<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>The present study aims to explain and predict the monetary amount awarded by courts as compensation for harm suffered. A set of machine-learning algorithms was applied to a sample of decisions handed down by the Polish common courts. The methodology involved two steps: identification of words and phrases whose counts or frequencies affect the amounts adjudicated with LASSO regression and expert assessment, then applying OLS, again LASSO, random forests and XGBoost algorithms, as well as a BERT approach to make predictions. Finally, an in-depth analysis was undertaken on the influence of individual words and phrases on the amount awarded. The results demonstrate that the size of awards is most strongly influenced by the type of injury suffered, the specifics of treatment, and the family relationship between the harmed party and the claimant. At the same time, higher values are awarded when compensation for material damage and compensation for harm suffered are claimed together or when the claim is extended after it was filed.</p>
</abstract>

The present study aims to explain and predict the monetary amount awarded by courts as compensation for harm suffered. A set of machine-learning algorithms was applied to a sample of decisions handed down by the Polish common courts. The methodology involved two steps: identification of words and phrases whose counts or frequencies affect the amounts adjudicated with LASSO regression and expert assessment, then applying OLS, again LASSO, random forests and XGBoost algorithms, as well as a BERT approach to make predictions. Finally, an in-depth analysis was undertaken on the influence of individual words and phrases on the amount awarded. The results demonstrate that the size of awards is most strongly influenced by the type of injury suffered, the specifics of treatment, and the family relationship between the harmed party and the claimant. At the same time, higher values are awarded when compensation for material damage and compensation for harm suffered are claimed together or when the claim is extended after it was filed.

Predicting the Amount of Compensation for Harm Awarded by Courts Using Machine-Learning Algorithms

Central European Economic Journal

This work is licensed under the Creative Commons Attribution 4.0 International License.

The present study aims to explain and predict the monetary amount awarded by courts as compensation for harm suffered. A set of machine-learning algorithms was...

Predicting the Amount of Compensation for Harm Awarded by Courts Using Machine-Learning Algorithms

Online veröffentlicht: 26. Mai 2024

Seitenbereich: 214 - 232

DOI: https://doi.org/10.2478/ceej-2024-0015

Schlüsselwörter
compensation amount, harm, machine learning, Polish courts, prediction

© 2024 Maciej Świtała, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Predicting the Amount of Compensation for Harm Awarded by Courts Using Machine-Learning Algorithms

Online veröffentlicht: 26. Mai 2024

Seitenbereich: 214 - 232

DOI: https://doi.org/10.2478/ceej-2024-0015

Schlüsselwörtercompensation amount, harm, machine learning, Polish courts, prediction

© 2024 Maciej Świtała, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Schlüsselwörter
compensation amount, harm, machine learning, Polish courts, prediction