Verification of Barrierboard Over-pressure Withstand Capability and Transformer Operational Risk Mitigation by an Explosion Experiment

2020 ◽  
Author(s):  
Lie Xiao ◽  
Christoph Krause ◽  
Balz Schlittler ◽  
Ivica Cukor
Keyword(s):  
Risk Mitigation ◽  
Operational Risk ◽  
Explosion Experiment

scholarly journals A Behavioral Probabilistic Risk Assessment Framework for Managing Autonomous Underwater Vehicle Deployments

2012 ◽  
Vol 29 (11) ◽  
pp. 1689-1703 ◽  
Author(s):  
Mario Brito ◽  
Gwyn Griffiths ◽  
James Ferguson ◽  
David Hopkin ◽  
Richard Mills ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Autonomous Underwater Vehicle ◽  
Risk Mitigation ◽  
Operational Risk ◽  
Maximum Error ◽  
Underwater Vehicle ◽  
Behavioral Approach ◽  
Mitigation Measures ◽  
The Arctic ◽  
Deep Diving

Abstract The deployment of a deep-diving long-range autonomous underwater vehicle (AUV) is a complex operation that requires the use of a risk-informed decision-making process. Operational risk assessment is heavily dependent on expert subjective judgment. Expert judgments can be elicited either mathematically or behaviorally. During mathematical elicitation experts are kept separate and provide their assessment individually. These are then mathematically combined to create a judgment that represents the group view. The limitation with this approach is that experts do not have the opportunity to discuss different views and thus remove bias from their assessment. In this paper, a Bayesian behavioral approach to estimate and manage AUV operational risk is proposed. At an initial workshop, behavioral aggregation, that is, reaching agreement on the distributions of risks for faults or incidents, is followed by an agreed upon initial estimate of the likelihood of success of the proposed risk mitigation methods. Postexpedition, a second workshop assesses the new data and compares observed to predicted risk, thus updating the prior estimate using Bayes’ rule. This feedback further educates the experts and assesses the actual effectiveness of the mitigation measures. Applying this approach to an AUV campaign in ice-covered waters in the Arctic showed that the maximum error between the predicted and the actual risk was 9% and that the experts’ assessments of the effectiveness of risk mitigation led to a maximum of 24% in risk reduction.

scholarly journals Financial Risk Management and Profitability of Deposit Taking Savings and Credit Cooperative Societies in Nyeri County, Kenya

2020 ◽  
Vol 2 (2) ◽  
pp. 1-20
Author(s):  
Margaret Gakenia Kinyua ◽  
Fredrick Warui
Keyword(s):  
Risk Management ◽  
Data Collection ◽  
Financial Risk ◽  
Risk Mitigation ◽  
Pearson Correlation ◽  
Risk Control ◽  
Liquidity Risk ◽  
Operational Risk ◽  
Financial Risk Management ◽  
Study Approach

Profitability is a key aspect of organization financial performance. Kenya SACCOs have been rated fastest growing SACCOs in Africa. However, this growth is largely attributed to growth in membership and penetration. On the other hand the sub sector has recorded irregular trend on the profitability over the last half a decade. Though past literature has tried to link financial risk management to profitability levels, a range of knowledge gaps remain undressed. The current study therefore sought to establish the effect of financial risk management on profitability targeting deposit-taking SACCOs in Nyeri County. To address this objective, the study targeted the following specific objectives; to examine the effect of credit mitigation, liquidity risk controls operational risk mitigation and finally compliance risk mitigation on profitability of deposit taking SACCOs in Nyeri County. Descriptive study design adopted targeting a population of 8 deposit-taking SACCOs. A census study approach was used to subject all the SACCOs to study. The respondents comprised of deposit taking SACCO managers or operational manager. Thus, in total, the study targeted 8 respondents from the management of the SACCOs. Questionnaires were adopted as a tool for data collection. The researcher administered questionnaires to the respondents by dropping to the respondent office and collected at convenient date agreed by both parties. Before undertaking the study, the researcher conducted a reliability test to assess the consistency of the tool using Cronbach’s Alpha. The study used descriptive and inferential statistic in summarizing the data. Under descriptive statistics, the researcher used mean and standard deviation. To test the significance of study variables, the researcher used Pearson correlation and simple linear regressions. The researcher adhered to research ethic during data collection period. The study findings are presented in charts and tables. The study found compliance risk control; liquidity risk control and operational risk control had significant effect on the performance of Saccos in Nyeri while credit risk control was found insignificant in predicting performance of Saccos in Nyeri County. The study recommends Saccos to intensify the compliance risk control, liquidity risk control and the operational risk control practices in enhancement of Sacco’s performance.  

scholarly journals The Role of Insurance in Operational Risk Mitigation - A Case Study

2012 ◽  
Vol 60 (4) ◽  
pp. 523-535 ◽  
Author(s):  
Milan Rippel ◽  
Lucie Suchánková ◽  
Petr Teplý
Keyword(s):  
Risk Mitigation ◽  
Operational Risk

scholarly journals Supply chain operational risk mitigation: a collaborative approach

2013 ◽  
Vol 51 (7) ◽  
pp. 2186-2199 ◽  
Author(s):  
Jie Chen ◽  
Amrik S. Sohal ◽  
Daniel I. Prajogo
Keyword(s):  
Supply Chain ◽  
Risk Mitigation ◽  
Operational Risk ◽  
Collaborative Approach

A Composite Risk Model for Railroad Operations Utilizing Positive Train Control (PTC)

2014 ◽  
Author(s):  
Andre’ Abadie ◽  
Damindra Bandara ◽  
Duminda Wijesekera
Keyword(s):  
Cyber Security ◽  
Risk Model ◽  
Risk Mitigation ◽  
Operational Risk ◽  
Security Risk ◽  
Dynamic Configuration ◽  
Train Control ◽  
Novel Approach ◽  
Positive Train Control ◽  
Composite Risk

This paper proposes a novel approach for composite risk management of rail operations incorporating operational risk computed by the rail industry and cyber security risk introduced due to Positive Train Control (PTC). The suggested risk model focuses on a given train location to estimate likelihood of the PTC system failing by considering environmental risk factors (precipitation, vegetation, obstacles) and the inherent vulnerability of the radio frequency — yielding a measure of system impact. For the same location, the risk model considers safety related attributes such as train speed, track curvature, freight type, etc. — offering an estimate of operational consequence if there were an accident due to the failure of PTC. It is this intersection of impact / consequence that separates the proposed model from existing risk calculations of impact / likelihood. This is accomplished by distinguishing the likelihood of a safety accident from the likelihood of a PTC system failure — and incorporating them both. What results is an enhancement of both models; the operational risk model factors potential PTC failure in its risk assessment and gains awareness of possible requirements for operator intervention while the system risk model factors operational risk as its severity metric leading to possible requirements for automated risk mitigation by dynamic configuration change to the PTC radio.

Part A Regulatory Matters, 6 Capital Adequacy, Liquidity, and Large Exposures

2015 ◽  
Author(s):  
Proctor Charles
Keyword(s):  
Credit Risk ◽  
Risk Mitigation ◽  
Banking System ◽  
Operational Risk ◽  
Market Risk ◽  
Capital Adequacy ◽  
Mitigation Techniques ◽  
The Stability ◽  
Basel 3

This chapter examines the current capital adequacy framework and associated provisions designed to ensure that a bank's business is managed on a prudent basis. It also considers other closely allied topics which may affect the stability of the banking system, namely, liquidity and large exposure requirement. Topics discussed include the origins of the Basel Standards; Basel 2 and Basel 3 rules; the calculation of risk-weighted assets; the nature and effect of credit risk mitigation techniques; market risk; operational risk; and reform on Basel 2.

scholarly journals Good practice guide to setting inputs for operational risk models

2016 ◽  
Vol 22 (1) ◽  
pp. 68-108 ◽  
Author(s):  
P. O. J. Kelliher ◽  
M. Acharyya ◽  
A. Couper ◽  
K. Grant ◽  
E. Maguire ◽  
...  
Keyword(s):  
Scenario Analysis ◽  
Risk Mitigation ◽  
Good Practice ◽  
Operational Risk ◽  
Capital Allocation ◽  
Solvency Ii ◽  
Service Firms ◽  
Risk Models ◽  
Operational Risks ◽  
Loss Data

AbstractThis paper seeks to establish good practice in setting inputs for operational risk models for banks, insurers and other financial service firms. It reviews Basel, Solvency II and other regulatory requirements as well as publicly available literature on operational risk modelling. It recommends a combination of historic loss data and scenario analysis for modelling of individual risks, setting out issues with these data, and outlining good practice for loss data collection and scenario analysis. It recommends the use of expert judgement for setting correlations, and addresses information requirements for risk mitigation allowances and capital allocation, before briefly covering Bayesian network methods for modelling operational risks.

scholarly journals ANALISIS TEKNIK MITIGASI RISIKO PRODUK TAKE OVER KPR PADA BANK PANIN DUBAI SYARIAH CABANG SURABAYA

2020 ◽  
Vol 7 (6) ◽  
pp. 1074
Author(s):  
Firly Aulia Alhimnie ◽  
Dina Fitrisia Septiarini
Keyword(s):  
Credit Risk ◽  
Qualitative Case Study ◽  
Risk Mitigation ◽  
Secondary Data ◽  
Operational Risk ◽  
Primary Data ◽  
Financial Report ◽  
Mitigation Technique ◽  
Descriptive Qualitative

This research aims to determine the risk mitigation technique for home financing takeover-funded products. The method used for this research is descriptive qualitative-case study. The data gained from this research is a primary data from an interview with three sources from Panin Dubai Sharia bank, and a secondary data of documentation and financial report of Panin Dubai Sharia Bank. The result of this research is Panin Dubai Sharia bank used reduction mitigation technique either on credit risk or operational risk. On the operational risk, Panin Dubai Sharia bank prepared document takeover and properties takeover further before the contract is done, and implementing Take over Operational Day only on Monday and Thursday. Meanwhile, for credit risk, Panin Dubai Sharia Bank used 4 kinds of systems such as backup of credentials, guarantees, internal ratings, computer models.Keywords: Mitigation, Risk, Take Over, KPR

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