Measuring What Matters: How a Regional Bank Upgraded its Credit Risk Assessment Process

Measuring credit risk—including Probability of Default (PD) and Loss Given Default (LGD)—demands specialized expertise, significant time, and considerable resources.  The Risk Management function is a vital function for financial institutions, banks, or other organizations managing extensive loan portfolios or addressing high-risk issues. As a part of risk management, quantifying risk (a requirement for compliance with regulations) accurately and efficiently is not only vital for effective management but also a regulatory requirement, requires significant investment. This was the challenge faced by a regional bank, which required an efficient and accurate way to assess and quantify risk in its existing loan portfolio to meet compliance standards.

This regional bank, based in Texas, USA, is a specialty lender offering a broad range of banking services with a strong focus on capital markets. The bank holds billions of dollars in exposure, diversified across various industries. Accurate risk measurement is critical to running their Current Expected Credit Loss (CECL) model, which relies heavily on probability of default (PD) and loss given default (LGD) calculations as the foundation for precise and compliant reporting.

The bank’s Risk Department faced significant challenges in managing over 500 credits spanning across different industries and asset classes. They required a cost-efficient solution to calculate PD for their counterparties and LGD for their exposure. Furthermore, given the complexity and sensitivity of accounting standards, they needed a robust and defensible solution to satisfy auditor scrutiny. Identifying gaps in their existing models, they sought a fast, reliable, and effective method for measuring risk.

Pain Points

During our discussions with the bank, S&P Global Market Intelligence (Market Intelligence) assessed their challenges, and, in examining their current workflow, determined that a solution that delivered fast, accurate PD and recovery (LGD) scores (which would also withstand auditor examination) for their portfolio was their immediate priority. The objective was to propose solutions capable of addressing the following challenges:

1. Comprehensive Coverage: The bank’s portfolio was highly diverse, with exposure across multiple industries and asset classes.

2. Replace Manual Input with Automation: With the need to manage a large volume of credits, the bank required a solution that minimized manual intervention. The goal was to implement a system that could generate scores with minimal user input, streamlining their workflow and saving valuable time.

3. Accuracy and Efficiency: The ideal solution for the Risk Department, which consisted of only five employees, needed to monitor creditworthiness and default potential while seamlessly integrating into existing workflows. This would enable swift adoption and reduce the need for extensive training.

4. Seamless Compliance Reporting: To meet regulatory and compliance requirements, the bank required a solution that facilitated efficient and transparent reporting. The ability to present clear, audit-ready findings to their auditors was a critical necessity.

Solution

Our product specialist team conducted a detailed review of this case and recommended the adoption of S&P Market Intelligence’s Credit Analytics solution. This solution integrates sophisticated methodologies with robust data from more than 400M+ entities globally to estimate PD and credit scores, enabling organizations to efficiently monitor risk exposure to counterparties and investments globally.

Credit Analytics provides a comprehensive view of credit risk exposure through dynamic analytical models that generate actionable credit risk indicators. These models are both market-oriented and fundamentals-driven, delivering PD and credit scores designed to broadly align with ratings from S&P Global Ratings. The solution offers transparency into the drivers of default risk and facilitates scenario analyses. It covers more than 400M+ entities, includes a method for generating scores based on limited data, and includes a function whereby clients can also upload their own proprietary data and run models directly within the platform.

Key Features and Benefits

1. PD Models: Credit Analytics calculates PD using three advanced methodologies, ensuring flexibility and accuracy: 

• PD Fundamentals: This model evaluates the likelihood of default over multiple time horizons using financial statements, proprietary risk metrics, and one of the world’s largest financial databases. It measures 1- to 5-year default risk for public and private banks, corporations, and REITs of all sizes. PDs can be mapped to lowercase letter credit scores (e.g., ‘bbb’) for comparability. The model provides global coverage, spanning over 250 countries and 20+ sectors, regions, and industries. 
• Credit Model: This statistical model uses financial statements and macroeconomic data to generate quantitative credit scores that statistically align with S&P Global Ratings. These scores can also be mapped to observed default rates (e.g., 1.2%), providing a precise measure of default risk. 
• RiskGauge Scores: The RiskGauge Score delivers a holistic credit risk assessment, combining insights from the PD Fundamental, PD Model Market Signal, and CreditModel™ scores.

2. LossStats™ Model

The LossStats™ model leverages proprietary default and recovery data to estimate loss and recovery levels for US and European fixed-income and lending facilities. It accounts for industry- and instrument-specific characteristics and calculates losses across multiple exposures and seniorities. Key features include: 

• Broad coverage of collateral types, including real estate, intellectual property, oil and gas reserves, and more.
• Calibration based on a proprietary database of over 4,000 US bond and loan recoveries spanning 30+ years and 1,000 European bond and loan recoveries spanning 13+ years.
• Access to one of the largest datasets of company financial information globally, featuring standardized, transparent, and analytically enhanced data.

Results and Client Feedback

1. Coverage - During the testing phase, Credit Analytics demonstrated comprehensive coverage, exceeding client expectations. After testing their portfolio against our coverage, the client was highly satisfied, particularly upon learning that our credit analytics encompass a diverse range of over 400 million entities.

2. Methodology and Audit Readiness - The client reviewed our whitepapers and was impressed with our methodology for calculating Probability of Default (PD) scores, noting its strong alignment with S&P ratings standards. They expressed confidence that both the PD and Loss Given Default (LGD) scores would stand up to rigorous auditor scrutiny.

3. Ease of Use - Utilizing our Excel plugins, the client seamlessly integrated the PD and LGD data into their existing models with minimal effort. The plugin delivered the automation and efficiency they required, while requiring little to no training.

4. Automated Reporting - Additionally, the client was particularly pleased with our RiskGauge report functionality, which generates fully customizable reports with a single click, providing comprehensive details on the PD calculation process. This feature proved invaluable for sharing insights with both management and auditors.

S&P Global Market Intelligence’s Credit Analytics solution provided the regional bank with an automated, scalable, and efficient tool to streamline risk measurement and ensure compliance with regulatory requirements. Ultimately, this partnership enabled the bank to address its immediate challenges while enhancing long-term risk management capabilities, positioning it for continued success in managing its diverse portfolio with confidence.