Driving Behavior and Insurance Pricing: A Framework for Analysis and Some Evidence from Italian Data Using Zero-Inflated Poisson (ZIP) Models

Paola Fersini, Michele Longo and Giuseppe Melisi ()
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Paola Fersini: Department of Law, Economics and Quantitative Methods, University of Sannio, 82100 Benevento, BN, Italy
Michele Longo: Department of Law, Economics and Quantitative Methods, Catholic University of Milan, 20123 Milan, MI, Italy
Giuseppe Melisi: Department of Law, Economics and Quantitative Methods, Catholic University of Milan, 20123 Milan, MI, Italy

Risks, 2025, vol. 13, issue 11, 1-30

Abstract: Usage-Based Insurance (UBI), also referred to as telematics-based insurance, has been experiencing a growing global diffusion. In addition to being well established in countries such as Italy, the United States, and the United Kingdom, UBI adoption is also accelerating in emerging markets such as Japan, South Africa, and Brazil. In Japan, telematics insurance has shown significant growth in recent years, with a steadily increasing subscription rate. In South Africa, UBI adoption ranks among the highest worldwide, with market penetration placing the country among the top three globally, just after the United States and Italy. In Brazil, UBI adoption is expanding, supported by government initiatives promoting road safety and innovation in the insurance sector. According to a MarketsandMarkets report of February 2025, the global UBI market is expected to grow from USD 43.38 billion in 2023 to USD 70.46 billion by 2030, with a compound annual growth rate (CAGR) of 7.2% over the forecast period. This growth is driven by the increasing adoption of both electric and internal combustion vehicles equipped with integrated telematics systems, which enable insurers to collect data on driving behavior and to tailor insurance premiums accordingly. In this paper, we analyze a large dataset consisting of trips recorded over five years from 100,000 policyholders across the Italian territory through the installation of black-box devices. Using univariate and multivariate statistical analyses, as well as Generalized Linear Models (GLMs) with Zero-Inflated Poisson distribution, we examine claims frequency and assess the relevance of various synthetic indicators of driving behavior, with the aim of identifying those that are most significant for insurance pricing.

Keywords: black box; insurance premium; UBI; ZIP (search for similar items in EconPapers)
JEL-codes: C G0 G1 G2 G3 K2 M2 M4 (search for similar items in EconPapers)
Date: 2025
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