Data science for connected car insurance : use of trips raw telematics data for knowledge discovery and customers profiling

Detalhes bibliográficos
Autor(a) principal: Spada, Enrico
Data de Publicação: 2018
Tipo de documento: Dissertação
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10362/42452
Resumo: Internship Report presented as the partial requirement for obtaining a Master's degree in Information Management, specialization in Knowledge Management and Business Intelligence
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spelling Data science for connected car insurance : use of trips raw telematics data for knowledge discovery and customers profilingData ScienceCar InsuranceRaw Telematics DataClusteringRisk KnowledgeInternship Report presented as the partial requirement for obtaining a Master's degree in Information Management, specialization in Knowledge Management and Business IntelligenceThis report presents all data science processes designed and implemented during the internship at the Actuarial Department of Sterling Insurance1 (Italy). The project developed a complete data science solution, organized according to Cross-Industry Standard Process for Data Mining. The objective is to study in-depth – for the very first time – trips raw telematics data, and to discover actionable knowledge that can be applied to generate value for the business. The research is based on trips raw telematics data generated over 5 months by telematics black-box devices installed in the cars of 937 customers. The data are solely related to trips, with granularity at the finest level of individual geospatial coordinate sets composing trajectories. The features describing each timestamped GPS coordinate set are average speed in the last second, heading, GPS quality, meters travelled since previous position. The data sources consist of semi-structured data stored in several flat files in their native format, batch extracted from the data lake. Starting from trips raw telematics data at the granular level of geospatial coordinate sets, they are extensively studied and enriched with additional open data sources exploiting spatial join operations. Next, a complex concatenation of data preparation tasks is performed to obtain the final dataset, aggregated at the granular level of trips and described by 117 features. The final dataset is fed to the k-means algorithm for discovering patterns over trips characteristics. Patterns are studied considering the overall portfolio, regardless of driver and intentionally neglecting historical or personal information. The study concludes by deploying the clustering results to profile customers, bringing to a new level the risk knowledge of the line of business about its customers. This discovery opens a world of new possibilities, some of the uncountable examples are improve pricing, using results in fraud detection and offering new services and overall risk prevention for customers.Cabral, Pedro da Costa BritoClaeys, OlivierRUNSpada, Enrico2021-07-13T00:30:17Z2018-07-132018-07-13T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttp://hdl.handle.net/10362/42452TID:201954990enginfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-03-11T04:22:53Zoai:run.unl.pt:10362/42452Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T03:31:29.651266Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Data science for connected car insurance : use of trips raw telematics data for knowledge discovery and customers profiling
title Data science for connected car insurance : use of trips raw telematics data for knowledge discovery and customers profiling
spellingShingle Data science for connected car insurance : use of trips raw telematics data for knowledge discovery and customers profiling
Spada, Enrico
Data Science
Car Insurance
Raw Telematics Data
Clustering
Risk Knowledge
title_short Data science for connected car insurance : use of trips raw telematics data for knowledge discovery and customers profiling
title_full Data science for connected car insurance : use of trips raw telematics data for knowledge discovery and customers profiling
title_fullStr Data science for connected car insurance : use of trips raw telematics data for knowledge discovery and customers profiling
title_full_unstemmed Data science for connected car insurance : use of trips raw telematics data for knowledge discovery and customers profiling
title_sort Data science for connected car insurance : use of trips raw telematics data for knowledge discovery and customers profiling
author Spada, Enrico
author_facet Spada, Enrico
author_role author
dc.contributor.none.fl_str_mv Cabral, Pedro da Costa Brito
Claeys, Olivier
RUN
dc.contributor.author.fl_str_mv Spada, Enrico
dc.subject.por.fl_str_mv Data Science
Car Insurance
Raw Telematics Data
Clustering
Risk Knowledge
topic Data Science
Car Insurance
Raw Telematics Data
Clustering
Risk Knowledge
description Internship Report presented as the partial requirement for obtaining a Master's degree in Information Management, specialization in Knowledge Management and Business Intelligence
publishDate 2018
dc.date.none.fl_str_mv 2018-07-13
2018-07-13T00:00:00Z
2021-07-13T00:30:17Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/masterThesis
format masterThesis
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10362/42452
TID:201954990
url http://hdl.handle.net/10362/42452
identifier_str_mv TID:201954990
dc.language.iso.fl_str_mv eng
language eng
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron:RCAAP
instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron_str RCAAP
institution RCAAP
reponame_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository.name.fl_str_mv Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
repository.mail.fl_str_mv
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