An Explorative Guide on How to Detect Forged Car Insurance Claims with Language Models

Quentin Telnoff, Quentin Telnoff, Emanuela Boros, Mickael Coustaty, Fabrice Crohas, Antoine Doucet, Frédéric Bars

2023

Abstract

Detecting forgeries in insurance car claims is a complex task that requires detecting fraudulent or overstated claims related to property damage or personal injuries after a car accident. Building predictive models for detecting them raises several issues (e.g. imbalance, concept drift) that cannot only depend on the frequency or timing of the reported incidents. The difficulty of tackling this type of task is further intensified by the static tabular data generally used in this domain, while submitted insurance claims largely consist of textual data. We, thus, propose an explorative guide for detecting forged car insurance claims with language models. Specifically, we investigate two transformer-based frameworks: supervised (where the model is trained to differentiate between forged and non-forged cases) and self-supervised (where the model captures the standard attributes of non-forged claims). For handling static tabular data and unstructured text fields, we inspect various forms of data row modelling (table serialization techniques), different losses, and two language models (one general and one domain-specific). Our work highlights the challenges and limitations of existing frameworks.

Paper Citation

in Harvard Style

Telnoff Q., Boros E., Coustaty M., Crohas F., Doucet A. and Bars F. (2023). An Explorative Guide on How to Detect Forged Car Insurance Claims with Language Models. In Proceedings of the 15th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 1: KDIR; ISBN 978-989-758-671-2, SciTePress, pages 403-412. DOI: 10.5220/0012232900003598

in Bibtex Style

@conference{kdir23,
author={Quentin Telnoff and Emanuela Boros and Mickael Coustaty and Fabrice Crohas and Antoine Doucet and Frédéric Bars},
title={An Explorative Guide on How to Detect Forged Car Insurance Claims with Language Models},
booktitle={Proceedings of the 15th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 1: KDIR},
year={2023},
pages={403-412},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012232900003598},
isbn={978-989-758-671-2},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 15th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 1: KDIR
TI - An Explorative Guide on How to Detect Forged Car Insurance Claims with Language Models
SN - 978-989-758-671-2
AU - Telnoff Q.
AU - Boros E.
AU - Coustaty M.
AU - Crohas F.
AU - Doucet A.
AU - Bars F.
PY - 2023
SP - 403
EP - 412
DO - 10.5220/0012232900003598
PB - SciTePress