Description: Applications of Stress Testing

Description: A sound enterprise risk management (ERM) framework functions as an ecosystem by balancing the interdependencies of its elements while constantly adapting to an ever‐changing, external environment. Each stakeholder has a unique role to play in forming a thriving ERM ecosystem by integrating risk‐conscientiousness in decision‐making. A resilient ERM framework has a single well‐ understood risk language and culture to promote healthy risk‐taking behaviors. The central focus of such a framework is concentrated around all stakeholders and everyone is held accountable. Every day, external forces can potentially disrupt how we operatively conduct business. Unforeseen changes in regulation, market trends, terrorist’s attacks and extreme natural disasters are often categorized as extremely adverse. How then will your ERM ecosystem survive the one‐in‐200 event and continue to flourish through dynamically changing environments?

Description: A sound enterprise risk management (ERM) framework functions as an ecosystem by balancing the interdependencies of its elements while constantly adapting to an ever‐changing, external environment. Each stakeholder has a unique role to play in forming a thriving ERM ecosystem by integrating risk‐conscientiousness in decision‐making. A resilient ERM framework has a single well‐ understood risk language and culture to promote healthy risk‐taking behaviors. The central focus of such a framework is concentrated around all stakeholders and everyone is held accountable. Every day, external forces can potentially disrupt how we operatively conduct business. Unforeseen changes in regulation, market trends, terrorist’s attacks and extreme natural disasters are often categorized as extremely adverse. How then will your ERM ecosystem survive the one‐in‐200 event and continue to flourish through dynamically changing environments?

Description: In a very general setting this paper describes a straightforward, non-parametric approach to aggregate "stand-alone" or marginal distributions with desired correlations without imposing additional assumptions on those marginals. We then develop two optimizations for the enterprise, one based on maximizing return on economic capital and the other based on a mean -semivariance efficient frontier from the investor point of view.

Description: This paper presents the output of in-house research on an emerging area of risk appetite management and our global implementation best practices. It intends to provide readers with detail implementation of risk appetite framework and assessment across an organization. It provides the conceptual risk appetite framework based model- developed by the author, implementation plan, and global best practices of a risk appetite assessment across an organization. It identifies the challenges and exceptions in the risk appetite assessment with an approach to manage it effectively, and helps organizations with cost-benefit analysis. It also includes an illustrative case study.

Description: Feature article describing the different types of risk cultures companies can have.

Description: Risk management and capital budgeting are two critical components of the corporate decision process. They often need to be considered jointly at the corporate level because of their natural interaction through the dependent risk exposures and other synergetic relationships within an intricate corporate structure in a dynamic business environment. . This paper develops an integrated framework that aligns these two important corporate strategies across business divisions to optimize the streamlined enterprise strategic goal in a multi-period setting. The proposed integrated framework can serve as a practical guideline for corporate executives to optimally coordinate capital budgeting and risk management at the enterprise level.

Description: The paper argues that Risks Evaluation at its core is a psychological process that can lead to the special type of chaos described in modern Chaos Theory. It will argue that quantification and scientific modeling does not exempt risk assessment from the potential for deep biases. Presented at 2010 Enterprise Risk Management Symposium, Society of Actuaries, April 12-15, 2010.