Catastrophic Risk (CAT), Climate Investment Risk, Climate Credit Analytics, Asset Allocation, Dynamic Financial Analysis (DFA), MCEV (Market Consistent Embedded Value), Economic Scenario Generations (ESG) & other Risk Management & Artificial Intelligence (Machine Learning) Tools. Market Risk (VaR, SVaR, ES, FRTB) and Potential Future Exposure/ FX/ Counterparty Risk/ Insurance Risk, Operational Risk, Credit Risk for high default portfolios (default intensity et al)
Quantitative Risk Management in an organization should prudently manage risks to protect the organization irrespective of the regulatory authorities (local or global), Central Bank, internal audit or actuarial analysis. At international class organizations, the standards of enterprise risk management (ERM) methodologies, models, and policies put in place are at a significantly deeper level than those required to merely satisfy regulatory requirements. Consequently, all decisions processes, strategies or models used in an organization would require independent validation by risk management departments and possibly external validation by quantitative risk leaders. Given the recent market turmoil, commodity price uncertainty, currency fluctuations, investment risk, there is an enhanced sense of urgency in ensuring model validation and internal rating are in place. Any strategy or any model used to understand impacts of the strategy, can only be validated through quantitative transformations.
Information is power and without it risk managers simply walking in the dark with unknown and unquantifiable risk exposures lurking in the shadows. To this end, this RsRL CEL is designed to appeal to risk leaders including CROs, CEOs, chief economists, chief investment officers, risk officers to collaborate with ministers, policy leaders and sovereign investors to construct a feasible Risk Management framework for the regional markets and economies.
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