Dr. Yogesh Malhotra: LinkedIn: Risk Analytics Beyond 'Prediction' to 'Anticipation of Risk': Princeton University Presentations on FinTech CyberFinance
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Goldman Sachs CEO Lloyd Blankfein told the Australian Institute of Company Directors at a breakfast briefing on Friday, July 26 2013, how investors should prepare for the most extreme risk scenario. His comments about risk management capture the essence of the 'anticipation of surprise' model mentioned above and explained in Dr. Yogesh Malhotra's research papers and research monographs published over the last decade or so.
"The future is moving so quickly that you can’t anticipate it… We have put a tremendous emphasis on quick response instead of planning. We will continue to be surprised, but we won't be surprised that we are surprised. We will anticipate the surprise." - Anticipation of Surprise Framework
Risk Management Analytics beyond 'Prediction' to 'Anticipation of Risk'™ (1993-Current)
On the Origin of the Model Risk Management (MRM) Research Program
The concept of 'anticipation of surprise' articulated in a strategy journal* by scholar-practitioner Steve Kerr, the Chief Learning Officer of GE, and the future Goldman Sachs MD responsible for Goldman Sachs Leadership Development caught Yogesh Malhotra's fascination in 1995. Malhotra's research developed that concept into a comprehensive and actionable framework of model risk management of non-deterministic risks such as those associated with black swans through 'anticipation of surprise' by 'effective challenge of models'....
...Over subsequent years, Yogesh Malhotra's influential research and practices on realizing and executing the cyberspace era vision of risk modeling and risk management have guided world's greatest nations, firms, and institutions at the forefront of managing risk and uncertainty. During the same time span, Goldman Sachs as a firm is known to have fundamentally transformed its global risk management strategy around the same concept...
* Kerr, S. (1995). Creating the boundaryless organization: the radical reconstruction of organization capabilities. Planning Review, p. 41-45 (September-October)
...Subsequently, the Model Risk Guidance SR11-7/OCC 2011-12 was issued by US Federal Reserve and OCC in aftermath of the Global Financial Crisis of 2008... in 2011-2012. Just around the same time, as illustrated here, Wall Street CEOs, CFOs, and CROs started noting that "we must anticipate risk"...
...Coincidentally, this applied research program supported by a digital social enterprise has been already developing frameworks and models for the anticipated future of finance and future of risk starting with the first WWW-browser in 1993... adopted by worldwide firms, governments, and institutions... and written about and recommended by greatest tech visionaries such as Microsoft founder Bill Gates...
...Whether you are a pioneer in the ERM and MRM game or just getting started, you are all "welcome to the new world of business!!" being designed, practiced, and disseminated from that digital social enterprise for over two decades.
...Having affirmed the trajectory of his own post-doctoral quantitative risk modeling and risk management research in 2012 with the Columbia University Professor Emanuel Derman, world's most known expert on Model Risks in his view, who was prior MD and head of Quantitative Strategies group at Goldman Sachs, Dr. Yogesh Malhotra is optimistic about a more enlightened future of quantitative risk modeling...
Recent Research Presentations and Research Reports
Princeton University Presentations on the Future of Finance: 'Rethinking Finance' for Era of Global Networked Digital Finance.
2016 Princeton Quant Trading Conference Invited Research Presentation: Beyond Stochastic Models to Non-Deterministic Methods.
2015 Princeton Quant Trading Conference Invited Research Presentation: Beyond Risk Modeling to Knightian Uncertainty Management.
Beyond 'Bayesian vs. VaR' Dilemma to Empirical Model Risk Management: How to Manage Risk (After Risk Management Has Failed).
Markov Chain Monte Carlo Models, Gibbs Sampling, & Metropolis Algorithm for High-Dimensionality Complex Stochastic Problems.
Risk, Uncertainty, and Profit for the Cyber Era: 'Knight Reconsidered': Model Risk Management of Cyber Risk Insurance Models.
Cybersecurity & Cyber-Finance Risk Management: Strategies, Tactics, Operations, &, Intelligence: ERM to Model Risk Management.
Number Field Sieve Cryptanalysis Algorithms for Most Efficient Prime Factorization on Composites: Beyond Shannon's Maxim.
Bitcoin Protocol & Bitcoin Block Chain: Model of 'Cryptographic Proof' Based Global Crypto-Currency & Electronic Payments System.
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