Risk Management Heroes
From Open Risk Manual
Risk Management Heroes
This page includes a list of historical and current figures that have had a significant impact in the development of Risk Management as a discipline. Their work has typically been in the context of other fields (e.g., mathematics, economics of psychology).
NB 1: This is a subjective list aiming to provide useful pointers for reading / research. The Open Risk manual is not the Nobel Prize Foundation :-)
NB 2: The objective of the list is inspire and motivate risk managers. As such, academic rigor in attributing precedence and credit is of somewhat secondary importance. Additions / contributions are welcome via the feedback button or by registered authors.
NB 3: The work of early researchers is always performed in their respective historical context which may have changed significantly as norms and attitutes change.
| Hero | Period | Contribution | Counterpoint |
|---|---|---|---|
| Thales of Miletus | First recorded use of option contracts to lock-in a payoff in specified future states of the world | Not clear how influential this early example might have been for the development of derivatives markets much later in history | |
| Luca Pacioli | First person to publish a work on the Double Entry System of Book Keeping in Europe | ||
| Gerolamo_Cardano | His book about games of chance, Liber de ludo aleae ("Book on Games of Chance") contains the first systematic treatment of probability | Also the first documentation of effective cheating methods | |
| Blaise Pascal | Among the most important early contributors to the mathematical theory of probabilities | ||
| Edmond Halley | Credited with the first calculation of a mortality table, thereby laying the ground for the life insurance and pension industries | ||
| James Dodson | Mathematician who's mortality risk work played a key role in the establishment of the "Society for Equitable Assurances on Lives and Survivorships", the first modern life insurance | ||
| Daniel Bernoulli | Significant early contributions to the theory of risk aversion, risk premia and utility theory | ||
| William Morgan | Considered the first modern actuarial scientist | ||
| Thomas Bayes | Bayes first provided an equation that allows new evidence to update beliefs | ||
| Gauss | Major contributions to statistics and probability methods relevant for risk management | The tractability of Gaussian methods has facilitated application also in domain where they are not applicable | |
| Laplace | Main architect of the Bayesian view of probability | ||
| Andrey Markov | Seminal work on stochastic processes underpinning most practical (tractable) applications in quantitative risk management | See Gauss counterpoint | |
| Florence Nightingale | A pioneer in the graphical representation of statistics. She illustrated seasonal sources of patient mortality in military field hospitals, establishing modern nursing | ||
| Frank Knight | Economist who first carefully distinguished between economic risk (where probability distributions are known at the outset) and uncertainty | ||
| Ronald Fisher | Statistician and Geneticist with fundamental contributions in methodologies for classification and Discriminant Analysis | ||
| Walter Shewhart | Physicist and Statistician with fundamental contributions in methodologies for Statistical Process Control | ||
| Keynes | Major contributions at the interface between probability and economics | ||
| Jan Tinbergen | Considered to be one of the persons that founded the econometrics discipline | ||
| John von Neumann | Among many other contributions, co-inventor of the Monte-Carlo method of simulation that finds wide applicability in risk management | Simulation may hide significant weaknesses of the underlying probabilistic framework | |
| Maurice Allais | Physicist/Economist with significant work on establishing a theory of risk | Impact was delayed by a lack of translations of his work from French | |
| George E.P. Box | Influencial statistician, who worked in the areas of quality control, time-series analysis, design of experiments, and Bayesian inference. He famously said: "All models are wrong but some are useful" | ||
| George Akerlof | Economist who identified problems that afflict markets characterized by asymmetric information | ||
| Paul_Slovic | Psychologist who contributed towards the psychometric paradigm of risk perception | ||
| Richard Thaler | Economist, major contributor to the field of behavioral finance | ||
| Daniel Kahneman | With Amos Tversky and others, Kahneman established a cognitive basis for common human errors that arise from heuristics and biases | ||
| Gerd Gigerenzer | Psychologist who has studied the use of bounded rationality and heuristics in decision making | ||
| Robert J Shiller | Economist with significant theoretical work on behavioral aspects of economic bubbles | ||
| Barry A. Turner | Developed a methodology for systematically looking at the causes of a wide range of disasters, providing a theoretical basis for the origins of man-made disasters | ||
| Till Guldiman | Credited with developing the Value-at-Risk concept at bank JPMorgan. Value-at-risk is an example of algorithmic quantification of portfolio market risk | Excessive reliance on VaR widely criticised for a variety of risk management failures | |
| Nicholas Taleb | Coined the term "Black Swan", popularising the failure of formulaic approaches to risk quantification, including the Valua-at-Risk methodologies | Black swans have been invoked to explain a host of unrelated risk management pathologies | |
| Satoshi Nakamoto | Pseudonymus inventor of the bitcoin protocol, first known application to establish a distributed ledger, a technology
that offers new possibilities for establishing data based ground truth || The technology has significant shortcomings at the technical level | ||
| Judea Pearl | Computer scientist and philosopher, best known for championing the probabilistic approach to artificial intelligence and the development of Bayesian networks. He is also credited for developing a theory of causal and counterfactual inference based on structural models |
