
Nicola Candellieri
Development of an Integrated Alert System for Earthquake Parametric Insurance.
Rel. Paolo Garza. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2025
Abstract: |
This report details the design and implementation of an automated Alert System structured to support the Earthquake team at Descartes, an Insurtech company specializing in parametric insurance against natural disasters. The system was built to provide daily notifications of relevant earthquakes worldwide and automate the claims calculation process, i.e. the process of detecting and computing eventual losses caused by recent events. The project was initiated to address the need for efficient monitoring of global seismic activity, particularly in regions with high insurance exposure, and to streamline the labor-intensive and delay-prone process of claims assessment following an earthquake. The Alert System is structured as an end-to-end data project, encompassing data ingestion, parsing, processing, and visualization. It is designed to run each morning as part of the data engineers’ Airflow DAG, ensuring that daily updates are consistently delivered to the team. The development process followed an iterative approach, beginning with a Proof of Concept that was refined based on feedback from key stakeholders, including underwriters and risk managers, and culminating in the industrialization and integration of the Alert System into the Earthquake team’s codebase. The report discusses the system’s data sources, architecture, validation process, and future improvements, while also providing context about the fields of Para metric Insurance and Seismology where the Alert System operates. Ultimately, it demonstrates the benefits of integrating advanced data processing and automation within the insurance industry. |
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Relatori: | Paolo Garza |
Anno accademico: | 2024/25 |
Tipo di pubblicazione: | Elettronica |
Numero di pagine: | 63 |
Informazioni aggiuntive: | Tesi secretata. Fulltext non presente |
Soggetti: | |
Corso di laurea: | Corso di laurea magistrale in Data Science And Engineering |
Classe di laurea: | Nuovo ordinamento > Laurea magistrale > LM-32 - INGEGNERIA INFORMATICA |
Ente in cotutela: | Institut National des Sciences Appliquees de Lyon - INSA (FRANCIA) |
Aziende collaboratrici: | Descartes Underwriting |
URI: | http://webthesis.biblio.polito.it/id/eprint/35363 |
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