HKUST Business Review

3. Engaging CRAs to Ensure Accurate Assessments On the other hand, to ensure accurate assessments, firms should also be sure to maintain open and transparent communication with CRAs. They should engage proactively with S&P analysts during site visits and meetings; share accurate and comprehensive information about financial performance, forecasts, and strategic plans; and promptly address any concerns raised by S&P to prevent negative rating actions that may raise red flags among investors. Takeaways for Regulators Finally, our study offers important implications for capital market regulators tasked with detecting fraud, such as the SEC in the U.S. or the Securities and Futures Commissions (SFC) in Hong Kong. 1. Leveraging CRA’s Data for Fraud Detection First, regulators should consider incorporating data from CRAs with access to private information into their fraud detection frameworks. Beyond simply viewing published ratings, regulators can collaborate with these agencies to glean nuanced insight into potential cases of fraud without compromising confidentiality. For example, governments can establish formal channels for CRAs to share anonymized or aggregated data on rating actions, whether through voluntary reporting mechanisms or as part of existing regulatory oversight frameworks. They can also encourage CRAs to disclose the methodologies they use to assess fraud-related risks, again without compromising specific firms’ proprietary information. 2. Leveling Informational Playing Field In addition, while our study shows that CRAs that aren’t paid by the firms they rate are less able to detect fraud, they also have fewer conflicts of interest and are thus less likely to withhold information about accounting fraud when they do discover it. As such, regulators could explore ways to enhance these CRAs’ access to relevant information or incentivize their development of alternative fraud detection methodologies. Policies that level the informational playing field, such as requiring firms to disclose certain non-public information to all CRAs under controlled conditions, may help boost fraud detection, as can governmental investment into advancing the data analytics tools these agencies use to detect fraud. Looking Ahead: The Future of Fraud Detection Today, negative rating actions from CRAs with access to companies’ private information can provide valuable early insight into potential fraud—and going forward, new technologies and regulatory frameworks will likely further boost their detection capabilities. On the regulatory front, we’ve already seen that reforms passed in response to the 2008 Financial Crisis improved S&P’s fraud detection performance, and greater collaboration with and support of CRAs may strengthen their performance even more. And on the technical front, advances in data analytics and machine learning could further enhance predictive capabilities. For instance, integrating CRA data with AI-driven fraud detection models could enable a powerful hybrid approach, combining human insights with algorithmic precision. At the end of the day, we’re unlikely to ever fully eliminate fraud. After all, as regulators, internal managers, and external analysts improve their detection techniques, so too will fraudsters inevitably come up with new ways to evade notice. But our research demonstrates that despite the potential for conflicts of interest, CRAs that are paid by the companies they rate actually detect fraud sooner and more accurately than other analysts, highlighting their potential to help investors, firms, and regulators alike more effectively identify and address fraud. This article draws on the research paper “The Usefulness of Credit Ratings for Accounting Fraud Prediction,” authored by Allen Huang, Pepa KRAFT, and Wang Shiheng. Allen Huang s a professor of accounting and the head of the accounting department at HKUST, focusing on issues related to natural language processing in financial text, earnings management, financial analysis, accounting fraud, and securities litigation. Wang Shiheng is an associate professor of accounting at HKUST, focusing on international accounting, financial reporting, contracting, and market efficiency. 43 HKUST Business Review