion", has developed a collective intelligence model based on the figure of the chartered accountant. As such, a partnership was set up with the Order of Chartered Accountants. However, this partnership was dropped after a year and a half. Antoine Souchaud and Héloïse Berkowitz look into the causes of this failure and propose a model of collective intelligence engineering by drawing on co-dependence and organizational theory cases and literature. Their study was carried out for over three years and based on a wide range of material from interviews with a variety of people involved and discussions between crowds and project leaders on platform forums, i.e. where collective intelligence is directly expressed.
The two co-authors demonstrate that if the partnership logic has failed between the platform and the order of chartered accountants, it is due to the introduction of a new actor in the business model, the chartered accountant, without respecting the principle of co-dependence between stakeholders.
In the revised model suggested by the two researchers, collective intelligence applied to crowd-lending has a variety of functions both before and after the fundraising, provided that there is co-dependence between the platform, the crowd, the project leaders and the accountants. Such co-dependence results in shared decision-making power between the various parties involved and the mechanisms for exclusion from the crowding process in place. Beforehand, and thanks to the role of the chartered accountant, crowd intelligence is used to understand and asses the project and the business model and to anticipate risk and therefore make a decision concerning investment (by blocking or authorising a collection). After, collective intelligence allows the risk to be shared and also to build a network of contributors.