Ali Samad-Khan, the founder of Stamford Risk Analytics, is a globally recognized thought leader in risk management. For his many innovations and contributions to the field of risk management, he was named “One of the One Hundred Most Influential People in Finance” by Treasury & Risk Management magazine and was also invited to become a charter member of Who’s Who in Risk Management.
His contributions include:
- From 1998-2000 he developed a framework for measuring operational risk capital based on an event risk matrix and property-casualty loss modeling techniques. This framework was implemented by numerous leading banks around the world and later served as the blueprint for the Basel II Advanced Measurement Approach for operational risk.
- From 2001-2003, as founder of OpRisk Analytics, he led the team that conceived, developed and operationalized a method for fitting left-truncated loss data to loss-probability distributions specified from zero. (Left-truncated data means data that is collected above the zero-loss threshold.) This technical breakthrough addressed a critical problem in property-casualty loss modeling that had remained unsolved throughout the 300+ year history of the actuarial profession. This technique, which is referred to as the Truncated Maximum Likelihood Estimation (MLE) method, currently represents the standard for best practices in operational risk modeling. However, the Truncated MLE method is being superseded by another more accurate and reliable method of fitting data called the Annualized Loss Exceedence Curve (ALEC) method, which Ali also invented (see below).
- From 2002-2006 he developed a framework for classifying risks based on a multi-dimensional risk architecture and taxonomy which leveraged game theory techniques (a payoff matrix). This approach, which has made consistent risk classification feasible and practical, is critical to portfolio-based risk assessment and risk measurement. Variations of this technique have been adopted by numerous financial institutions and regulators around the world.
- From 2008-2014 he conceived and operationalized “Strategic ERM,” a framework that transforms ERM from a compliance exercise into a process that facilitates informed risk-based decision-making and adds tangible value. Strategic ERM techniques allow executives to objectively and systematically identify and quantify their key risks as well as to optimize risk-reward trade-offs at the risk tolerance level of their stakeholders. Strategic ERM is applicable across all industries, globally.
- From 2009-2011 he invented and operationalized a new Monte Carlo simulation algorithm for convoluting frequency and severity distributions. This new technique can reduce processing time by as much as 99%. With this ultra-high speed routine, certain tasks that previously took hours can now be completed in minutes or even seconds. By producing virtually instantaneous results this invention facilitates dynamic, real-time risk management decision-making. Absent this discovery, Strategic ERM would be rendered impractical.
- From 2009-2018 he led the team that conceived, developed and operationalized the ALEC method of modeling losses – a variation of the property-casualty loss modeling approach. A key characteristic of the ALEC method is that it allows one to simultaneously (not sequentially) fit data to frequency and severity distributions and thereby produces the combined best-fit frequency and severity parameters. The ALEC method addresses critical weaknesses inherent in the traditional property-casualty loss modeling approach; specifically, it mitigates the risk of model inconsistencies caused by data that are truncated, non-homogenous, contain outliers and exhibit clustering. It is also the only such model that allows for the legitimate use of inputs based on expert opinion as well as the combination of such inputs with empirical data in an objective, transparent and theoretically valid manner. Absent this discovery, Strategic ERM would be infeasible.
- From 2009-2018 he led the team that conceived, designed and managed the development of the industry’s most advanced operational risk modeling and model validation tools. These tools, Risk Modeler and Model Validator, are currently being used by many leading banks and insurance companies around the world.
- From 2010-2018 he led the team that conceived, designed and managed the development of the Enterprise Risk Manager software solution which is to be formally released in 2018.