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Title: Address identification using telematics: An algorithm to identify dwell locations Authors:  Christopher Grumiau - Allianz Benelux (Belgium)
Mina Mostoufi - Allianz Benelux (Belgium) [presenting]
Solon Pavlioglou - Allianz Benelux (Netherlands)
Tim Verdonck - UAntwerp, KU Leuven (Belgium)
Abstract: A method is proposed for exploiting the predictive power of a geo-tagged data set as a means of identification of user-relevant points of interest (POI). The proposed methodology is subsequently applied in an insurance context for the automatic identification of a drivers residence address, solely based on his pattern of movements on the map. The analysis is performed on a real-life telematics dataset. We have anonymized the considered dataset to respect privacy regulations. The model performance is evaluated based on an independent batch of the dataset for which the address is known to be correct. The model is capable of predicting the residence postal code of the user with a high level of accuracy, with an f1 score of 0.83. A reliable result of the proposed method could generate benefits beyond the area of fraud, such as general data quality inspections, one-click quotations, and better-targeted marketing.