Artificial Intelligence Based Commercial Risk Management Framework for SMEs
2. Nature and Implications of Commercial Risk for SMEs and General Definitions: Risk, Risk Assessment and Management
2.1. Uncontrolled Risk in Commercial Processes as One of the Factors Destroying SMEs Competitiveness and SDG Objectives
2.2. General Definitions: Risk, Risk Assessment and Management
- What can happen?
- How likely is it that it will happen?
- If it does happen, what are the consequences?
2.3. Ecosystem Perspective Approach to Commercial Risk Management Framework
3. AI Solutions for Commercial Risk Management
3.1. Existing AI Solutions, Their Applicability, and Availability
- First, it is highly desirable for decision-makers to be aware of the full range of the possible risk in order to make informed and balanced decisions.
- Second, point risk estimates frequently are very uncertain because of the accumulation of the effects of rare data, expert judgments or/and various conservative assumptions.
3.2. Risk Assessment Workflow Using Machine Learning
4. Discussion on Recommendations for CRMF and AI Applicability
- Commercial risk is a substantial issue for SMEs, affecting their performance and international competitiveness. Insufficient performance does not allow SMEs to achieve SDG defined state of the business. Unassessed and unmanaged commercial risk results in business shortages.
- The given theoretical approach of risk management framework could be extended considering expected implications in policy, further research, and business levels dealing with commercial risk and AI applications.
- Though there are many risk definitions, the commercial risk here is perceived as the assessed probability of an event with negative commercial consequences. The factors of risk, i.e., events having negative commercial consequences, are found in a broad range of analytical levels around commercial processes, including product/process/value stream, commercial infrastructure, intra- and inter-organizational relationships/networks, social and natural environment. The latter analytical level covers those factors that are certain company invariant and define their groups based on sector, home country, etc.
- The calculation of negative event probability is done applying the statistical analysis of selected certain risk event factors. The statistical analysis of selected risk factors is applied to the artificial intelligence development approach, i.e., by learning machines to apply historical patterns for new data evaluation and respective potential risk assessments.
- CRMF is conceptualized as external to the certain business ecosystem-level services provider. SMEs as CRMF’s services users would get risk assessments of potential and/or existent commercial partners—suppliers or buyers. Such services would help SMEs reduce costs for human resource development, data collection, data processing and AI-based risk assessment solution maintenance.
- Observing a variety of financial data, it would be difficult for machine learning techniques to identify the risky case. However, this task becomes easier in the finance domain considering the relevant features.
- Proposed CRMF based SME support solutions development is expected to include data from various sources. Internal business data defining selected risk factors are shared by SMEs themselves. External data, collected and structured (maybe analyzed) by private or public bodies, also defining selected risk factors are associated with particular SMEs. State or industry level indicators, whose values are invariant to the certain SME and define their environmental or other fixed characteristics, are also used to assess the probability of events with negative consequences for the business.
Conflicts of Interest
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Žigienė, G.; Rybakovas, E.; Alzbutas, R. Artificial Intelligence Based Commercial Risk Management Framework for SMEs. Sustainability 2019, 11, 4501. https://doi.org/10.3390/su11164501
Žigienė G, Rybakovas E, Alzbutas R. Artificial Intelligence Based Commercial Risk Management Framework for SMEs. Sustainability. 2019; 11(16):4501. https://doi.org/10.3390/su11164501Chicago/Turabian Style
Žigienė, Gerda, Egidijus Rybakovas, and Robertas Alzbutas. 2019. "Artificial Intelligence Based Commercial Risk Management Framework for SMEs" Sustainability 11, no. 16: 4501. https://doi.org/10.3390/su11164501