About Nabil Abu el Ata
Nabil Abu el Ata has invested over 20 years maturing the science of risk management and the practical application of predictive analytics technologies. In the late 1970s Dr. Abu el Ata's mathematical discoveries provided accurate coordinates for space exploration. By solving a problem that was previously defined as unsolvable, Dr. Abu el Ata set the foundation for a new era of risk management, which today enables companies worldwide to more accurately predict future system behaviors and take strategic actions to improve business outcomes.
Entries by Nabil Abu el Ata
Current risk management practices, which deal mostly with the risk of reoccurring historical events, cannot help business, government or economic leaders deal with the uncertainty and rate of change driven by the Fourth Industrial Revolution. As new innovations threaten to disrupt, business leaders lack the means to measure the risks and rewards associated with the adoption of new technologies and business models. Established companies are faltering as leaner and more agile start-ups bring to market the new products and services that customers of the on-demand or sharing economy desire—with better quality, faster speeds and/or lower costs than established companies can match.
Successful risk determination and mitigation is dependent on how well we understand and account for dynamic complexity, its evolution, and the amount of time before the system will hit the singularity (singularities) through the intensification of stress on the dependencies and intertwined structures forming the system. In this blog post, we provide an example of a client case where dynamic complexity played a key role in terms of resource consumption, time to deliver and volume to deliver. It illustrates how the predictive emulation provided by X-Act OBC Platform can be used to isolate the evolving impact of dynamic complexity and calculate risk as an impact on system performance, cost, scalability and dependability.
We have developed an algorithm that aggregates multiple domain specific blockchains to form a purpose-oriented blockchain. Tested under a variety of cases to prove its applicability, the patented algorithm complements the blockchain protocol to provide a solution for multi-party transaction processes using multiple shared blockchains.
Traditional financial risk management methods were formulated in an analogy with the early foundational principles of thermodynamics. However, traditional economic models are incomplete models of reality because economic systems are not inclined to attain equilibrium states unless we are talking about very short windows of time (similar to meteorological or most nuclear or gravitational systems).
After years of theoretical debates and abstract use cases, it is no longer a question of if blockchain will cause market disruption, but rather when and how widely the impact will be felt. Now is the time to remove any outstanding doubts about blockchain applicability and strategically manage the business and operational risks that inevitably come with innovation.
Our causal deconstruction method is a seven-stage scientific methodology that is used to understand the constituent components of a system and any dependencies by establishing the base dynamics, deconstructing complexity, constructing an emulator, predicting singularities, comparing to the actual system, defining improvements and monitoring the execution. Causal deconstruction allows us to uncover results that often defy […]
A system is composed of components, objects, or members—each having specific properties that characterize its behavior. All members interact, impact, serve and receive from other members. Depending on the intensity of such relations and their configuration, the overall system will expose behavior patterns and characteristics.
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