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Intelligent recommender system for car insurance plans - explainability as a key to recommend the right insurance
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Orientador(es)
Resumo(s)
Acknowledging the success of personalized recommendations as support to promote
sales within a business, this paper proposes the development of a recommender system to answer
Fidelidade’s problem of depersonalization in the auto insurance sector. To build a model able to
consider historical data from the customer and the car to recommend the best auto insurance
package, a thorough data cleaning and model hypertunning were made to ensure that the three
main objectives: predictability (accuracy when predicting), explainability (explaining to each
customer the reason to recommend a certain product) and flexibility (proposing different
coverages combinations) were satisfied.
Descrição
Palavras-chave
Recommendation system Business analytics Data science Car insurance Data driven decision making