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- Publisher Website: 10.3390/risks11090166
- Scopus: eid_2-s2.0-85172263185
- WOS: WOS:001145321400001
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Article: Assessing ChatGPT's proficiency in quantitative risk management
Title | Assessing ChatGPT's proficiency in quantitative risk management |
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Authors | |
Keywords | ChatGPT dependence extremes quantitative risk management risk risk measures time series |
Issue Date | 19-Sep-2023 |
Publisher | MDPI |
Citation | Risks, 2023, v. 11, n. 9 How to Cite? |
Abstract | We engage in a scholarly discussion with artificial intelligence chatbot ChatGPT on concepts in quantitative risk management important for actuarial practice and analyze the interaction. We investigate the extent to which ChatGPT can grasp concepts from the realm of risk, risk measures, time series, extremes and dependence. Non-technical aspects of risk (such as explanations of various types of financial risk, the driving factors underlying the financial crisis of 2007 to 2009, or a basic introduction to the Basel Framework) are well grasped. However, more technical aspects (such as mathematical facts) are often inaccurate or wrong, sometimes in rather subtle ways. We provide guidance on the types of applications for which consulting ChatGPT can be useful in order to enhance your knowledge about quantitative risk management in actuarial practice, and point out those for which ChatGPT should better not be invoked. |
Persistent Identifier | http://hdl.handle.net/10722/337080 |
ISSN | 2023 Impact Factor: 2.0 2023 SCImago Journal Rankings: 0.403 |
ISI Accession Number ID |
DC Field | Value | Language |
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dc.contributor.author | Hofert, Jan Marius | - |
dc.date.accessioned | 2024-03-11T10:17:56Z | - |
dc.date.available | 2024-03-11T10:17:56Z | - |
dc.date.issued | 2023-09-19 | - |
dc.identifier.citation | Risks, 2023, v. 11, n. 9 | - |
dc.identifier.issn | 2227-9091 | - |
dc.identifier.uri | http://hdl.handle.net/10722/337080 | - |
dc.description.abstract | <p>We engage in a scholarly discussion with artificial intelligence chatbot ChatGPT on concepts in quantitative risk management important for actuarial practice and analyze the interaction. We investigate the extent to which ChatGPT can grasp concepts from the realm of risk, risk measures, time series, extremes and dependence. Non-technical aspects of risk (such as explanations of various types of financial risk, the driving factors underlying the financial crisis of 2007 to 2009, or a basic introduction to the Basel Framework) are well grasped. However, more technical aspects (such as mathematical facts) are often inaccurate or wrong, sometimes in rather subtle ways. We provide guidance on the types of applications for which consulting ChatGPT can be useful in order to enhance your knowledge about quantitative risk management in actuarial practice, and point out those for which ChatGPT should better not be invoked.<br></p> | - |
dc.language | eng | - |
dc.publisher | MDPI | - |
dc.relation.ispartof | Risks | - |
dc.rights | This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License. | - |
dc.subject | ChatGPT | - |
dc.subject | dependence | - |
dc.subject | extremes | - |
dc.subject | quantitative risk management | - |
dc.subject | risk | - |
dc.subject | risk measures | - |
dc.subject | time series | - |
dc.title | Assessing ChatGPT's proficiency in quantitative risk management | - |
dc.type | Article | - |
dc.identifier.doi | 10.3390/risks11090166 | - |
dc.identifier.scopus | eid_2-s2.0-85172263185 | - |
dc.identifier.volume | 11 | - |
dc.identifier.issue | 9 | - |
dc.identifier.eissn | 2227-9091 | - |
dc.identifier.isi | WOS:001145321400001 | - |
dc.identifier.issnl | 2227-9091 | - |