Deep Credit Analytics Lab
Traditional credit rating and scoring methods used by credit agencies are no longer sufficient to meet the evolving demands of credit analysis in the digital era. Credit rating agencies have faced increasing scrutiny since the financial crisis. The primary criticisms focus on the methods used to evaluate credit risk, the absence of accountability, and conflicts of interest. Despite these shortcomings, credit ratings are essential for the efficient operation of contemporary financial markets. Incorrect ratings can result in severe negative impacts, potentially causing widespread disruptions in different economic sectors.
The Credit Research Initiative (CRI), founded in 2009, offers a solution to these challenges. As a non-profit undertaking, CRI provides credit risk measures for exchange-listed firms worldwide. By pioneering “public good” credit risk measures, CRI is dedicated to advancing big data analytics and delivering directly useful credit intelligence to both academic and professional communities. This innovative approach ensures more accurate and responsive credit evaluations, better suited to the complexities of today’s financial landscape.
CRI Product Suite
- NUS-CRI Probability of Default (NUS-CRI PD) is a forward-looking point-in-time probability of default measure which is produced on a daily basis.
- Daily updated Probability of Default data for over 80,000 exchange-listed firms worldwide.
- NUS-CRI PD is produced using a fully transparent and regularly updated methodology to provide a measure based on the latest research in credit risk and is trusted by organisations around the world for uses such as risk management, regulatory compliance and early-warning systems
- Credit stress testing and scenario analysis toolkit jointly developed by the Credit Research Initiative (CRI) team of the National University of Singapore (NUS) and the International Monetary Fund (IMF)
- Provides a unique framework to evaluate the probabilities of default (PDs) of individual firms under prescribed macroeconomic scenarios