There is a pressing need throughout the world for large-scale investments in infrastructure across a broad spectrum of industries. Infrastructure can play a key role in revitalizing the global economy by generating short-term income and long-term growth, while assisting with environmental sustainability.^[1] This leading bank in Thailand provides financing for large projects across Asia in numerous areas, including renewables, petrochemicals, and infrastructure. Project finance had become a growing portion of the bank’s loan portfolio, gaining more attention from management and compliance. The bank’s portfolio management team felt it needed to enhance its capabilities for evaluating the level of risk related to each project, especially given the inherent complexity of the asset class and the need for predominantly qualitative analysis that is unique to each transaction.

Pain Points

The portfolio management team needed to estimate the creditworthiness of a wide range of project finance transactions to evaluate potential risks for the bank, help with loan pricing, and determine appropriate capital provisioning for regulatory requirements. The team lacked the extensive internal default data necessary for the construction of statistical models that could be robustly calibrated and validated. As such, it wanted to identify a firm that could provide:

• A project finance-specific solution to address the unique characteristics of this asset class.
• A sound methodology for calculating probabilities of default (PDs) to complement cash flow analysis.
• A capability for assessing loss given default (LGD) to enhance decision making on pricing and risk mitigation.
• The ability to consider environmental, social, and governance (ESG) factors, as well as traditional credit factors.

The portfolio management team met with S&P Global Market Intelligence (“Market Intelligence”) to discuss the firm’s capabilities.

The Solution

Market Intelligence discussed its project finance solution that provides a general framework for the analysis of transactions, regardless of the industry or sector in which they operate, with the use of well-established project finance debt rating criteria. The solution comprises PD and LGD Scorecards that bring together statistically validated methodologies, quantitative and qualitative risk factors, and market benchmarks to build a single, robust assessment framework.  The Project Finance PD Scorecard is enhanced to include visualized ESG analysis, which is part of a holistic approach to assessing credit risk. Combined, these capabilities would help the portfolio management team:

Evaluate PDs for different transactions. The Project Finance PD Scorecard generates credit scores that are designed to broadly align with credit ratings by S&P Global Ratings.^[2] Results are calibrated to PDs using data from S&P Global Ratings proprietary default database, accumulated since 1981. This Excel®-based tool draws on a mix of quantitative and qualitative questions in a check-box style to identify key risks. It is transparent, providing the underlying logic, including weights. In line with S&P Global Ratings project finance criteria, it explicitly separates construction risk from operation risk to capture the credit quality of a project during its weakest period, until the obligation is repaid through project cash flows.

Determine actual losses. The Project Finance LGD Scorecard is designed to estimate the potential loss experienced by an exposed party, assuming the project is in default. The Scorecard produces point estimates of loss, capturing even the smallest changes in the value of inputs, which is crucial in the proof-of-concept stage of a project where sensitivity analysis is key. It is complemented by unique insights sourced from the Annual Global Project Finance Default and Recovery Study published by Market Intelligence,^[3] as well as relevant research and criteria published by S&P Global Ratings. LGD point estimates can be mapped to any discrete recovery rating scale, and average LGD estimates for most portfolios are considerably below 45%. 

Assess ESG factors. The Project Finance PD Scorecard is enhanced to include visualized ESG analysis, enabling the impact of ESG factors to be considered in credit risk analysis in a transparent and structured way. This adopts a holistic approach, while working through the regular credit assessment process. For each of the three ESG dimensions (environmental, social, and governance), ESG credit risk factors are defined, which are the factors that influence the capacity and willingness of an obligor to meet its financial commitments and that can have negative or positive credit impacts. ESG factors can be considered in several areas within the Scorecard framework.

Key Benefits

The portfolio management team saw many benefits to using the Market Intelligence Project Finance Scorecards to help minimize risks and meet compliance and regulatory requirements. This included having: 

• Access to an off-the-shelf, transparent, and user-friendly credit assessment framework for project finance with a clear methodology to complement cash flow analysis.
• Methodological transparency that reveals all risk factors, weights, benchmarks, and scoring algorithms.
• A broad and global scope of application, including: power generation and transmission projects (e.g., wind, hydro, biomass, nuclear and solar thermal), transportation projects (e.g., toll roads, bridges, tunnels, and ports), oil and gas projects, (e.g., refinery processing, pipelines, and storage), public-private partnership/private finance projects (e.g., schools, stadiums, hospitals, and museums), and generic projects that do not fit in the any of the categories named.
• The ability to consider ESG factors along with traditional credit analysis.
• An annual model review process to maintain high performance, reliability, and granularity.
• Technical documentation describing the analytical/statistical processes used to develop the model, identifying the data used in the construction, and providing testing performance results.
• Scorecard implementation and application training workshops, plus ongoing analytical and operational support.