Understanding Model Risk Management -- Model Rationalization in Financial Industry

2015 ◽  
Author(s):  
Hevel Jean-Baptiste ◽  
Lixin Tao ◽  
Meikang Qiu ◽  
Keke Gai
Keyword(s):  
Risk Management ◽  
Management Model ◽  
Financial Industry ◽  
Model Risk

Modelli di business e modelli manageriali della banca. Dal rischio di business model al rischio strategico. Verso una revisione del framework dei rischi bancari?

2020 ◽  
Vol 3 (2020) ◽  
pp. 15-28
Author(s):  
Maurizio Baravelli ◽  
Keyword(s):  
Risk Management ◽  
Business Model ◽  
Planning Process ◽  
Theoretical Framework ◽  
Position Paper ◽  
Management Model ◽  
Model Risk ◽  
Strategic Risk ◽  
Risk Framework

The paper takes up the theoretical aspects that I dealt with in the first part of the AIFIRM-APB position paper, Business Model and SREP: the role of the CRO and the CFO and which I commented on in the Webinar of last July 9th. Starting from a defining framework, I deepen the theme of business model risk and its relationship with strategic risk. And I raise the question of revising the banking risk framework. In particular, I highlight how the business model and strategic risk depend on the management model. At the same time, ample space is dedicated to illustrating how the management model risk influences the sustainability of the business model. I examine the operational implications of the theoretical framework of the business model and propose a review of the business planning process. The purpose of the article is to start a debate with the intervention of risk management specialists above all.

Grid Cyber-Physical System Risk Management Model Based on Cooperative Game Theory

2020 ◽  
Vol 21 (1) ◽  
Author(s):  
Cunbin Li ◽  
Ding Liu ◽  
Yi Wang ◽  
Chunyan Liang
Keyword(s):  
Game Theory ◽  
Risk Management ◽  
Cooperative Game ◽  
Physical System ◽  
Cooperative Game Theory ◽  
Power Grid ◽  
Management Model ◽  
Cyber Physical System ◽  
Model Based ◽  
Generation Power

AbstractAdvanced grid technology represented by smart grid and energy internet is the core feature of the next-generation power grid. The next-generation power grid will be a large-scale cyber-physical system (CPS), which will have a higher level of risk management due to its flexibility in sensing and control. This paper explains the methods and results of a study on grid CPS’s behavior after risk. Firstly, a behavior model based on hybrid automata is built to simulate grid CPS’s risk decisions. Then, a GCPS risk transfer model based on cooperative game theory is built. The model allows decisions to ignore complex network structures. On this basis, a modified applicant-proposing algorithm to achieve risk optimum is proposed. The risk management model proposed in this paper can provide references for power generation and transmission decision after risk as well as risk aversion, an empirical study in north China verifies its validity.

scholarly journals Dynamics of Systems with a Discontinuous Hysteresis Operator and Interval Translation Maps

Axioms ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 80
Author(s):  
Sergey Kryzhevich ◽  
Viktor Avrutin ◽  
Nikita Begun ◽  
Dmitrii Rachinskii ◽  
Khosro Tajbakhsh
Keyword(s):  
Risk Management ◽  
Invariant Measure ◽  
Invariant Measures ◽  
Interval Exchange ◽  
Management Model ◽  
Closing Lemma ◽  
Symbolic Model ◽  
Metric Properties ◽  
Ergodic Measures ◽  
Maximal Invariant

We studied topological and metric properties of the so-called interval translation maps (ITMs). For these maps, we introduced the maximal invariant measure and demonstrated that an ITM, endowed with such a measure, is metrically conjugated to an interval exchange map (IEM). This allowed us to extend some properties of IEMs (e.g., an estimate of the number of ergodic measures and the minimality of the symbolic model) to ITMs. Further, we proved a version of the closing lemma and studied how the invariant measures depend on the parameters of the system. These results were illustrated by a simple example or a risk management model where interval translation maps appear naturally.

Model Risk Management le prassi e il modello a tendere

2021 ◽  
Author(s):  
Rosa Cocozza ◽  
◽  
Marco Boccarussi ◽  
Federrica Guarnieri ◽  
Damiano Pecchini ◽  
...  
Keyword(s):  
Decision Making ◽  
Risk Management ◽  
Model Risk

I modelli hanno assunto un ruolo pervasivo nell’operatività bancaria configurandosi come driver essenziali nel decision making sia in ambito regolamentare che gestionale, e questa considerazione, seppur con caratterizzazioni diverse, risulta valida sia per banche “significant” che “less significant”.

scholarly journals Enterprise Risk Management in Kosovo’s Banking Sector

2017 ◽  
Vol 5 (1) ◽  
pp. 38-50
Author(s):  
Arbana Sahiti ◽  
Arben Sahiti ◽  
Muhamet Aliu
Keyword(s):  
Risk Management ◽  
Financial Reporting ◽  
Banking Sector ◽  
Vital Role ◽  
Main Role ◽  
Financial Industry ◽  
Telephone Interviews ◽  
Enterprise Risk ◽  
Banking Business ◽  
Post War

Abstract Today risk management plays a vital role in business. Each firm, whether big or small, makes an effort to manage risk more effectively. Risk management is very important in the financial system, especially in banks. Billions of Euros are spent each year on the financial reporting of banks. Banks should implement effective solutions in risk management to mitigate their risks. Great financial debate that originated in the 1990s is reportedly linked to errors that occurred in the banking sector due to poor risk management. It should be noted that today technology plays a key role in risk management and it has already had a positive effect on the financial industry. Analysis of risk and its management has become significant in the Kosovo economy since the post-war period. The nature of the banking business is threatened by risks because more financial products are becoming complicated. The main role of banks is intermediation between those who have resources and those seeking them. Banks face various risks at the corporate level, such as operational, liquidity, legal, credit, and market risks; thus, these risks should be converted into a composite measure. This research aims to determine practices and effects of risk management in the banking sector. Relevant data were collected from banks through questionnaires and telephone interviews; analysis has been conducted using statistical tools. This study will engage both the quantitative and qualitative methods of data analysis. Dependent variables will be separated from independent variables, and regression analysis will be used to analyse the quantitative data.

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