Risk Management Tools and Techniques

2015 ◽  
pp. 67-107
Keyword(s):  
Risk Management ◽  
Management Tools ◽  
Tools And Techniques

E-Banking Operational Risk Management using Soft Computing Tools

2012 ◽  
pp. 176-202 ◽  
Author(s):  
Rita E Ochuko ◽  
Andrea Cullen ◽  
Daniel Neagu
Keyword(s):  
Risk Management ◽  
Soft Computing ◽  
Fuzzy Inference ◽  
Operational Risk ◽  
Management Tools ◽  
Modeling Tools ◽  
Market Opportunities ◽  
Inference Systems ◽  
Tools And Techniques ◽  
Improved Technology

Electronic banking (E-banking) systems provide a promising solution for breaking geographical, industrial, and regulatory barriers. Improved technology could help with creating anytime, anywhere services and new market opportunities, but does not necessarily ensure a risk-free transaction environment. A main aim for E-banking adopters is to include E-banking risk management to their overall risk management strategy. They must identify the tools and techniques available for managing such risk. In this chapter we provide an overview of E-banking and identify the various risks which exist within the system. The chapter focuses on analyzing state-of-the-art risk management tools and techniques, paying attention to models for internally managing E-banking operational risk. It discusses several soft computing techniques applied to E-banking operational risk as causal modeling tools. The tools include: Decision Trees, Artificial Neural Networks (ANN), Fuzzy Inference Systems, and Bayesian Networks. Some examples are presented to describe the models developed.

Risk Management Practices in Indian Microfinance Sector

2018 ◽  
pp. 1-29
Author(s):  
Ashish Kumar Sana ◽  
Bappaditya Biswas
Keyword(s):  
Risk Management ◽  
Financial Management ◽  
Financial Stability ◽  
Management Practices ◽  
West Bengal ◽  
Microfinance Institutions ◽  
Management Tools ◽  
Operational Risks ◽  
Tools And Techniques ◽  
Structured Questionnaire

Microfinance institutions (MFIs) are exposed to a great number of risks such as institutional risks, operational risks, financial management risks, and external risks that threaten effective services to clients, financial stability, and future sustainability. In this background, the objectives of the chapter are (1) to understand the concept risk and risk management of MFIs and (2) to examine the risk management practices of select MFIs in West Bengal. Based on the objectives, a structured questionnaire has been prepared to examine risk management practices of MFIs and problems associated with implementing risk management tools and techniques. The study found that most of the MFIs have not adopted risk management tools and techniques so far in their institutions to minimize risks. The study also found that the small MFIs are lacking qualified and professional persons in management and hence facing more strategic and governance risks.

scholarly journals The Interplay of Risk Management and Uncertainty: A Project Management Practice Perspective.

2009 ◽  
pp. 74-84
Author(s):  
Claude Besner ◽  
Brian Hobbs
Keyword(s):  
Risk Management ◽  
Project Management ◽  
Management Practices ◽  
Management Practice ◽  
Management Approach ◽  
General Tendency ◽  
Management Tools ◽  
Empirical Perspective ◽  
Contextual Variability ◽  
Tools And Techniques

THE PAPER EMPIRICALLY MEASURES THE INTERPLAY BETWEEN RISK MANAGEMENT AND UNCERTAINTY AND THE CONTEXTUAL VARIABILITY OF RISK MANAGEMENT PRACTICE. THE RESEARCH FIRST CLARIFIES THE CONCEPTS OF UNCERTAINTY, RISK AND RISK MANAGEMENT. THE RESEARCH DEFINES RISK MANAGEMENT FROM AN EMPIRICAL PERSPECTIVE I.E., FROM AN EMPIRICALLY IDENTIFIED SET OF TOOLS THAT IS ACTUALLY USED TO PERFORM RISK MANAGEMENT. THIS TOOLSET IS DERIVED FROM THE RESULTS OF AN ONGOING MAJOR WORLDWIDE SURVEY ON WHAT EXPERIENCED PRACTITIONERS ACTUALLY DO TO MANAGE THEIR PROJECTS. THIS PAPER USES A SAMPLE OF 1,296 RESPONSES FOR WHICH THE INTERPLAY BETWEEN RISK MANAGEMENT AND UNCERTAINTY COULD BE MEASURED. The results are very coherent. They verify and empirically validate many of the propositions drawn from a review of the literature. But results challenge some of the propositions found in the conventional project management literature and some commonly held views. The research shows that the use of risk management practices and tools is negatively related to the degree of project uncertainty. This somewhat counter-intuitive result is consistent with a general tendency for all project management tools and techniques to be used more intensively in better defined contexts. The dominant project management paradigm is oriented towards reducing or controlling uncertainty, but is less well adapted to unforeseeable events and high levels of uncertainty. A better understanding of the reality of the actual practice leads to a discussion about supplementing the current paradigm with new approaches to manage the uncertainty that cannot be removed or reduced by the conventional project management approach.

Design Thinking as a Tool for the Analysis of Project Risks

2019 ◽  
Vol 16 (6) ◽  
pp. 60-77
Author(s):  
E. V. Vasilieva ◽  
T. V. Gaibova
Keyword(s):  
Risk Management ◽  
Risk Analysis ◽  
Design Thinking ◽  
Management Tools ◽  
Project Risk ◽  
Team Members ◽  
Investment Projects ◽  
Risk Management Process ◽  
Project Objectives ◽  
Project Risk Analysis

This paper describes the method of project risk analysis based on design thinking and explores the possibility of its application for industrial investment projects. Traditional and suggested approaches to project risk management have been compared. Several risk analysis artifacts have been added to the standard list of artifacts. An iterative procedure for the formation of risk analysis artifacts has been developed, with the purpose of integrating the risk management process into strategic and prompt decision-making during project management. A list of tools at each stage of design thinking for risk management within the framework of real investment projects has been proposed. The suggested technology helps to determine project objectives and content and adapt them in regards to possible; as well as to implement measures aimed at reducing these risks, to increase productivity of the existing risk assessment and risk management tools, to organize effective cooperation between project team members, and to promote accumulation of knowledge about the project during its development and implementation.The authors declare no conflict of interest.

The Risk-Based Approach to Data Protection

2020 ◽  
Author(s):  
Raphaël Gellert
Keyword(s):  
Risk Management ◽  
Data Protection ◽  
Personal Data ◽  
Management Tools ◽  
General Data Protection Regulation ◽  
Regulation Theory ◽  
Régulation Theory ◽  
General Data ◽  
Data Protection Law ◽  
The Way

The main goal of this book is to provide an understanding of what is commonly referred to as “the risk-based approach to data protection”. An expression that came to the fore during the overhaul process of the EU’s General Data Protection Regulation (GDPR)—even though it can also be found in other statutes under different acceptations. At its core it consists in endowing the regulated organisation that process personal data with increased responsibility for complying with data protection mandates. Such increased compliance duties are performed through risk management tools. It addresses this topic from various perspectives. In framing the risk-based approach as the latest model of a series of regulation models, the book provides an analysis of data protection law from the perspective of regulation theory as well as risk and risk management literatures, and their mutual interlinkages. Further, it provides an overview of the policy developments that led to the adoption of such an approach, which it discusses in the light of regulation theory. It also includes various discussions pertaining to the risk-based approach’s scope and meaning, to the way it has been uptaken in statutes including key provisions such as accountability and data protection impact assessments, or to its potential and limitations. Finally, it analyses how the risk-based approach can be implemented in practice by providing technical analyses of various data protection risk management methodologies.

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