Part IV Other Risks, 19 Operational Risk Requirements

2018 ◽  
Author(s):  
Gleeson Simon
Keyword(s):  
Operational Risk ◽  
Risk Exposure ◽  
The Third ◽  
Operational Risks ◽  
Indicator Approach ◽  
External Events ◽  
A Charge ◽  
Measurement Approach ◽  
Actual Incidence

Operational risk is the ‘risk of loss resulting from inadequate or failed internal processes, people, and systems or from external events’. Banks are required to control their operational risk exposure. This chapter discusses the three approaches Basel 2 offers to determine operational risk: the basic indicator approach, the standardized approach, and the advanced measurement approach (AMA). The first two mechanisms which Basel provides for calculating operational risk eschew the analysis of operational risks themselves, and operate on a percentage of lead indicator basis. However, the third approach, i.e. the AMA, permits banks to assess the actual incidence and severity of operational risk within the institution, and to model a charge based on that information.

scholarly journals ANALISA PENGUKURAN BEBAN MODAL RISIKO OPERASIONAL METODE BASIC INDICATOR APPROACH (BIA) DAN ADVANCE MEASUREMENT APPROACH (AMA) DI BANK EFG

2020 ◽  
Vol 21 (1) ◽  
pp. 14-20
Author(s):  
Edian Fahmy
Keyword(s):  
Value At Risk ◽  
Goodness Of Fit ◽  
Geometric Distribution ◽  
Operational Risk ◽  
Risk Capital ◽  
Loss Distribution ◽  
Indicator Approach ◽  
External Events ◽  
Measurement Approach

This study aims to compare the magnitude of operational risk losses between the Basic Indicator Approach (BIA) method, and the loss distribution model in the Advanced Measurement Approach (AMA) approach so as to provide a more realistic picture for banks to determine the operational risk capital burden that must be provided based on the causes Operational risks are as follows Internal Process, Human and External Events. Measurement of operational risk capital burden by the AMA method is the determination of frequency of loss distribution, determination of severity of loss distribution, testing with goodness of fit test, then compilation of aggregated loss distribution, calculation of Operational Value at Risk (OpVar), testing the model with back testing and comparison of capital adequacy from the results of the calculation of the Basic Indicator Approach (BIA) and the Advance Measurement Approach (AMA). The results of research based on the BIA require an operational risk capital cost of Rp.291,652,000,000. The results of the research on the AMA approach use the frequency of loss distribution parameter for the internal causes of the process with a Geometric distribution of 0.17561, while for the human cause of 0.08511, for the cause of external events amounting to 0.83721. Determination of Frequency of Loss Distribution using Goodness of Fit for internal processes, people and external events. The results of the Operational Value at Risk (OpVar) with a geometric distribution pattern, then the maximum loss that can arise due to human factors is Rp.24,114,480,096, -, for internal process factors of Rp.6,010,929,367, whereas for external causes for Rp. 2,161,092,909. In total operational risk capital needs through the AMA method of Rp. 32,286,502,372.

scholarly journals RISIKO OPERASIONAL BANK DAN PERMODELANNYA

2019 ◽  
Vol 1 (1) ◽  
pp. 28-43
Author(s):  
Iwan Lesmana
Keyword(s):  
Risk Management ◽  
Management Practice ◽  
Operational Risk ◽  
Internal Controls ◽  
Banking Supervision ◽  
Risk Models ◽  
Basel Committee ◽  
Operational Risks ◽  
Indicator Approach ◽  
Measurement Approach

Managing bank’s operational risks becoming an important feature of sound risk management practice in modern financial markets. The most important types of operational risk involve breakdown in internal controls and corporate governance, which could lead to financial losses through fraud, error or failure to perform. Development of statistic has accelarated banks to create internal operational risk models in different ways. Although those models created in different ways, they surely use the pattern of risk management that is developed by Basel Committee on Banking Supervision. Basel Committee on Banking Supervision has proposed three increasingly sophisticated approaches of operational risk, i.e basic indicator approach, standardized approach and advanced measurement approach. Applying those approaches will help banks to eliminate the operational risk, that will lead them to a better intermediation process.

scholarly journals Calculating capital requirements for operational risk

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Gerd Waschbusch ◽  
Sabina Kiszka
Keyword(s):  
Financial Crisis ◽  
Operational Risk ◽  
Capital Requirements ◽  
Banking Supervision ◽  
Future Measurement ◽  
Basel Committee ◽  
Operational Risks ◽  
Increased Risk ◽  
Risk Potential ◽  
Measurement Approach

Operational risks have become increasingly important for banks, especially against the background of growing IT dependency and the increasing complexity of their activities. Further-more, the corona pandemic contributed to the increased risk potential. Therefore, banks have to back these risks with own funds. There are currently three measurement approaches for determining the capital requirements for operational risk. In recent years, and especially during the Great Financial Crisis of 2007/2008, however, some of the weaknesses inherent in these approaches have become apparent. Thus, the Basel Committee on Banking Supervision revised the current capital framework. Therefore, this article examines the various measurement approaches, addresses inherent weaknesses and moreover, presents the future measurement approach developed by the supervisory authorities.

scholarly journals Calculating Operational Risk Capital Charges for Indonesian Rural Banks

2011 ◽  
Vol 1 (1) ◽  
pp. 286 ◽  
Author(s):  
Abdul Mongid ◽  
Izah Mohd Tahir
Keyword(s):  
Historical Data ◽  
Operational Risk ◽  
Banking Supervision ◽  
Risk Capital ◽  
Basel Committee ◽  
Operational Risks ◽  
Indicator Approach ◽  
New Basel Capital Accord ◽  
Capital Charge

In January 2001, the Basel Committee on Banking Supervision published a proposal for a new capital framework, the “New Basel Capital Accord (Basel 11)” thus replacing Basel 1. One of the major motivations in the proposal is the introduction of explicit capital charge for operational risks in the business activities of banks. The objective of this paper is to estimate operational risk capital charge using historical data for 77 rural banks in Indonesia for a three-year period, 2006 to 2008. This study uses three approaches:  (i) Basic Indicator Approach (BIA), (ii) Standardized Approach (SA) and (iii) Alternative Standardized Approach (ASA). We found that the average capital charge required to cover operational risk is IDR 154 million (1.5% of asset). When the calculation is conducted using the SA method, we found, on average a requirement of IDR 123 million (1.23% of asset). When the calculation is conducted using the Alternative Standardized Approach (ASA), the capital required was IDR 43 million (0.43% of asset). The results provide evidence that banks using more advance model require less capital charge.

scholarly journals Cyber operational risk scenarios for insurance companies

2019 ◽  
Vol 24 ◽  
Author(s):  
R. Egan ◽  
S. Cartagena ◽  
R. Mohamed ◽  
V. Gosrani ◽  
J. Grewal ◽  
...  
Keyword(s):  
Cyber Security ◽  
Operational Risk ◽  
Social Engineering ◽  
Insurance Companies ◽  
List Type ◽  
Operational Risks ◽  
Life Insurer ◽  
Cyber Risk ◽  
The Impact ◽  
Over Time

AbstractCyber Operational Risk: Cyber risk is routinely cited as one of the most important sources of operational risks facing organisations today, in various publications and surveys. Further, in recent years, cyber risk has entered the public conscience through highly publicised events involving affected UK organisations such as TalkTalk, Morrisons and the NHS. Regulators and legislators are increasing their focus on this topic, with General Data Protection Regulation (“GDPR”) a notable example of this. Risk actuaries and other risk management professionals at insurance companies therefore need to have a robust assessment of the potential losses stemming from cyber risk that their organisations may face. They should be able to do this as part of an overall risk management framework and be able to demonstrate this to stakeholders such as regulators and shareholders. Given that cyber risks are still very much new territory for insurers and there is no commonly accepted practice, this paper describes a proposed framework in which to perform such an assessment. As part of this, we leverage two existing frameworks – the Chief Risk Officer (“CRO”) Forum cyber incident taxonomy, and the National Institute of Standards and Technology (“NIST”) framework – to describe the taxonomy of a cyber incident, and the relevant cyber security and risk mitigation items for the incident in question, respectively.Summary of Results: Three detailed scenarios have been investigated by the working party:∙Employee leaks data at a general (non-life) insurer: Internal attack through social engineering, causing large compensation costs and regulatory fines, driving a 1 in 200 loss of £210.5m (c. 2% of annual revenue).∙Cyber extortion at a life insurer: External attack through social engineering, causing large business interruption and reputational damage, driving a 1 in 200 loss of £179.5m (c. 6% of annual revenue).∙Motor insurer telematics device hack: External attack through software vulnerabilities, causing large remediation / device replacement costs, driving a 1 in 200 loss of £70.0m (c. 18% of annual revenue).Limitations: The following sets out key limitations of the work set out in this paper:∙While the presented scenarios are deemed material at this point in time, the threat landscape moves fast and could render specific narratives and calibrations obsolete within a short-time frame.∙There is a lack of historical data to base certain scenarios on and therefore a high level of subjectivity is used to calibrate them.∙No attempt has been made to make an allowance for seasonality of renewals (a cyber event coinciding with peak renewal season could exacerbate cost impacts)∙No consideration has been given to the impact of the event on the share price of the company.∙Correlation with other risk types has not been explicitly considered.Conclusions: Cyber risk is a very real threat and should not be ignored or treated lightly in operational risk frameworks, as it has the potential to threaten the ongoing viability of an organisation. Risk managers and capital actuaries should be aware of the various sources of cyber risk and the potential impacts to ensure that the business is sufficiently prepared for such an event. When it comes to quantifying the impact of cyber risk on the operations of an insurer there are significant challenges. Not least that the threat landscape is ever changing and there is a lack of historical experience to base assumptions off. Given this uncertainty, this paper sets out a framework upon which readers can bring consistency to the way scenarios are developed over time. It provides a common taxonomy to ensure that key aspects of cyber risk are considered and sets out examples of how to implement the framework. It is critical that insurers endeavour to understand cyber risk better and look to refine assumptions over time as new information is received. In addition to ensuring that sufficient capital is being held for key operational risks, the investment in understanding cyber risk now will help to educate senior management and could have benefits through influencing internal cyber security capabilities.

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.

High-Tech Spin-Offs’ Operational Risk Assessment System

2010 ◽  
Vol 40-41 ◽  
pp. 968-973
Author(s):  
Li Ma ◽  
Li Hua Li
Keyword(s):  
Evaluation Model ◽  
Operational Risk ◽  
Sustainable Growth ◽  
Assessment System ◽  
High Tech ◽  
Mathematical Methods ◽  
Operational Risks ◽  
Overall Evaluation ◽  
Hierarchical Index ◽  
Hierarchy Process

This paper analyzes the sources of high-tech spin-offs’ operational risks, establishes a multifactor hierarchical index system and applies Analytical Hierarchy Process and fuzzy mathematical methods to build a fuzzy overall evaluation model. This research can provide a useful tool to help high-tech spin-offs scientifically assess their operational risk degree in order to formulate corresponding countermeasures to evade the risks, and realize sustainable growth.

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