Zhang, Wen and Dunkley, Andrew and Kanabar, Urvi and Elliott, David and Wynn, Henry P (2022) A decision support system for liability in civil litigation: a case study from an insurance company. Annals of Operations Research, 315 (2). pp. 695-706. DOI https://doi.org/10.1007/s10479-020-03905-0
Zhang, Wen and Dunkley, Andrew and Kanabar, Urvi and Elliott, David and Wynn, Henry P (2022) A decision support system for liability in civil litigation: a case study from an insurance company. Annals of Operations Research, 315 (2). pp. 695-706. DOI https://doi.org/10.1007/s10479-020-03905-0
Zhang, Wen and Dunkley, Andrew and Kanabar, Urvi and Elliott, David and Wynn, Henry P (2022) A decision support system for liability in civil litigation: a case study from an insurance company. Annals of Operations Research, 315 (2). pp. 695-706. DOI https://doi.org/10.1007/s10479-020-03905-0
Abstract
The use of statistical and AI methods in civil litigation is an area likely to expand. As with many areas of social science, the data requirements are high but complex, because of the complexity of the legal process and the nature of the causal connections. This paper looks at the early stage of the process where the initial establishment of liability acts as a legal triage which affects the route through the litigation process. A simple model is used in which the training set is the assessment of the probability of liability given hypothetical scenarios in road traffic accidents. The model is augmented by additional “weight of evidence” assessments. The model, once built, is used as a decision support system for claim handlers on a routine basis. The methods can be seen as a way of utilising a special type of expert judgment elicitation.
Item Type: | Article |
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Uncontrolled Keywords: | Business analytics; Decision support systems; Experts’ judgment; Legal; Insurance claims |
Divisions: | Faculty of Social Sciences Faculty of Social Sciences > Essex Business School |
SWORD Depositor: | Unnamed user with email elements@essex.ac.uk |
Depositing User: | Unnamed user with email elements@essex.ac.uk |
Date Deposited: | 05 Jan 2021 13:28 |
Last Modified: | 30 Oct 2024 17:38 |
URI: | http://repository.essex.ac.uk/id/eprint/29457 |
Available files
Filename: foresight revised.pdf