Research On Operational Risk Measurement Of Commercial Banks

According to the definition of Basel Ⅲ,operational risk refers to risk due to incomplete or malfunctioning internal processes,personnel and systems,or external events.In recent years,the scale of commercial bank's assets has been continuously expanded and business activities have become increasingly complex.Operational risks have increasingly become the main risk affecting their business development.How to measure and then manage operational risks is a problem that regulators and banks have to face.From the regulators' perspective,so as to keep the stability of the financial system and protect the security of depositor's funds,controlling the risk of banks is their basic task.To this end,the regulatory authorities will issue a series of strict regulatory documents,such as raising the capital adequacy ratio and reducing the leverage ratio.However,from the bank's point of view,they hope that the regulatory authorities will properly relax risk control,because part of the capital requirements could have been used for investment to obtain higher returns.Therefore,the regulatory authorities and banks have different attitudes towards operational risk.The regulatory authorities have a more conservative or strict attitude toward risk,while banks are less conservative.When researchers cannot obtain bank's operational loss data and can only obtain open data,researchers can also use the income model method to measure the bank's operational risk.Studying the factors that affect the number of operating losses has certain practical significance.By controlling the main influencing factors of the number of operational losses,the goal of reducing operational losses can be achieved.This paper first introduces the background and significance of operational risk,sorts out related domestic and foreign research literature,and gives some preparative knowledge needed for the research process.Then,the provisions of the coverage ratio are considered.Income models are used to measure the operational risks of eight banks.The results show that the average operational risk of state-owned banks is significantly greater than that of joint-stock banks.Secondly,because the commercial bank's operational risk loss data tends to have a "heavy-tailed"characteristic in statistical distribution,the extreme value theory is considered to be a more appropriate model to deal with operational risks.Using the POT model to measure the bank's operational risk,three kinds of GlueVaR value are obtained under the risk attitude.The bank uses the Glue VaR value as the regulatory capital of operational risk.GlueVaR risk measurement takes into account conservative,neutral,and optimistic risk attitudes in response to disagreements between regulators and banks on risk attitudes,and can help them achieve consensus on regulatory capital.It can not only effectively compensate for potential operational losses,but also avoid excessively high regulatory capital which will reduce bank's profit.Finally,the main factors affecting the number of operational risk occurrences are analyzed.Due to the excessively discrete nature of the data on the number of operational losses,three regression models have been studied,which are Poisson,quasi poisson and negative binomial.The results show that the debt asset ratio,bad loan ratio and unemployment rate are positively related to the number of operational losses.The GDP growth rate and the Shanghai Composite Index are both negatively related to the number of operational losses.Finally,the main research conclusions of this article are summarized and the follow-up research is prospected.