The Role of ‘Expert Reviewers’ in Private Capital Markets

Investors rely on information produced by intermediaries such as research analysts and auditors, or other legal sources such as company regulatory filings to obtain knowledge about offerings in public markets. Private market participants, however, do not have access to such information. We investigate whether a market for voluntary ‘experts’ can potentially fill this void.

We exploit the introduction of the market for initial coin offerings (ICOs), a popular but unregulated mechanism for capital formation that is often targeted at retail investors. ICOs are a form of early-stage crowdfunding that, according to their issuers, did not fall under the purview of securities regulation. Thus, issuers were not required to follow disclosure or accounting rules. In order to overcome information frictions, the ICO market uses voluntary experts to provide an assessment of the offering.  In many aspects, these experts provide reviews comparable to those in crowdfunding platforms and on financial chat websites. Our paper examines many interesting questions about the role of voluntary reviewers in reducing information asymmetry in unregulated capital markets.  

It is relatively easy to become a voluntary expert on the third-party ICO rating platform ICObench. Experts assign a numerical rating to each of three characteristics of an offering: team, vision, and product. They may also provide a textual review of the offering. To better understand the information in these reviews, we use machine learning to categorize the content of the textual review and then test if narrative content affects ICO outcomes after controlling for the numerical rating. Since the activities of reviewers are not subject to regulatory scrutiny, we also analyze if conflicts of interest affect a reviewer’s textual content, and whether market participants are able to recognize these conflicts.

We find that reviewers are motivated to provide textual reviews in order to increase their reputation. Using the Stanford Natural Language Processing to determine the sentiment of a review, we find that experts’ reviews become more balanced over time as the content becomes less positive. Moreover, the textual content of reviews has an impact on the success of the offering. The more positive a review and the higher consensus among reviewers, the greater the amount of proceeds raised. Thus, textual content provides investors with information that may be used in an investment decision.

We acknowledge, however, that voluntary expert reviewers may produce reviews for reasons other than information production. We show that experts that are more likely to have conflicts of interest produce reviews that are more positive, consistent with the notion that conflicted reviewers may hype an offering. However, investors seem to recognize these conflicts of interest. We find that the sentiment of reviews of experts identified as being more conflicted does not affect the proceeds raised. In contrast, proceeds are increasing in the positive sentiment of reviews for reviewers with low (or no) conflicts of interest. This suggests that investors discount the more positive (and potentially less informative) reviews of highly conflicted experts and focus on those that do not have a prior relationship with the ICO team.

Although the ICO market was short-lived, our results suggest that some frictions in unregulated markets can be mitigated by self-oversight. Given the increased role of private capital raising, our results should be of interest to policy makers and market participants in formulating ways to overcome frictions in the private market.

Reena Aggarwal is the Robert E. McDonough Professor of Finance and Director of the Georgetown University Center for Financial Markets and Policy.

Kathleen Hanley holds the Bolton-Perella Chair and is Director of the Center for Financial Services, College of Business and Economics, Lehigh University.

Xiaofei Zhao is an Associate Professor of Finance at Georgetown University.