An integrated inverse adaptive neural fuzzy system with Monte-Carlo sampling method for operational risk management

作者：

Highlights：

• A flexible integrated inverse adaptive fuzzy inference model is proposed.

• The model contributes to improve operational risk measurement.

• The model combines Monte Carlo estimation of loss distribution and risk profiles.

• The model relies on the fuzzy input that represents frequency and severity of risk.

• The model can monitor the evolution of the risk profile of an organization.

摘要

•A flexible integrated inverse adaptive fuzzy inference model is proposed.•The model contributes to improve operational risk measurement.•The model combines Monte Carlo estimation of loss distribution and risk profiles.•The model relies on the fuzzy input that represents frequency and severity of risk.•The model can monitor the evolution of the risk profile of an organization.

论文关键词：Monte-Carlo sampling,Integrated adaptive neural fuzzy system,Loss distribution approach,Operational value at risk,Risk profile,Basel committee on banking supervision

论文评审过程：Received 10 June 2017, Revised 14 December 2017, Accepted 1 January 2018, Available online 3 January 2018, Version of Record 12 January 2018.

论文官网地址：https://doi.org/10.1016/j.eswa.2018.01.001