Interdisciplinary Aspects of Cost-Risk Tradeoffs

OCEANS 2006 ◽  
2006 ◽  
Author(s):  
Peter Marshall
Keyword(s):  
Cost Risk ◽  
Risk Tradeoffs

Medical treatment decisions: Individual differences in risk tradeoffs

1998 ◽  
Author(s):  
Andrea L. Washburne ◽  
Sandra L. Schneider ◽  
Teresa Broughton
Keyword(s):  
Individual Differences ◽  
Medical Treatment ◽  
Treatment Decisions ◽  
Risk Tradeoffs

scholarly journals Modeling of Bank Credit Risk Management Using the Cost Risk Model

2021 ◽  
Vol 14 (5) ◽  
pp. 211
Author(s):  
Iryna Yanenkova ◽  
Yuliia Nehoda ◽  
Svetlana Drobyazko ◽  
Andrii Zavhorodnii ◽  
Lyudmyla Berezovska
Keyword(s):  
Risk Management ◽  
Decision Support ◽  
Credit Risk ◽  
Risk Model ◽  
Bank Credit ◽  
Credit Risk Management ◽  
Loan Default ◽  
Increased Risk ◽  
Credit Portfolio ◽  
Cost Risk

This article deals with the issue of managing bank credit risk using a cost risk model. Modeling of bank credit risk management was proposed based on neural-cell technologies, which expand the possibilities of modeling complex objects and processes and provide high reliability of credit risk determination. The purpose of the article is to improve and develop methodical support and practical recommendations for reducing the level of risk based on the value-at-risk (VaR) methodology and its subsequent combination with methods of fuzzy programming and symbiotic methodical support. The model makes it possible to create decision support subsystems for nonperforming loan management based on the neuro-fuzzy approach. For this paper, economic and mathematical tools (based on the VaR methodology) were used, which made it possible to analyze and forecast the dynamics of overdue payment; assess the quality of the credit portfolio of the bank; determine possible trends in bank development. A scientific and practical approach is taken to assess and forecast the degree of credit problematicity by qualitative criteria using a mathematical model based on a fuzzy technology, which can forecast the increased risk of loan default at an early stage in the process of monitoring the loan portfolio and model forecasting changes in the degree of credit problematicity on change of indicators. A methodology is proposed for the analysis and forecasting of indicators of troubled loan debt, which should be implemented as software and included in the decision support system during the process of monitoring the risk of the bank’s credit portfolio.

scholarly journals Cost risk benefit analysis to support chemoprophylaxis policy for travellers to malaria endemic countries

2011 ◽  
Vol 10 (1) ◽  
Author(s):  
Eduardo Massad ◽  
Ben C Behrens ◽  
Francisco AB Coutinho ◽  
Ronald H Behrens
Keyword(s):  
Benefit Analysis ◽  
Risk Benefit Analysis ◽  
Cost Risk

Scenario based evaluation of a cost risk model through sensitivity analysis

2015 ◽  
Vol 22 (4) ◽  
pp. 403-423 ◽  
Author(s):  
Önder Ökmen ◽  
Ahmet Öztaş
Keyword(s):  
Risk Factors ◽  
Risk Analysis ◽  
Risk Model ◽  
Practical Method ◽  
Cost Evaluation ◽  
Sensitivity Analyses ◽  
Analysis Model ◽  
Content Type ◽  
Detailed Evaluation ◽  
Cost Risk

Purpose – Actual costs frequently deviate from the estimated costs in either favorable or adverse direction in construction projects. Conventional cost evaluation methods do not take the uncertainty and correlation effects into account. In this regard, a simulation-based cost risk analysis model, the Correlated Cost Risk Analysis Model, previously has been proposed to evaluate the uncertainty effect on construction costs in case of correlated costs and correlated risk-factors. The purpose of this paper is to introduce the detailed evaluation of the Cost Risk Analysis Model through scenario and sensitivity analyses. Design/methodology/approach – The evaluation process consists of three scenarios with three sensitivity analyses in each and 28 simulations in total. During applications, the model’s important parameter called the mean proportion coefficient is modified and the user-dependent variables like the risk-factor influence degrees are changed to observe the response of the model to these modifications and to examine the indirect, two-sided and qualitative correlation capturing algorithm of the model. Monte Carlo Simulation is also applied on the same data to compare the results. Findings – The findings have shown that the Correlated Cost Risk Analysis Model is capable of capturing the correlation between the costs and between the risk-factors, and operates in accordance with the theoretical expectancies. Originality/value – Correlated Cost Risk Analysis Model can be preferred as a reliable and practical method by the professionals of the construction sector thanks to its detailed evaluation introduced in this paper.

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