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The Impact of Risk Management in Credit Rating Agencies

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The Impact of Risk Management in Credit Rating Agencies risks Article The Impact of Risk Management in Credit Rating Agencies A. Seetharaman 1,*, Vikas Kumar Sahu 1, A. S. Saravanan 2, John Rudolph Raj 3 and Indu Niranjan 1 1 SP Jain School of Global Management, 10, Hyderabad Road, Singapore 119579, Singapore; [email protected] (V.K.S.); [email protected] (I.N.) 2 School of Communication, Taylors University, 57500 Petaling Jaya, Malaysia; [email protected] 3 Faculty of Management, Multimedia University, 63000 Cyberjaya, Malaysia; [email protected] * Correspondence: [email protected]; Tel.: +65-9770-5672 Academic Editor: Mogens Steffensen Received: 19 February 2017; Accepted: 2 August 2017; Published: 21 September 2017 Abstract: An empirical study was conducted to determine the impact of different types of risk on the performance management of credit rating agencies (CRAs). The different types of risks were classified as operational, market, business, financial, and credit. All these five variables were analysed to ascertain their impact on the performance of CRAs. In addition, apart from identifying the significant variables, the study focused on setting out a structured framework for future research. The five independent variables were tested statistically using structural equation modelling (SEM). The results indicated that market risk, financial risk, and credit risk have a significant impact on the performance of CRAs, whereas operational risk and business risk, though important, do not have a significant influence. This finding has a significant implication for the examination and inter-firm evaluation of CRAs. Keywords: credit rating financial risk; credit risk; business risk; operational risk; market risk 1. Introduction Since 1909, when John Moody first began to provide ratings for a handful of railroad companies, management has been concerned with firms’ credit ratings (Sylla 2002). A significant number of corporations with public debt now have ratings, as do many firms without public debt. Some firms have explicitly targeted a rating, while others have expressed their commitment to maintaining a certain threshold—for example, investment grade (Kisgen 2006). To achieve or maintain their targeted ratings, some companies have changed their capital structures directly by issuing equity or buying back debt; others have attempted to strengthen their balance sheets through actions such as asset sales or dividend cuts (Kisgen 2007). Many believe that the financial crisis in the United States in 2008 and the recent European Union crisis were avoidable and were caused by widespread failures in financial regulation. Thus, policymakers and regulators worldwide are now confronting the formidable challenge of restoring confidence in markets and formulating long-term responses to the crisis. CRAs played a significant role in the financial crisis—even with so much information, they could not predict the fall of big financial institutions (Voorhees 2012). Investors primarily focused on the ratings that CRAs assigned to exotic financial instruments, such as asset-backed securities, collateralized debt obligations, credit default swaps, and structured investment vehicles, which shocked the financial market. Corporate bonds and securities with the highest ratings of AAA/Aaa defaulted or lost value at an alarming rate; the result was a loss of investor confidence in the value of the AAA/Aaa rating. The financial media questioned these CRAs’ competency and expertise regarding their rating mechanism used in assessing and evaluating various financial institutions’ instruments and their economic viability in the financial markets (White 2010). Risks 2017, 5, 52; doi:10.3390/risks5040052 www.mdpi.com/journal/risks Risks 2017, 5, 52 2 of 16 Risks 2017questioned, 5, 52 these CRAs’ competency and expertise regarding their rating mechanism used in2 of 16 assessing and evaluating various financial institutions’ instruments and their economic viability in the financial markets (White 2010). TheThe structure structure of thisof this article article includes includes aa detaileddetailed analysis analysis of of the the literature literature review, review, which which is is summarizedsummarized in a in tabular a tabular format format inin Table 11,, with with a aclear clear emphasis emphasis on the on research the research trajectory trajectory that this that this articlearticle will follow, follow, indicating indicating the theresearch research gap iden gaptified identified in the literature in the literature review. The review. research The model research modelis isdepicted depicted in Figure in Figure 1, with1, with the five the fiveindependent independent variables variables that are that the arefocus the of focusthis study of this and study their and their impactimpact on on the the performance performance management management of ofCRAs. CRAs. This This model model will will then then be captured be captured in the in design the design and formulation of nine hypotheses, followed by a summary of the demographic characteristics of and formulation of nine hypotheses, followed by a summary of the demographic characteristics of the the respondents. The empirical findings generated with the use of partial least squares SEM will respondents. The empirical findings generated with the use of partial least squares SEM will further further reinforce and provide statistical reasoning and mathematical robustness to the research reinforcemodel. and provide statistical reasoning and mathematical robustness to the research model. Figure 1. The Research Model. Figure 1. The Research Model. 2. Literature Review 2. Literature Review In the fallout from the financial crisis of 2008–2009, which plagued the United States’ economy, Ina debate the fallout arose fromregarding the financialthe culpability crisis of of CRAs 2008–2009, in creating which or contributing plagued the to Unitedthe crisis. States’ Several economy, years a debatelater, arose their regarding performance the and culpability reliability of are CRAs still bein in creatingg called into or contributing question. Our to research the crisis. emphasis Several and years later,focus their are performance intended to and strengthen reliability the integrity are still and being im calledprove the into transparency question. Our of credit research ratings. emphasis As part and focusof are our intended research, to we strengthen will explore the the integrity possible and opti improveons for CRAs’ the transparency rating performance of credit by ratings. evaluating As part various independent variables. The independent variables mainly represent the type of risk involved of our research, we will explore the possible options for CRAs’ rating performance by evaluating in the rating and measure how the ratings help CRAs to develop and grow. various independent variables. The independent variables mainly represent the type of risk involved Doumpos and Zopounidis (2011) concluded that there was the potential for an outranking, in themulti-criteria, rating and measure decision-aiding how the approach ratings for help credit CRAs rating to develop that would and further grow. enhance the quality of Doumposcredit rating. and They Zopounidis thoroughly( 2011examined) concluded the usage that of the there accounting was the ratio potential as a variable for an to outranking,support multi-criteria,this analytical decision-aiding approach. In similar approach research for creditKhalil, ratingMartel, thatand Jutras would (Khalil further et al. enhance 2007) claimed the quality that of creditcredit rating. risk They was a thoroughly default function examined of the reimbursem the usageent of capacity the accounting of the borrower ratio as (risk a variable of default) to and support this analyticalthe risk type approach. was mainly In similarcategorised research into the Khalil, risk of Martel, default andand Jutrasthe credit (Khalil risk. et al. 2007) claimed that credit riskChan, was aFaff, default Hill, functionand Scheule of the(Chan reimbursement et al. 2011) used capacity the core of empirical the borrower predictions (risk of the default) Boot and the riskmodel type to was confirm mainly that categorisedthe prediction into of thecertain risk credit of default rating andevents the is credit likely risk.to be more informative than others, and that CreditWatch procedures are an important driver of such differences and Chan, Faff, Hill, and Scheule (Chan et al. 2011) used the core empirical predictions of the Boot provide an information advantage to investors. model to confirm that the prediction of certain credit rating events is likely to be more informative Kisgen (2009) suggests that once a firm is downgraded, a firm is more likely to reduce leverage, than others,in order and to attain that a CreditWatch previous rating procedures target. These are effects an important are shown driver to be of significant such differences at the investment and provide an informationgrade cutoff, advantage and also important to investors. for firms which see downgrades in their commercial paper ratings, Kisgenboth of( 2009which) suggestsare consistent that oncewith the a firm significance is downgraded, of regulations. a firm Rating is more upgrades likely to usually reduce do leverage, not in orderaffect to the attain subsequent a previous capital rating structure target. activity, These effectssuggesting are that shown firms to target be significant minimum at rating the investment levels gradeand cutoff, lowered and leverage also important after downgrades for
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