Component level risk assessment in Grids: A probablistic risk model and experimentation

2011 ◽  
Author(s):  
Asif Sangrasi ◽  
Karim Djemame
Keyword(s):  
Risk Assessment ◽  
Risk Model ◽  
Component Level

A CONDITIONAL EQUITY RISK MODEL FOR REGULATORY ASSESSMENT

2018 ◽  
Vol 49 (1) ◽  
pp. 217-242
Author(s):  
A. Floryszczak ◽  
J. Lévy Véhel ◽  
M. Majri
Keyword(s):  
Risk Assessment ◽  
Risk Model ◽  
Capital Requirements ◽  
Market Failures ◽  
Equity Prices ◽  
Equity Risk ◽  
Solvency Capital ◽  
Functional Differential ◽  
Stochastic Functional

AbstractWe define and study in this work a simple model designed for managing long-term market risk of financial institutions with long-term commitments. It allows the assessment of solvency capital requirements and the allocation of risk budgets. This model allows one to avoid over-assessment of solvency capital requirements specifically after market disruptions. It relies on a dampener component in charge of refining risk assessment after market failures. Rather than aiming at a realistic and thus complex description of equity prices movements, this model concentrates on minimal features enabling accurate computation of capital requirements. It is defined both in a discrete and continuous fashion. In the latter case, we prove the existence, uniqueness and stability of the solution of the stochastic functional differential equation that specifies the model. One difficulty is that the proposed underlying stochastic process has neither stationary nor independent increments. We are however able to perform statistical analyses in view of its validation. Numerical experiments show that our model outperforms more elaborate ones of common use as far as medium-term (between 6 months and 5 years) risk assessment is concerned.

An Evaluation of a Test-Driven Security Risk Analysis Approach Based on Two Industrial Case Studies

2019 ◽  
pp. 69-103 ◽  
Author(s):  
Gencer Erdogan ◽  
Phu H. Nguyen ◽  
Fredrik Seehusen ◽  
Ketil Stølen ◽  
Jon Hofstad ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Case Studies ◽  
Risk Model ◽  
Case Study Research ◽  
Security Risk ◽  
Risk Models ◽  
First Case ◽  
Assessment Approach ◽  
Security Risk Assessment

Risk-driven testing and test-driven risk assessment are two strongly related approaches, though the latter is less explored. This chapter presents an evaluation of a test-driven security risk assessment approach to assess how useful testing is for validating and correcting security risk models. Based on the guidelines for case study research, two industrial case studies were analyzed: a multilingual financial web application and a mobile financial application. In both case studies, the testing yielded new information, which was not found in the risk assessment phase. In the first case study, new vulnerabilities were found that resulted in an update of the likelihood values of threat scenarios and risks in the risk model. New vulnerabilities were also identified and added to the risk model in the second case study. These updates led to more accurate risk models, which indicate that the testing was indeed useful for validating and correcting the risk models.

Assessing the Usefulness of Testing for Validating and Correcting Security Risk Models Based on Two Industrial Case Studies

2016 ◽  
pp. 1016-1037
Author(s):  
Gencer Erdogan ◽  
Fredrik Seehusen ◽  
Ketil Stølen ◽  
Jon Hofstad ◽  
Jan Øyvind Aagedal
Keyword(s):  
Risk Assessment ◽  
Case Studies ◽  
Web Application ◽  
Risk Model ◽  
Security Risk ◽  
Risk Models ◽  
First Case ◽  
New Information ◽  
Financial Application

The authors present the results of an evaluation in which the objective was to assess how useful testing is for validating and correcting security risk models. The evaluation is based on two industrial case studies. In the first case study the authors analyzed a multilingual financial Web application, while in the second case study they analyzed a mobile financial application. In both case studies, the testing yielded new information which was not found in the risk assessment phase. In particular, in the first case study, new vulnerabilities were found which resulted in an update of the likelihood values of threat scenarios and risks in the risk model. New vulnerabilities were also identified and added to the risk model in the second case study. These updates led to more accurate risk models, which indicate that the testing was indeed useful for validating and correcting the risk models.

Credit risk assessment using purchase order information

2018 ◽  
Vol 05 (04) ◽  
pp. 1850041
Author(s):  
Suguru Yamanaka
Keyword(s):  
Risk Assessment ◽  
Credit Risk ◽  
Financial Institutions ◽  
High Frequency ◽  
Risk Model ◽  
Financial Statements ◽  
Order Information ◽  
Purchase Order ◽  
Credit Risk Assessment ◽  
Business Conditions

This paper proposes advanced credit risk assessment and lending operations using purchase order information from borrower firms. Purchase order information from a borrower firm is useful for financial institutions to evaluate the actual business conditions of the firm. This paper shows the application of purchase order information to lending operations and credit risk assessment, and reveals its effectiveness. First, we propose a “purchase order based” credit risk model for real-time credit risk monitoring of firms. Financial institutions can monitor the actual business conditions of borrower firms by evaluating the firm’s asset value using purchase order information. A combination of traditional firm monitoring using financial statements and high-frequency monitoring using purchase order information enables financial institutions to assess the business conditions of borrower firms more precisely and efficiently. Then, with high-frequency data, financial institutions can give borrower firms appropriate support if necessary on a timely basis. Second, we illustrate purchase order financing, which is the lending method backed by purchase order information from borrowers. With purchase order financing, firms that consistently receive purchase orders from credit-worthy firms can borrow money under more favorable lending terms than the usual lending terms based on the financial statements of the borrower firm.

An Evaluation of the Utility of the Breast Reconstruction Risk Assessment Score Risk Model in Prepectoral Tissue Expander Breast Reconstruction

2020 ◽  
Vol 84 ◽  
pp. S318-S322 ◽  
Author(s):  
Shanique Martin ◽  
Elizabeth Turner ◽  
Alan Nguyen ◽  
Brian Thornton ◽  
Rahim S. Nazerali
Keyword(s):  
Risk Assessment ◽  
Breast Reconstruction ◽  
Risk Model ◽  
Tissue Expander ◽  
Assessment Score ◽  
Score Risk

scholarly journals The Houston Methodist Lung Transplant Risk Model: A Validated Tool for Pretransplant Risk Assessment

2019 ◽  
Vol 108 (4) ◽  
pp. 1094-1100 ◽  
Author(s):  
Edward Y. Chan ◽  
Duc T. Nguyen ◽  
Thomas S. Kaleekal ◽  
Ahmad Goodarzi ◽  
Edward A. Graviss ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Lung Transplant ◽  
Risk Model

Enhanced Leak Detection Risk Model Development

2010 ◽  
Author(s):  
Lorna Harron ◽  
Rick Barlow ◽  
Ted Farquhar
Keyword(s):  
Risk Assessment ◽  
Risk Model ◽  
Risk Mitigation ◽  
Detection System ◽  
Leak Detection ◽  
Mitigation Strategies ◽  
Assessment Model ◽  
Flow Meter ◽  
The Matrix ◽  
Risk Mitigation Strategies

Increasing concerns and attention to pipeline safety have engaged pipeline companies and regulatory agencies to extend their approaches to pipeline integrity. The implementation of High Consequence Areas (HCAs) has in particular had an impact on the development of integrity management protocols (IMPs) for pipelines. These IMPs can require that a risk based assessment of integrity issues be applied to specific HCA risk factors. This paper addresses the development of an operational risk assessment approach for pipeline leak detection requirements for HCAs. A detailed risk assessment algorithm that includes 25 risk variables and 28 consequence variables was developed for application to all HCA areas. The significant likelihood and consequence factors were chosen through discussions with the Leak Detection Risk Assessment Model Working Group and subject matter experts throughout Enbridge. The leak detection algorithm focuses on sections of pipe from flow meter to flow meter, as these are the locations that impact the leak detection system used by Enbridge. Each section of pipe is evaluated for likelihood, consequence and risk. When a high or medium risk area has been identified, an evaluation of potential Preventive and Mitigative (P&M) measures will be undertaken. A P & M Matrix has been developed to identify potential mitigation strategies to be considered for higher risk variables, called risk drivers, in the model. The matrix has been developed to identify potential risk mitigation strategies to consider for each variable used in the HCA Leak Detection Risk Assessment. The purpose of the matrix is to guide the user to consider actions identified for variables that drive the risk for the particular location. Upon review of the matrix, the user determines feasibility of the risk mitigation strategies being considered to identify an action. The paper will describe the consultative process that was used to workshop the development of this algorithm. Included in this description is how the process addressed various methods of leak detection across a wide variety of pipelines. The paper closes with “development challenges” and future steps in applying operation risk assessment techniques to mainline leak detection risk management.

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