Global Risk Management Network, LLC, 757 Warren Rd, Cornell Business & Technology Park, Ithaca, NY 14852-4892
World Leading Hi-Tech Research Defining World Leading Digital, Computational, Quant & Cyber Risk Analytics Practices

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Dr. Yogesh Malhotra
PhD,MSQF,MSCS,MSNCS,MSAcc,MBAEco,
BE,CEng,CISSP,CISA,CEH,CCP/CDP
Who's Who in America®,
Who's Who in the World®,
Who's Who in Finance & Industry®,
Who's Who in Science & Engineering®

E-mail: Dr.Yogesh.Malhotra[at]gmail.com
*LinkedIn: linkedin.com/in/yogeshmalhotra

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*RESEARCH
*SSRN
*GoogleScholar
*Princeton
*Syracuse
      


 

Global Finance-IT-Risk Management Digital, Computational, Quant, & Cybersecurity Practices Leaderships:
Computer Scientist, Management Scientist, Information Scientist: Research Impact among Nobel Laureates
World's Largest Banking & Finance Firms, IT & Telecom Firms, Wall Street CxOs, Silicon Valley CxOs,
National Science Foundation; United Nations; US & World Governments, Economies, Defense Agencies.

*2016 Princeton Quant Trading Conference: Among other Presenters: It was a pleasure to collaborate.
*2016 Princeton Quant Trading Conference Invited Research Presentation: Sponsor: Princeton University.
*2015 Princeton Quant Trading Conference Invited Research Presentation: Sponsor: Princeton University.
*2015-2016: 39 Top-10 SSRN Research Rankings: Digital, Computational, Quantitative & Cyber Risk Analytics.
*2016 New York State Cyber Security Conference Research Presentation: Sponsor: New York State Governor.
*2015 New York State Cyber Security & Engineering Technology Association Conference: Sponsor: NYSETA.
*2008: AACSB: Real Impact of Research among Nobel Laureates such as Black-Scholes & William Sharpe.

FinTech AI-Modeling, Algorithms, & Machine Learning for Computational Quant Analytics, Cyber-Finance-Risk

MarkovChainMonteCarloBitcoinProtocolBlockchainCryptographicProofOfWork  Princeton Quant Trading Conference 2016  Number Field Sieves Algorithmic Cryptanalysis

2015-2016: 39 Top-10 SSRN Research Rankings in World-Leading Digital, Computational, Quant & Cyber Risk Analytics.
2015-2016: Digital, Computational, Quant & Cyber Risk Analytics Presentations sponsored by New York State and Princeton University.
Over 20-Years of Global High Impact Hi-Tech Digital Practices Leadership spans Silicon Valley to Seoul and all continents in between.
Considerable Global Impact of Research on Digital Transformation Practices ranked among Finance & IT Nobel laureates in scientific studies.

AACSBAACSB logo

  
Wall Street Journal
  
Risk Management Tech Ventures leading Computational Quantitative Analytics, Machine Learning, Data Science, Quantitative Finance, & Cybersecurity Practices.
Worldwide Business and IT Editorial Coverage & Interviews in Wall Street Journal, New York Times, Fortune, Fast Company, Forbes, Business Week, CIO, CIO Insight, Computerworld, Information Week, etc.


FinTech AI-Modeling, Algorithms, & Machine Learning for Computational Quant Analytics, Cyber-Finance-Risk

MarkovChainMonteCarloBitcoinProtocolBlockchainCryptographicProofOfWork  Princeton Quant Trading Conference 2016  Number Field Sieves Algorithmic Cryptanalysis

[39 SSRN Top-10 Research Rankings: Computational Quant Analytics, Algorithms, & Machine Learning, 2015-2016].


VENTURES: [Computational Quant Analytics] [Cyber Security Risk Engineering] [Digital Transformation Pioneer] [Algorithms & Machine Learning] [FinTech: 'Rethinking Finance']
Dr. Yogesh Malhotra: LinkedIn: Risk Analytics Beyond 'Prediction' to 'Anticipation of Risk': Princeton University Presentations on FinTech CyberFinance
Who's Who in America®, Who's Who in the World®, Who's Who in Finance & Industry®, Who's Who in Science & Engineering®
2015 & 2016 Princeton Quant Trading Conference Presentations: Computational Quant & Crypto Machine Learning Algorithms,
2008: AACSB International Impact of Research Report: Named among Black-Scholes, Harry Markowitz & Bill Sharpe

*Projects *Goldman Sachs *JP Morgan *Wall Street Hedge Funds *Princeton Presentations *Model Risk Arbitrage *Cyber Finance *Cyber Risk Insurance * Ventures
*Bayesian vs. VaR *Markov Chain Monte Carlo Models *Mobile Trust Models * Pen Testing Frameworks *Bitcoin Cryptanalytics *NFS Cryptanalytics Algorithms
*Research Impact *Future of Finance *Beyond VaR *Model Risk Management *SR11-7 *OCC2011-12 *Future of Risk *Cyber Risk *SSRN *Google Scholar *Publications


Advancing on leadership of top Wall Street investment banks and hedge funds and having examined next-generation computational probabilistic modeling of financial econometric signals processing for global financial markets using computer science algorithms and machine learning, his computational quantitative risk management focus advanced to include global electromagnetic spectrum networks and global networking and encryption protocols. Spanning deterministic, stochastic, and non-deterministic computational statistical modeling methodologies, his current Computer Science, Computational Quantitative Analytics, &, Cybersecurity-Finance applied research focus is on high-dimensionality complex stochastic problems involving computational time complexity and computational space complexity relevant to emerging Model Risk Arbitrage and Model Risk Management concerns of Wall Street Chief Risk Officers such as the following.

"Recently, such probabilistic, statistical, and numerical methods related concerns are in globally popular press related to cybersecurity controls and compliance. Earlier, similar probabilistic, statistical, and numerical methods related concerns were in the global popular press in the context of the Global Financial Crisis. Future questions focused on the underlying assumptions and logic may focus on related implications for compliance, controls, valuation, risk management, etc. Likewise, recent developments about mathematical entropy measures shedding new light on apparently greater vulnerability of prior encryption mechanisms may offer additional insights for compliance and control experts. For instance, given related mathematical, statistical and numerical frameworks, analysis may also focus on potential implications for pricing, valuation and risk models. The important point is that many such fundamental assumptions and logic underlying widely used probabilistic, statistical, and numerical methods may not as readily meet the eye."

Source: Invited Interview on Bitcoin BlockChain Cryptographic Protocols with Hong Kong Institute of CPAs, Jan. 20, 2014.
Reference: First Research Report on Bitcoin 'Cryptographic Proof' preceding Goldman Sachs & other high-profile FinTech reports, Dec. 04, 2013.

How applied research shapes worldwide practices - an exemplary illustration in context:

"[T]he approaches to mitigate operating risk associated with the use of models need to evolve to reflect recent trends in the Finance Industry. In particular there are a number of new areas where it is not possible for the "human eye" to necessarily detect material flaws: in the case of models operating over very small time scales in high frequency algorithmic trading, or for portfolio risk measurement models where outputs lack interpretability due to high-dimensionality and complex interactions in inputs, the periodic inspection of predicted versus realized outcomes is unlikely to be an effective risk mitigate. These situations require a holistic validation framework of the system focused on identifying and mitigating potential failures, taking into account the models’ objectives, their implementation including the joint interaction of software and hardware, their response to potential input shocks in real time and the fail-safe mechanisms."

Retained Exec Interview Spec: Managing Director/Executive Director, NYC, Top Wall Street Investment Bank; Interviewed: March 21, 2014.

2015-2016: 39 SSRN Top-10 Research Rankings:
Computational Quant Analytics & Machine Learning, Algorithms, AI & Modeling

• 39 SSRN Top-10 Research Rankings:
Computational-Quant-Cyber-FinTech-Algorithms-Machine Learning-AI & Modeling, 2015-2016.
- Quantitative Finance, Computer Science, Cybersecurity, Machine Learning, Bayesian Inference, Markov Chain Monte Carlo Models, Data Science, Computational Statistical Algorithms.
- Post-Doctoral Research & Working Papers
• Research selected for 39 SSRN Top-10 Rankings in Computational Quantitative Risk Analytics.
- SSRN Top-10 Ranking Categories: 
• Capital Markets, 
• Computational Techniques, 
• Corporate Governance, 
• Cyberlaw, 
• Decision-Making under Risk & Uncertainty, 
• Econometric & Statistical Methods, 
• Econometric Modeling, 
• Econometrics, 
• Hedging & Derivatives, 
• Information Systems & Economics, 
• Mathematical Methods & Programming, 
• Microeconomics, 
• Operations Research, 
• Risk Management, 
• Risk Management Controls, 
• Risk Modeling, 
• Stochastic Models, 
• Systemic Risk, 
• Uncertainty & Risk Modeling, and, 
• VaR Value-at-Risk

  • Math-FinTech-Algorithms: Transformation of Finance for Switzerland

    Math-Fintech-Algorithms: Transformation of Finance for Switzerland
    Sponsor: Switzerland Federal Department of Economic Affairs.
    Mathematics-FinTech-Algorithms: Digital Transformation of Global Banking & Finance, 2016.
    Switzerland Federal Department of Economic Affairs, Education & Research EAER.

  • Princeton University: Offensive Cybersecurity & Model Risk Arbitrage

    • 2016 Princeton Quant Trading Conference invited Post-Doc Presentation.
    - Sponsors: Princeton University, Goldman Sachs, Citadel, SIG, Apr 16, 2016.
    - Beyond Stochastics to Non-Deterministic Finance: Model Risk Arbitrage-Open Systems Finance:
    Focus: Cybersecurity, Quant FinTech, Bayesian Networks, Non-Deterministic Probability-Statistics.
    • Pioneered Computational Quantitative Analytics industrial research in Non-Deterministic Finance, Model Risk Arbitrage, Open Systems Finance, and, Black Hat Finance invited for presentation at the 2016 Princeton Quant Trading Conference.

  • Princeton University: Defensive Cybersecurity & Model Risk Management

    • 2015 Princeton Quant Trading Conference invited Post-Doc Presentation.
    - Sponsors: Princeton University, Citadel, KCG Holdings, Apr 4, 2015.
    - Quantitative Finance Models for Extreme Risks: Cyber Risk Insurance Modeling & Finance.
    Focus: Cyber Finance: Quantitative Finance, Computer Science, Cybersecurity, Machine Learning.
    • Pioneered Computational Quantitative Analytics industrial research in Cyber Finance & Cyber Risk Insurance Modeling in collaboration with the committee of distinguished research scientists from AFRL/NYS-CRI invited for presentation at the 2015 Princeton Quant Trading Conference.
    • Pioneering Quantitative Finance Analytics: Statistical Computing Methods & Algorithms
    Cyber Finance: Future of Finance Beyond 'Flash Boys': Tail Risks & Systemic Risks: 
    Risk Modeling for Managing Uncertainty in an Increasingly Non-Deterministic Cyber World.
    Advanced Risk Modeling Statistical Techniques: Econometrics & Time Series Models, Bayesian Inference, Markov Chain Monte Carlo, Capital Markets, Derivatives, Portfolio Construction & Optimization Models, Volatility Models, VaR, ARCH, GARCH, Multifactor Pricing Models, Market Risk, Credit Risk, Liquidity Risk, Cyber Risk Insurance Models.
    • Invited ERM/MRM Keynotes to Top Investment Bank HQ and National CROs/CSOs.
    • Invited Cyber-RM Expert Advice & Invited Interviews by MDs-Teams of Top Wall Street Firms.

  • Journal of Defense Modeling and Simulation (JDMS): STIX, TAXII, MCMC, Bayesian Networks

    40+ Scientific Research Journals & Proceedings Editorial & Review Boards: 
    ACM, IEEE, IBM, MISQ, ISR, JMIS, Decision Sciences, JDMS:
    Latest Expert Panel: Journal of Defense Modeling and Simulation (JDMS), 2016
    (Cybersecurity, Bayesian Networks, Markov Chain Monte Carlo Models, STIX, TAXII, etc.)
    - Society for Modeling and Simulation International.
    Tier-1 Global Refereed Research Journals, Conference Proceedings, and Research Monographs:
    100+ Computational Quant Analytics Modeling Reviews for Tier-1 Research Publications
    Academy of Management Best Reviewer Award: Review of Structural Quantitative Models Best Paper.

  • • Technologies of Computational Quantitative Finance & Risk Analytics and Risk Management
    • Algorithms & Computational Finance: C++, SAS, Java, Machine Learning, Signal Processing

While AACSB International Impact of Research Task Force reports "substantial impact on practice" of his research among Finance & Economics Nobel laureates such as Black-Scholes, Harry Markowitz, and, Bill Sharpe, premier scientific impact studies in top-tier research journals have ranked and recognized the impact of his research among top Economists, Information Scientists, and, Strategists such as Joseph Schumpeter, Paul Romer, Nobel laureate Herbert Simon, and, Michael Porter. In addition to being included among both Ikujiro Nonaka and Herbert Simon in the top-ranked research impact by the citation impact analysis studies published by the American Society for Information Science & Technology (ASIST), and, the University of Minnesota MIS Research Center, he was among them to be invited as seminal contributors to advancing Knowledge Management by the American Society for Quality, the administrator of Malcolm Baldrige National Quality Program Awards, for their flagship peer-reviewed research journal.

Dr. Yogesh Malhotra’s recent research is the focus of invited research presentations at the 2016 Princeton Quantitative Trading Conference and the 2015 Princeton Quantitative Trading Conference sponsored by Princeton University, Goldman Sachs, Citadel, and, KCG Holdings. That research is also selected for 39 SSRN Top-10 Research Rankings in statistical, econometric, computational, and stochastic modeling techniques by the SSRN research network founded and overseen by professors from institutions such as Harvard Business School. Earlier, the real world impact of his published research in Model Risk Management on worldwide practices was recognized by the AACSB International Impact of Research Report while he served as Assistant Professor of Quantitative Methods at Syracuse University and was promoted to Associate Professor. His earlier research is ranked and recognized among Top-50 Business & Economics researchers as well as Information Science and Finance/Economics Nobel laureates in business press, industry surveys & scientific impact studies. His applied research including world's Top-ranked Research Web site (Computerworld), Top-3 Search Engine (Carnegie Mellon Industry.Net National Awards), and Top-10 social network developed while doing PhD is recognized among global benchmarks of practice in worldwide business technology press including Wall Street Journal, New York Times, Los Angeles Times, Fortune, Forbes, Inc., Business Week, San Jose Mercury News, Computerworld, Information Week, CIO Magazine, CIO Insight, Chief Executive, etc. His applied research ventures are also recommended and applied by top IT Executives such as Microsoft Founder, Chairman and CEO Bill Gates; top Business Executives such as PwC Vice Chairman and CKO Ellen Knapp; global Banking and Finance institutions; CxOs of NASA / US Army / US Navy / US Air Force / US Air Force Research Lab; and senior leaders at world governments and parliaments such as the European Union and the Australian Parliament.

His Computational Quantitative Risk Management focus over the last decade has been on advancing top Wall Street investment banking leadership risk management strategies to reflect recent trends in Finance particularly as they relate to Model Risk Management concerns. His recent experience is in leading quantitative finance and quantitative risk modeling projects for top Wall Street investment banks with $1 trillion AUM such as JP Morgan Private Bank. Prior to that he founded award-winning influential financial and risk analytics ventures with clients and patrons such as top Wall Street and IT firms such as Goldman Sachs, Google, IBM, Intel, Microsoft, and, Ogilvy; top consulting firms such as Accenture, E&Y, McKinsey, and, PwC; and top business schools such as Harvard, MIT, Princeton, Stanford, and, Wharton while Associate Professor & Assistant Professor of Quantitative Methods in research academia and invited Executive Education faculty at Carnegie Mellon University Graduate School of Industrial Administration (now, Tepper School of Business) & and, Kellogg School of Management among Digital Business-IT Pioneers. Before research academia, he was a global banking modeling & implementation projects leader with big banks such as Bank of America across USA and Hong Kong and led development of global financial systems used by worldwide banks and financial firms. His research is advancing execution of SR11-7 and OCC 2011-12 Model Risk Management Guidance of OCC and US Federal Reserve System such as 'anticipation of risks' by 'effective challenge of models'.

He has been called on to advise the US National Science Foundation (NSF), the United Nations (UN),  US & World governments, parliaments, and, cabinets and delivered national keynotes and nationally broadcast interviews among Knowledge Management pioneers such as Dr. Ikujiro Nonaka, University of California Berkeley Distinguished Professor, and Dr. Charles Lucier, Booz Allen Hamilton Partner & CKO. He has been interviewed among Virtual Organization pioneers such as Hatim A. Tayabji, CEO, Verifone, while he held a PhD research fellowship in mid-1990s pioneering some of the early globally influential digital transformation ventures including world's Top-ranked Research Web site (Computerworld), Top-3 Search Engine (Carnegie Mellon Industry.Net National Awards), and Top-10 Social Network. His Digital & Analytics ventures recommended by IT visionaries such as Microsoft founder Bill Gates are recognized as global benchmarks of practice in worldwide business technology press including Wall Street Journal, New York Times, Los Angeles Times, Fortune, Forbes, Inc., Business Week, San Jose Mercury News, Computerworld, Information Week, CIO Magazine, CIO Insight, and, Chief Executive, etc. and by prestigious institutions such as Harvard Business School and MIT.

While serving in quantitative risk modeling research academia, as one of the two US economists with Northwestern University Departmental Chair & Professor of Economics being the other, he led the United Nations global expert panel of economists as invited quantitative economist expert on National Knowledge Assets Measurement. He also served as invited panelist on 32 national expert panels of computer scientists for the US National Science Foundation for allocation of multi-million dollar US federal funds. He served as one of four founding members and contributing editors for Ziff Davis and led US CxOs in global standards development for the Global Standard for Internet Commerce. He guided strategic development of Next Generation e-Business Architectures for $100 billion hi-tech firms such as Intel Corporation. He served as invited plenary keynote speaker & thought leader for Silicon Valley Venture Capitalists & CxOs; the Conference Board National Quality Council of Malcolm Baldrige National Quality Award CxOs; the Institute for Supply Management; United Nations world headquarters Global Economists Expert Panel; and United States Federal Government and world governments, parliaments and cabinets such as Government of Netherlands and Government of Mexico, and national economies such as South Korea.

Six years before AACSB highlighted the impact of his research, CNet had conferred Corporate Computing Award on his research paper cited by the AACSB as being the most influential research paper based upon their usage counts of all their archived research papers. His applied research technology ventures have won top awards, top rankings, and, editorial reviews as global CxO best practices benchmarks in most known US and worldwide top-tier Information Technology and Information Systems business press journals. Editorial reviews of his technology ventures and his interviews have appeared in the worldwide business and technology press including Wall Street Journal, New York Times, Los Angeles Times, Fortune, Forbes, Inc., Business Week, San Jose Mercury News, Computerworld, Information Week, CIO Magazine, CIO Insight, Chief Executive, etc.

His research for advancing thought leadership and insights of world's foremost leaders and top executives is found in use as standard reference in libraries of institutions such as Harvard, MIT and Princeton, and in top universities and business schools of the world such as Harvard Business School MBA Program, Stanford Graduate School of Business and Wharton School. His biography has been selected by invitation for inclusion in biographical profiles of worldwide leaders and achievers from both the United States and around the world in: Marquis Who's Who in America®, Marquis Who's Who in the World®, Marquis Who's Who in Finance & Industry®, and Marquis Who's Who in Science & Engineering®.

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.
*2015-2016 39 SSRN Top-10 Research Rankings for Computational Quantitative & Risk Analytics Algorithms Machine Learning Research.
* 2008 AACSB International Impact of Research Report: Named among Black-Scholes, Markowitz, Sharpe, Modigliani & Miller

Top Wall Street Investment Banks Quantitative Finance Projects & FinTech Ventures
Princeton: Future of Finance: 'Rethinking Finance' for Era of Global Networked Digital Finance
2016 Princeton Quant Trading Conference: Invited Research Presentation: Model Risk Arbitrage
2015 Princeton Quant Trading Conference: Invited Research Presentations: Future of Finance
Quantitative Finance Risk Analytics Modeling Wall Street Investment Banks & VC Projects
Model Risk Management: Risk Management Analytics from 'Prediction' to 'Anticipation of Risk'
Quantitative Finance Risk Analytics, Econometric Analytics, Numerical Programming Models
Quantitative Finance Model Risk Management for Systemic-Tail Risks in Cyber Risk Insurance
JP Morgan Portfolio Optimization, VaR & Stress Testing: 17-Asset Class Portfolio
JP Morgan Portfolio Liquidity Risk Modeling Framework for $500-600Bn Portfolio
Bayesian VaR Beyond Value-At-Risk (VaR) Model Risks Exposed by Global Financial Crisis
Goldman Sachs Alumnus Asset Manager Large-Scale Data High Freq Econometric Models
Quantitative Finance, Risk Modeling, Econometric Modeling, Numerical Programming
Technologies of Computational Quantitative Finance & Risk Analytics and Risk Management
Algorithms & Computational Finance: C++, SAS, Java, Machine Learning, Signal Processing
Cybersecurity, Financial Protocols & Networks Protocols Analysis, and, Penetration Testing
Quantitative Finance, Quantitative Risk Analytics & Risk Management Projects Impact
Digital Social Enterprise Ventures Creating Trillion $ Practices for Hundreds of Millions

Named among FinTech Finance & IT Nobel laureates for Real World Impact of Research
FinTech Innovations: Model Risk Arbitrage, Open Systems Finance, Cyber Finance, Cyber Insurance
AACSB International Reports Impact of Research among Black-Scholes, Markowitz, Sharpe
Research Impact Recognized among Finance & Information Technology Nobel laureates
39 SSRN Top-10 Rankings: Computational Quant Analytics: Algorithms, Methods & Models
FinTech Innovations: Model Risk Arbitrage, Cyber Finance, Cyber Risk Insurance Modeling
Computational Quantitative Finance Modeling & Risk Management Research Publications
Model Risk Management of Cyber Risk Insurance Models & Quantitative Finance Analytics
Thesis on Ongoing Convergence of Financial Risk Management & Cyber Risk Management
U.S. Federal Reserve & Office of the Comptroller of the Currency Model Risk Guidance
Bayesian VaR Beyond Value-At-Risk (VaR) Model Risks Exposed by Global Financial Crisis
Markov Chain Monte Carlo Models & Algorithms to Enable Bayesian Inference Modeling
OCC Notes Cybersecurity Risk & Cyber Attacks as Key Contributor to Banks' Financial Risk
Future of Bitcoin & Statistical Probabilistic Quantitative Methods: Global Financial Regulation
Models Validation Expert Panels: IT, Operations Research, Economics, Computer Science

Global, National, & Enterprise CxO Level FinTech-Cyber-Risk Analytics Ventures
CxO Think Tank that pioneered 'Digital' Management of Risk, Uncertainty, & Complexity
CxO Consulting: Global, National & Corporate Risk Management Practices Leadership
CxO Guidance: Cyber Defense & Finance-IT-Risk Management: Uncertainty & Risk
CxO Keynotes: Conference Board, Silicon Valley, UN, World Economy: Uncertainty & Risk
The Future of Finance Project Leading Quantitative Finance Practices at Elite Conferences
The Griffiss Cyberspace Cybersecurity Venture Spans Wall Street and Hi-Tech Research
UN Quantitative Economics Expert Paper & Keynote on Global Economists Expert Panel
National Science Foundation Cybersecurity & Cybercomputing National Expert Panels
Digital Social Enterprise Innovation Ventures Pioneering the Future of Risk and Quant
Global Footprint of Worldwide World-Leading CxO Risk Management Ventures & Practices