Barriers to entry

Despite earlier attempts to improve market access for new entrants and to promote competition amongst CRAs, the US GAO concluded in its “Action Needed to Improve Rating Agency Registration Program and Performance-Related Disclosures 2010” report that the barriers to entry for structured products in particular remained especially high.⁹⁹ Dittrich¹⁰⁰ and Haar¹⁰¹ have attributed the lack of competition among CRAs to ‘network effects’, the underlying ‘lock-in effects’, and ‘lack of product differentiation’

opportunities between firms.

Each of these is discussed in greater detail below:

▪ Network Effects:

Because CRA ratings are ostensibly a measure of relative risk, both direct and indirect network effects¹⁰² are acutely relevant. For an elementary example that helps to visualize the importance of economies of scale and power of direct network effects, one

99 US Gov-GAO-b, Action Needed to Improve Rating Agency Registration Program and Performance-Related Disclosures, U.S. Government Accountability Office, at 96-97, Sept. 2010, available at http://www.gao.gov/assets/310/309849.pdf.

100 Dittrich, Fabian, The Credit Rating Industry: Competition and Regulation, Note (4 June 2007) at 73.

101 Brigitte Haar, Nachhaltige Ratingqualität durch Gewinnabschöpfung? - Zur Regulierung und ihrerImplementierung im Ratingsektor./ Transl.: Sustainable quality ratings by profit-skimming? For the regulation and its implementation in the rating industry, 21 ZBB (3) 177, 179 (2009).

102 See e.g., International Center for Monetary and Banking Studies (ICMB), The Fundamental Principle of Financial Regulation: Geneva Reports on the World Economy 11(Geneva , Switzerland, Jan., 2009) at 50 (CRAs have a “franchise value or network value…”).

need only consider the telephone. The utility of the very first telephone was essentially zero; its network worth was zero since with no-one to call, the instrument held no value for any potential consumer. With the introduction of a second handset, the utility of the first telephone would surely increase exponentially. This trend of an increase in marginal utility would continue relatively unabated with the addition of each new handset to the network. Each additional unit increases member utility and strengthens the entire network, a feature that McKnight and Bailey referred to as a “network externality”.¹⁰³

The availability of numerous ratings (and by default the generation of a large volume of securities to be rated), allows for greater breadth which enhances a rating system that evaluates risk on a relative basis. Dittrich¹⁰⁴ notes that the ability to compare a large volume of different debt securities is valued by investors, and hence, the theory is that more ratings allow for better (i.e. “higher quality”) ratings to be issued. Alongside direct network effects, Katz and Shapiro identify two other forms of positive consumption externalities; namely indirect network effects and, in the case of durable goods, the availability of and experience in a post-purchase servicing system.¹⁰⁵

Regarding indirect network effects, Katz and Shapiro provide an example of a PC buyer having to consider the number of other similar hardware units that have been sold as this would have a direct influence on the amount and variety of software supplied and would be available for him to buy. In addition, Katz and Shapiro developed a simple, static model of oligopoly to analyse markets where consumption externalities are present.¹⁰⁶ They find that consumers are willing to pay more for a firm's product if their expectation

103 Lee W. McKnight & Joseph P. Bailey, Internet Economics: When Constituencies Collide in

Cyberspace, 1 IEEE, INTERNET ECON. (6), at 31 n.3 (1997)(“[A] network externality is the benefit gained by incumbent users of a group when an additional user joins the group”).

104 Dittrich, Fabian, The Credit Rating Industry: Competition and Regulation, Note, passim, (4 June 2007)

105 Michael L. Katz & Carl C. Shapiro, Network Externalities, Competition and Compatibility, 75 AM. ECON.REV. (3), 424, 424 (1985).

106 Id., 75 AM.ECON.REV. (3), 426-432 (1985).

leads them to believe that the firm is dominant in its market. By acting on this perception, the consumers ensure that the perceived dominant player does become dominant.

Moreover, CRAs in general - and NRSROs in particular - have benefitted from indirect network effects which can be observed in the expedited growth of the ancillary services businesses. Parallels can be drawn to the legal requirements favouring NRSROs as the NRSRO status served to elevate the designated CRAs to a position of perceived market domination by consumers, thereby resulting in consumers choosing them over non-NRSRO firms as well as more recently accredited non-NRSROs.

In addition, Veljanovski makes mention of “induced (i.e. endogenous) network effects”¹⁰⁷ by which a network participant incentivises existing and potential network users of the network by offering lower transaction rates for interactions within the network (i.e. on-net) than with those on a rival network. Veljanovki finds that a network externality characterised by availability of large volume of cheap on-net calls increases switching costs which in turn are advantageous to the larger network. The final effect is that this creates a lock-in effect for consumers in the network.

For the home video game industry with the two dominant competitors Nintendo and Sega, limits to the advantages of a larger network were found. ¹⁰⁸ Unlike CRAs which rely on similar but differentiated rating methodologies, the two firms in that study competed with entirely incompatible product technologies. So whereas an investor might be willing to use ratings from different CRAs interchangeably, a video game consumer’s post-purchase product and service options would be restricted once his post-purchase is concluded.

The study also examined the impact of network effects as determined by network size (i.e.

measured by customer base) and network strength (i.e. measured by the marginal impact

107 Cento Veljanovski, Network Effects and Multi-Sided Markets 6, SSRN (2007), available at http://ssrn.com/abstract=1003447.

108 Venkatesh Shankar & Barry L. Bayus 23-27, Network Effects and Competition, 24 STRATEGIC MGMT J., 375-384 (2002).

of a unit increase in network size on demand). An asymmetric relationship which exists between network size and network strength, was identified.

Despite having a larger customer base than Nintendo, Sega’s network strength was found to be lower. The authors proposed this as a possible explanation for Nintendo, despite its smaller network, being able to overtake the sales of its larger network competitor. These findings seem to suggest that by focusing on developing their network strength, smaller CRAs could similarly increase their market share and offer the Big Three greater competition. The findings also appear to indicate that a threshold is eventually reached where the marginal utility of each new additional handset becomes negligible. In fact, it could possibly even become negative, for instance where the additional marginal transaction costs exceed the marginal benefit from each additional handset (i.e.

diminishing marginal returns); where each additional handset slows down or depreciates the network in some form. It can then be argued that three large NRSROs might indeed be this threshold, and recognizing additional large NRSROs might actually entail introducing negative marginal utility. This rationale might explain the failure of the other seven NRSROs to take significant market share away from the Big Three.

▪ Lock-in Effects:

Lock-in effects refer to “the cost of switching to a different service”,¹⁰⁹ i.e. the cost that consumers would incur when substituting one CRA for another. Hadfield et al., are of the view that the attributes of a credence good are discovered, if at all, a significant period of time after consumption.¹¹⁰ The cost of making an ex-post determination can also be significant. For issuers, the cost of switching is considered significant because of the reputational value in ratings, especially if the switch is away from either Moody’s or S&P.

109 OZ SHY, THE ECONOMICS OF NETWORK INDUSTRIES 4(Cambridge Univ. Press, 2001).

110 Gillian K. Hadfield, Robert Howse & Michael J. Trebilcock, Information-Based Principles for Rethinking Consumer Protection Policy, 21 J.CONSUMER POLICY (2) 131, 142n .17 (1998).

Such a move is almost certain to arouse suspicions of rate-shopping (i.e. avoiding close scrutiny generally by selecting an agency of lesser reputation, and by assumption, lesser capability) by investors.¹¹¹ This is more-so since Moody’s and S&P are established joint market leaders, both in terms of size and quality of service. A.M. Best conceivably is a beneficiary of the same advantage for insurance company ratings where they are the recognized industry leader.

▪ Product Differentiation:

The lack of product differentiation opportunities is a further barrier of entry for new entrants into the CRA industry. Investors anecdotally want high quality ratings; ratings that are accurate, timely and efficient to use:¹¹² Dittrich¹¹³ and Haar¹¹⁴ both note that specialising in either good risk or bad risk is not an option for CRAs. The nature of the credit ratings as a product means that there simply isn’t a viable market for a CRA that would aim to provide lower quality ratings.

Accepting, as argued by both Dittrich and Haar, that no market for lower quality ratings exists, new entrants are thus restricted to competing either within specific sectors (e.g. A.M. Best in covering insurance companies, and Morningstar (f.k.a. Realpoint) in

111 Brigitte Haar, Nachhaltige Ratingqualität durch Gewinnabschöpfung? - Zur Regulierung und ihrer Implementierung im Ratingsektor, 21 ZBB (3) 177, 179 (2009) (discusses how switching from a Big Three CRA creates a ‘lock-in effect’ for issuers). But see, Efraim Benmelech & Jennifer L. Dlugosz, The Credit Rating Crisis 27 (NBER,May 15, 2010) (find that tranches rated solely by one of the Big Three (in this instance, S&P, who have a leading reputation and are considered among the most able among CRAs, were most likely to be downgraded by January 2008).

112 Jonathan R. Macey, The Politicization of American Corporate Governance, 1VA L.&BUS.REV.10, 20 (CRA can cost-effectively monitor issuers).

113 Dittrich, Fabian, The Credit Rating Industry: Competition and Regulation, Note, passim, (4 June 2007) at 93.

114 Brigitte Haar, Nachhaltige Ratingqualität durch Gewinnabschöpfung? - Zur Regulierung und ihrer Implementierung im Ratingsektor, 21 ZBB (3) 177, 179 (2009).

covering asset backed securities), or within specific geographic regions (e.g. the Japan Credit Rating Agency).