Machine Learning in Risk Management Applications
(2023) DABN01 20231Department of Economics
Department of Statistics
- Abstract
- Risk Management is a broad domain that has many applications in different industries and organizations. There are many competing guidelines and overarching frameworks that describe workflow and best practice in various subdomains. The objective of this thesis is to explore how machine learning algorithms can be used in general terms of risk management frameworks in support of risk assessment with regards to established guidelines and workflows, specifically in the context of predictive maintenance for classifying machine failure. The findings suggest that the use of sampling techniques is an effective way of addressing class imbalance issues and that the classification techniques used offer good interpretability and can be used in support... (More)
- Risk Management is a broad domain that has many applications in different industries and organizations. There are many competing guidelines and overarching frameworks that describe workflow and best practice in various subdomains. The objective of this thesis is to explore how machine learning algorithms can be used in general terms of risk management frameworks in support of risk assessment with regards to established guidelines and workflows, specifically in the context of predictive maintenance for classifying machine failure. The findings suggest that the use of sampling techniques is an effective way of addressing class imbalance issues and that the classification techniques used offer good interpretability and can be used in support of risk management frameworks. (Less)
Please use this url to cite or link to this publication:
http://lup.lub.lu.se/student-papers/record/9140864
- author
- Göransson, Tim LU
- supervisor
- organization
- course
- DABN01 20231
- year
- 2023
- type
- H1 - Master's Degree (One Year)
- subject
- keywords
- Machine Learning, Risk Management, Classification, Predictive Maintenance, Model Interpretability
- language
- English
- id
- 9140864
- date added to LUP
- 2023-11-21 12:53:54
- date last changed
- 2023-11-21 12:53:54
@misc{9140864, abstract = {{Risk Management is a broad domain that has many applications in different industries and organizations. There are many competing guidelines and overarching frameworks that describe workflow and best practice in various subdomains. The objective of this thesis is to explore how machine learning algorithms can be used in general terms of risk management frameworks in support of risk assessment with regards to established guidelines and workflows, specifically in the context of predictive maintenance for classifying machine failure. The findings suggest that the use of sampling techniques is an effective way of addressing class imbalance issues and that the classification techniques used offer good interpretability and can be used in support of risk management frameworks.}}, author = {{Göransson, Tim}}, language = {{eng}}, note = {{Student Paper}}, title = {{Machine Learning in Risk Management Applications}}, year = {{2023}}, }