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Advanced Strategies in Credit Risk Management
This discussion explores the themes and strategies around credit risk management and modeling within an organization. The organization employs a multifaceted approach, combining advanced statistical models, machine learning, and qualitative adjustments to assess and quantify credit risk.
Aug 05, 2024
Michael Jacobs
Michael Jacobs, Lead Modeling & Analytics Expert, PNC Financial Services Group
Advanced Strategies in Credit Risk Management
The views and opinions expressed in this content are those of the thought leader as an individual and are not attributed to CeFPro or any other organization

The interview discusses the multi-faceted approach to credit risk management within an organization. Credit risk assessment and quantification involve statistical models and non-model methodologies, augmented by qualitative adjustments and expert judgment. The models are created with input from various business units to ensure they meet practical needs and business expectations. This includes using advanced algorithms like machine learning alongside human judgment.

The organization employs a rigorous quality assurance process, conducting independent testing before regulatory review. This helps mitigate risks from faulty models, which could lead to poor decisions and regulatory issues.

For stress testing, the organization adapts models and creates specific scenarios to handle unexpected economic changes, such as those seen during the COVID-19 pandemic. 

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