La gestión del riesgo operacional en la banca chilena

Oikos ◽  
2016 ◽  
Vol 19 (40) ◽  
pp. 47
Author(s):  
Cristian Muñoz Anziani ◽  
Alex Medina Giacomozzi
Keyword(s):  
Risk Management ◽  
Standard Model ◽  
Operational Risk ◽  
Bank Regulation ◽  
Optimal Management ◽  
Management Tools ◽  
Operational Risks ◽  
The Standard Model ◽  
Potential Losses

RESUMENEste artículo tiene como objetivo presentar las herramientas de gestión fundamentales que permitan una administración óptima de los riesgos operacionales, con el fin de mitigar las eventuales pérdidas, en los bancos, derivadas de este riesgo. La utilización de distintas herramientas de administración permite identificar, medir, controlar y monitorear los riesgos operacionales. El modelo estándar presentado, deja espacio para adaptaciones de acuerdo a la necesidad específica de la entidad financiera.Palabras clave: riesgo, Basilea, riesgo operacional, regulación bancaria, sistema financiero.Operational risk management in the chilean banking ABSTRACTThis article aims to present fundamental management tools that enable optimal management of operational risks, in order to mitigate potential losses, banks, derivative risk. The utilization of these tools incorporated as a whole, allows to identifying, measure, monitoring and controlling operational risks. The standard model presented, leaves room for adjustments according to the specific needs of the financial institution.Keywords: risk, Basilea, operational risk, bank regulation, banking system.A gestão do risco operacional no sistema bancário chilenoRESUMOEste artigo tem como objetivo apresentar as ferramentas fundamentais de gestão que permitam uma óptima administração dos riscos operacionais, a fim de mitigar as eventuais perdas nos bancos, resultado destes riscos. O uso de diferentes ferramentas de administração permite identificar, medir, controlar e monitorar os riscos operacionais. O modelo standard apresentado deixa o espaço para ajustes de acordo com a necessidade específica da entidade financeira.Palavras-chave: risco, Basilea, risco operacional, regulamentação bancária, sistema financeiro.

scholarly journals Estimation of Maximum Potential Losses for Digital Banking Transaction Risks Using the Extreme Value-at-Risks Method

Risks ◽  
2022 ◽  
Vol 10 (1) ◽  
pp. 10
Author(s):  
Moch Panji Agung Saputra ◽  
Sukono ◽  
Diah Chaerani
Keyword(s):  
Risk Management ◽  
Operational Risk ◽  
Threshold Value ◽  
System Failures ◽  
Operational Risks ◽  
Data Value ◽  
Kolmogorov Smirnov ◽  
Potential Risks ◽  
Potential Losses ◽  
Financial Transactions

The application of industry 4.0 in banking presents many challenges, with several operational risks related to downtime and timeout services due to system failures. One of the operational risk management steps is to estimate the value of the maximum potential losses. The purpose of this study is to estimate the maximum potential losses for digital banking transaction risks. The method used for estimating risks is the EVaR method. There are several steps in this study. The first step is to resample the data using MEBoot. This process is a simulation of the operational risk loss data of digital banking. Next, the threshold value is determined to obtain the extreme data value. Then, a Kolmogorov–Smirnov test is conducted to fit the data with the GPD. Afterward, the GPD parameter is estimated. Then, EVaR is calculated using a portfolio approach to obtain a combination of risk values as maximum potential losses. The analysis results show that the maximum potential loss is IDR144,357,528,750.94. The research results imply that the banks need to pay attention to the maximum potential losses of digital financial transactions as a reference for risk management. Therefore, banks can anticipate the adequacy of reserve funds for these potential risks.

scholarly journals Operational risk quantification and modelling within Romanian insurance industry

2017 ◽  
Vol 11 (1) ◽  
pp. 637-648
Author(s):  
Răzvan Tudor ◽  
Dumitru Badea
Keyword(s):  
Standard Model ◽  
Insurance Industry ◽  
Operational Risk ◽  
Solvency Ii ◽  
Capital Requirements ◽  
Capital Requirement ◽  
Risk Capital ◽  
Operational Risks ◽  
The Standard Model ◽  
Solvency Capital

Abstract This paper aims at covering and describing the shortcomings of various models used to quantify and model the operational risk within insurance industry with a particular focus on Romanian specific regulation: Norm 6/2015 concerning the operational risk issued by IT systems. While most of the local insurers are focusing on implementing the standard model to compute the Operational Risk solvency capital required, the local regulator has issued a local norm that requires to identify and assess the IT based operational risks from an ISO 27001 perspective. The challenges raised by the correlations assumed in the Standard model are substantially increased by this new regulation that requires only the identification and quantification of the IT operational risks. The solvency capital requirement stipulated by the implementation of Solvency II doesn’t recommend a model or formula on how to integrate the newly identified risks in the Operational Risk capital requirements. In this context we are going to assess the academic and practitioner’s understanding in what concerns: The Frequency-Severity approach, Bayesian estimation techniques, Scenario Analysis and Risk Accounting based on risk units, and how they could support the modelling of operational risk that are IT based. Developing an internal model only for the operational risk capital requirement proved to be, so far, costly and not necessarily beneficial for the local insurers. As the IT component will play a key role in the future of the insurance industry, the result of this analysis will provide a specific approach in operational risk modelling that can be implemented in the context of Solvency II, in a particular situation when (internal or external) operational risk databases are scarce or not available.

scholarly journals How Can Enterprise Risk Management Help in Evaluating the Operational Risks for a Telecommunications Company?

2021 ◽  
Vol 14 (3) ◽  
pp. 139
Author(s):  
José Ruiz-Canela López
Keyword(s):  
Risk Management ◽  
Banking Sector ◽  
Operational Risk ◽  
Field Work ◽  
Risk Identification ◽  
Enterprise Risk Management ◽  
Management Tool ◽  
Self Assessment ◽  
Operational Risks ◽  
Enterprise Risk

Operational risk is defined as the potential losses resulting from events caused by inadequate or failed processes, people, equipment, and systems or from external events. One of the most important challenges for the management of the company is to improve its results through its operational risk identification and evaluation. Most of Enterprise Risk Management (ERM) scholarship has roots in the finance/risk management and insurance (RMI) discipline, mainly in the banking sector. This study proposes an innovative operational risk assessment methodology (OpRAM), to evaluate operational risks focused on telecommunications companies (TELCOs), on the basis of an operational risk self-assessment (OpRSA) process and method. The OpRSA process evaluates operational risks through a quantitative analysis of estimates which inputs are the economic impact and the probability of occurrence of events. The OpRSA method is the “engine” for calculating the economic risk impact, applying actuarial techniques, which allow estimation of unexpected losses and expected losses distributions in a TELCO. The results of the analyzed business unit in the field work were compared with standardized ratings (acceptable, manageable, critical, or catastrophic), and contrasted against the company’s managers, proving that the OpRSA framework is a reliable and useful management tool for the business, and leading to more research in other sectors where operational risk management is key for the company success.

Full-Scale Validation of a Vessel’s Station-Keeping Capability With DynCap

2017 ◽  
Author(s):  
Luca Pivano ◽  
Dong Nguyen ◽  
Øyvind Smøgeli
Keyword(s):  
Time Domain ◽  
Scale Validation ◽  
Operational Risk ◽  
Full Scale ◽  
Management Tools ◽  
Worst Case ◽  
Operational Risks ◽  
Steady Growth ◽  
Transient Period ◽  
Key Aspects

With the steady growth of the number of Dynamic Positioning (DP) vessels, increasingly complex designs and operations, and a decreasing number of experienced DP operators, effective operational risk management tools are key for safer and more efficient operations. One of the key aspects when looking at the operational risks is the estimation of the vessel position and heading after the worst case single failure and in the transient period after the failure has occurred. The aim of this paper is to provide insight about the use of comprehensive dynamic operability analyses performed by time-domain simulations for understanding the vessel performance and limitations, in turn providing valuable and reliable input to operational risk assessment and planning. This paper presents also a comparison with results from full-scale trials.

scholarly journals Roles and responsibilities for managing operational risk in a banking environment

2008 ◽  
Vol 5 (3) ◽  
pp. 34-46
Author(s):  
Jackie Young
Keyword(s):  
Risk Management ◽  
Operational Risk ◽  
Main Role ◽  
Banking Supervision ◽  
Operational Risk Management ◽  
Roles And Responsibilities ◽  
Global Institutions ◽  
Basel Committee ◽  
Operational Risks ◽  
Role Players

Operational risk management is one of the fastest growing management disciplines within a banking environment as a result of various disastrous international incidents. Subsequently, various global institutions got involved in order to ensure that the effect of similar events do not negatively influence the international industries, for example, the Basel Committee on Banking Supervision regarding banks. It is, however, a known fact that operational risks are difficult to manage, as it is not easy to quantify. Therefore, it is of the utmost importance to understand the concept of operational risk management and, more specifically, the actual roles and responsibilities of various role-players within an organisation. This paper aims to identify the main role-players involved in the management of operational risk in a banking environment and to identify their specific roles and responsibilities

scholarly journals Operational Risk Management in A Commercial Bank

2018 ◽  
Vol 7 (4.36) ◽  
pp. 524
Author(s):  
I. I.Vasiliev ◽  
P. A. Smelov ◽  
N. V. Klimovskih ◽  
M. G. Shevashkevich ◽  
E. N. Donskaya
Keyword(s):  
Risk Management ◽  
Development Strategy ◽  
Commercial Bank ◽  
Operational Risk ◽  
Strong Impact ◽  
Credit Institution ◽  
Operational Risk Management ◽  
Operational Risks ◽  
Empirical Level ◽  
Analysis And Synthesis

The existing financial and economic situation in the world and in Russia impacts the activities of all sectors of the economy, including posing challenges for banks. In the conditions of prolonged instability, the banking community has to pay great attention to the risks taken and to manage them. Among all the risks that the bank is exposed to, operational risks represent a separate group due to its specifics, a lack of a systematic approach to analysis and a lack of identification criteria requiring more detailed study. The operational risk is unique in that, although it affects virtually all areas of the credit institution, it is difficult to establish and separate it from other bank risks. It should be noted that every year there appear all new types of operational risk that have a strong impact on the activities of the credit institution due to the development of information and computer systems, the complication of the instruments of the stock market and the improvement of business methods. Therefore, regulators of all countries try to constantly improve the regulatory framework related to the management of the operational risk of a commercial bank, based on the recommendations given by the Basel Committee on Banking Supervision.The article is aimed at developing an effective system for managing the operational risk of a commercial bank.The empirical level research methods used in this article are a description of what operational risk is, its types, tools and methods of assessment; comparison of operational risk management systems in the studied banks; generalization, analysis and synthesis of the information received; the hypothetical-deductive method is used at the theoretical level.Modernization and improvement of the operational risk management system helps stabilize the bank, increase stability and increase profitability, reduce the provision of capital for operational risk, and increase the attractiveness of banking services for consumers, thus benefiting a credit institution among competitors. In today's financial environment, the effective operational risk management is inherent in the long-term development strategy. 

scholarly journals A proposed operational risk management framework for small and medium enterprises

2017 ◽  
Vol 20 (1) ◽  
Author(s):  
Micheline J. Naude ◽  
Nigel Chiweshe
Keyword(s):  
Risk Management ◽  
Small And Medium Enterprises ◽  
Relevant Literature ◽  
Management Strategies ◽  
Operational Risk ◽  
Management Framework ◽  
Operational Risk Management ◽  
Operational Risks ◽  
Risk Management Framework ◽  
Medium Enterprises

Background: The gap between small and medium-sized enterprises (SMEs) and large businesses that perform risk assessment is significant. SMEs continuously face many operational risks and uncertainties in their daily operations, and these risks threaten to reduce productivity, increase costs and reduce profits.Aim: The purpose of this article was to develop an operational risk management framework that SMEs can use to identify and analyse risks in their operations and take corrective actions to mitigate these risks.Setting: Small and medium-sized enterprises in South Africa do not view risk management as a key component of organisational success, despite evidence that businesses that adopt risk management strategies are more likely to survive and grow.Methods: The article is exploratory in nature, and a conceptual analysis approach was used to formulate the framework. This study reviewed relevant literature sources on risk published between 2002 and 2017.Results: The four process steps of risk management were used as a reference point and form the foundation for the operational risk management framework. The categories of operational; marketing; technical and financial risks were identified from a review of available literature on risk management.Conclusion: There is a dearth of research that deals with operational risk management frameworks for SMEs. The expected contribution of this article, therefore, is twofold: firstly, it is envisaged that managers or owners of SMEs could use the proposed framework as a tool to appraise and minimise their operational risks; secondly, it will add to the current body of knowledge on risk appraisal for SMEs.

scholarly journals Empirical Analysis of Financial and Non-Financial Risks of the Commercial Bank

2019 ◽  
Vol 8 (2) ◽  
pp. 101 ◽  
Author(s):  
Asie Tsintsadze ◽  
Vladimer Glonti ◽  
Lela Oniani ◽  
Tamar Ghoghoberidze
Keyword(s):  
Risk Management ◽  
Credit Risk ◽  
Operational Risk ◽  
Financial Risks ◽  
Operational Risks ◽  
Increase Risk ◽  
Method Approach ◽  
Selection Of ◽  
Regressive Analysis

Background: Activities of commercial banks are connected with numerous risks, the source of which is the internal and external processes of the bank. Objectives: Risk management science has been studying the origins of the risks, determining their impact quality and avoiding expected loss models from the 1950s. Method/Approach: Credit risk regressive analysis is based on the selection of effective factors, determination of their influence and prediction of future according to the correlation coefficient. Results/Findings: In the article, it is discussed the regressive analysis of operational risk. Conclusion: The effect of credit and operational risks on the financial results of the Bank is based on the results obtained and recommendations have been developed to increase risk management efficiency. Keywords: credit risk, operational risk, regressive analysis, risk management, forecasting.

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