Nov 9, 2020 · In this paper we propose a framework for assessing the risk associated with deploying a machine learning model in a specified environment.

Dec 28, 2023 · Machine learning has emerged as a transformative force in the domain of risk management, offering new avenues for identifying, assessing, and mitigating risks.

We suggest a risk assessment approach based on machine learning. In particular, a deep neural network (DNN) model is developed and tested for a drive-off ...

Feb 6, 2024 · ML algorithms for risk assessment can be broadly categorized into two main types: supervised learning and unsupervised learning. risk assessment ...

In this paper we propose a framework for assessing the risk associated with de- ploying a machine learning model in a specified environment.

Dec 13, 2022 · ML-based systems help risk managers to achieve complete risk visibility by combining the data required for standard risk assessment with unstructured data.

Nov 16, 2021 · This paper uses three machine learning algorithms, ie, random forest (RF), support vector machine (SVM), and AdaBoost, to evaluate enterprise risk.

Jun 14, 2023 · Risk assessment: In assessing risk, it is important to recognize that AI/ML models are not inherently more risky than conventional models. A ...

In this study, the machine learning method implementations are proposed for risk management in operational domains.

Apr 28, 2023 · AI technologies are particularly useful in risk assessment due to their ability to quickly detect, analyze and respond to threats.