A Bayesian Approach for Prioritising Driving Behaviour Investigations in Telematic Auto Insurance Policies

arXiv:2404.14276v1 Announce Type: cross
Abstract: Automotive insurers increasingly have access to telematic information via black-box recorders installed in the insured vehicle, and wish to identify undesirable behaviour which may signify increased risk or uninsured activities. However, identification of such behaviour with machine learning is non-trivial, and results are far from perfect, requiring human investigation to verify suspected cases. An appropriately formed priority score, generated by automated analysis of GPS data, allows underwriters to make more efficient use of their time, …

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