Narrow Results

Bank risk management is a crucial issue in the stability of the financial system. How to select high-risk factors that make banks in trouble and how these factors affect bank risks have always been a core problem. Previous studies comprehensively identified bank risk factors from textual risk disclosures and used the disclosure frequency of risk factors to determine important factors to which banks should pay more attention. This paper creatively constructs the textual risk matrix with frequency and sentiment of risk factors to divide bank risk factors into the high-risk category, mid-risk category, and low-risk category. Then we explore the impact of different categories of risk factors on bank risk and the risk perception of investors. Based on 457,383 sentences of 2,735 Form 10-K reports of 240 American commercial banks from 2006 to 2020, 33 bank risk factors were identified. Three risk factors belong to in high-risk category, including loan loss risk, regulation risk, and interest rate risk. Three factors are classified in the mid-risk category and 27 risk factors are low-risk factors. The regression results show that compared with individual bankruptcy risk, risk factors have better prediction and interpretive ability on the systemic risk. The disclosure of bank risk factors will affect the investors’ risk perception, especially the worse risk situation of the high-risk factors will increase the risk perceived by investors.

Risk matrices are adopted and recommended by many organizations, but the way they are usually constructed violates some basic theoretical principles, giving rise to inconsistent risk ratings. This paper studies ways in which multiple criteria and portfolio decision analyses can improve the design and deployment of risk matrices, using MACBETH (the “Measuring Attractiveness by a Categorical Based Evaluation TecHnique”). Firstly, it introduces ‘value risk-matrices’, built with MACBETH in the following modeling steps: (1) building a value measurement scale on each impact dimension and constructing a subjective probability scale, (2) additive aggregation of the value scales into a cumulative value scale, and (3) design of the value risk-matrix. The value and probability scores of risks are plotted in the matrix and its analysis informs the identification of mitigation actions, which can then be prioritized making use of the recent portfolio module of the MACBETH decision support system. Taken all together, the paper sketches a new modeling approach for Improving Risk Matrice s (IRIS).

Small and medium-sized enterprises (SMEs) are the spine of the European economy and play a key role in adding value in all sectors of the economy. However, due to a lack of methodology and time, SME entrepreneurs struggle to formalize their strategies and too often remain ill-prepared to face today’s potential crises. This paper aims to propose a Risk Management (RM) tool to identify and assess the impact of risks on specific business strategic dimensions. The hypotheses and robustness of the model are tested using Monte Carlo simulation. The analysis shows that a reduced strategic risk matrix (size $4\times 4$) could provide the same quality of information as a full strategic risk matrix (size $20\times 10$) in about 80% of the cases, regardless of the weight of each criterion and the values of each risk factor. The results extend the limited use of RM tool in the field of SME Risk Management.

Every year flooding and landslides cause severe material damages and thousands of deaths and injuries. To reduce the risk, measures can be taken by applying different management strategies either by reducing the probability of the event or by reducing the potential consequences in case of an event. This chapter provides a systematic (step-by-step) guidance, a brief overview of landslide and flood risk management in general and a summary of an investigation of the present risk management situation in Sweden which has resulted in some general recommendations. Examples of general recommendations are to apply available knowledge, for example by learning from existing good examples and, when available, lessons learned and documentation of the rational argumentation made in the decision process. There is a request of checklists and guides that can be used in the current daily work among planners and risk managers. It is important with a broad basis for decisions, therefore integrated assessments and valuations are recommended for example by applying multi-criteria analysis methodology and involving relevant stakeholders in the process for example through well working networks. It is further important to counteract the current trend that more automatic monitoring results in less field monitoring and reduced local knowledge.