Risk Ontology
In the wave of thinking from the concepts such as Black Swan and Chaos Theory, resilient systems thrive with greater disorder and idiosyncrasies, fragile systems break under stress. From a mathematical perspective, it is impossible to come up with a probability of a rare (or unseen) small event, especially in the fat tail domain (known as the problem of induction). In Arabic, predictions are called “prophecies”, and indeed, forecasting is like prophesying which has many psychological aspects. Any economic number from oil prices to GDP growth forecasts from most forecasters have been incorrect; however, people still pay attention to it. The methods, results, and applications offered in my earlier research could either end up adding or reducing redundancy to the system, where technology itself should be a domain of risk. There are heuristics and simple solutions that have implications for human judgment thatrequire a system for orchestration of information and knowledge between man andmachine, and vice-versa, “externalities” that our system design aims to shed light on.
The research and development around our data platform aims to improve and standardize large scale data harvesting, transparent benchmarking of model reliability, and data visualization schemas to directly aid decision-making concerning economic, financial, and geopolitical information systems. Inevitably our work also aims to address fundamentally new areas, in human error and cognitive aspects of how decision-makers perceive and act upon new information.
Risk mitigation strategies based on multi-sensor fusion to classify human and machine errors can help avoid catastrophic financial or economic losses induced by human error. Many of these areas of research are inspired by the study of human error in nuclear power plants and defense, aerospace applications of autonomous vehicles, however, the applications to decision-making for large-scale infrastructure projects have not been studied in-depth. Our approach to standards is designed from a data-driven perspective to help build a macro-micro risk register. There are many categories of risks and ever-new risks that are emerging on a daily basis. With an ever expanding catalog of risks the idea is if similar risks are repeated the system can identify and quantify them systematically.
Figure. Static Scehma of Common Definitions of Entities, Risk Domains, Risk Classes, and Planning Horizons
| Domain | Subdomain |
|---|---|
| Business and Logistics | Dealing with construction permits |
| Business and Logistics | Ease of doing business |
| Business and Logistics | Enforcing contracts |
| Business and Logistics | Getting credit |
| Business and Logistics | Getting electricity |
| Business and Logistics | Logistics Performance Index |
| Business and Logistics | Paying Taxes |
| Business and Logistics | Protecting minority investors |
| Business and Logistics | Registering property |
| Business and Logistics | Resolving insolvency |
| Business and Logistics | Starting a business |
| Business and Logistics | Trading across borders |
| Climate and Environment | Biodiversity & protected areas |
| Climate and Environment | Biological Disaster |
| Climate and Environment | Climatological Disaster |
| Social and Demography | Density & urbanization |
| Climate and Environment | Disaster |
| Climate and Environment | Emissions |
| Climate and Environment | Freshwater |
| Climate and Environment | Geophysical Disaster |
| Climate and Environment | Hazard |
| Climate and Environment | Hydrological Disaster |
| Climate and Environment | Land use |
| Climate and Environment | Meteorological Disaster |
| Climate and Environment | Natural Disaster |
| Climate and Environment | Technological Disaster |
| Consumer Sentiment | Google Trends |
| Finance | Access |
| Finance | Bonds |
| Finance | Capital markets |
| Finance | Central Bank |
| Finance | Commodities |
| Finance | Equity |
| Finance | Financial Development |
| Finance | Foreign Exchange |
| Finance | Macro-Financial |
| Geopolitics | Democracy |
| Geopolitics | Geopolitical Opportunity |
| Geopolitics | Geopolitical Threat |
| Geopolitics | Governance |
| Macroeconomy | BOP and IIP |
| Macroeconomy | Central Bank |
| Macroeconomy | Debt |
| Macroeconomy | Fiscal |
| Macroeconomy | Labor |
| Macroeconomy | Macro-Financial |
| Macroeconomy | National Accounts |
| Macroeconomy | Natural resources contribution to GDP |
| Macroeconomy | Prices |
| Macroeconomy | Statistical Capacity |
| Macroeconomy | Structural |
| Macroeconomy | Trade |
| Policy & Regulations | CPIA |
| Policy & Regulations | Economic Policy Uncertainity |
| Policy & Regulations | Geopolitical Risk Index |
| Policy & Regulations | STRI Indicators |
| Sector | Agriculture |
| Sector | Defense & arms trade |
| Sector | Education |
| Sector | Energy |
| Sector | Health |
| Sector | Industry |
| Sector | Research & Development |
| Sector | Technology |
| Sector | Telecommunications |
| Sector | Tourism and Travel |
| Sector | Transport |
| Social and Demography | Education |
| Social and Demography | Population |
| Social and Demography | Social Protection |