AI for Car Damage Detection and Repair Price Estimation in Insurance: Market Research and Novel Solution

Vladimir Ghita (), Denis Iorga (), Laurentiu-Marian Neagu (), Mihai Dascalu () and Gheorghe Militaru ()
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Vladimir Ghita: University Politehnica of Bucharest
Denis Iorga: University of Bucharest ISDS
Laurentiu-Marian Neagu: University Politehnica of Bucharest
Mihai Dascalu: University Politehnica of Bucharest
Gheorghe Militaru: University Politehnica of Bucharest

A chapter in Rethinking Business for Sustainable Leadership in a VUCA World, 2024, pp 167-179 from Springer

Abstract: Abstract The current study focuses on Artificial Intelligence (AI) products for car damage detection and repair price estimation in the insurance industry. The opportunity to introduce such products in the Romanian local market is highlighted following a scoping review of potential benefits and challenges, existing commercial solutions, and existing market research. The lack of market research data concerning the challenges faced by Romanian customers and employees of insurance companies during the insurance claim process is identified as a gap. To address it, the current work presents the results of a pilot survey-based market research that sought to understand the challenges faced by two main Romanian stakeholders of the insurance claim process, namely drivers involved in car accidents (N = 20) and car damage inspectors (N = 15). The result are used to define and advance a novel architecture for an AI system for car damage detection and repair price estimation (InsureAI) that aims to: (a) streamline the communication process between customers and representatives of insurance companies, (b) minimize appointment and traveling challenges related to car damage inspection, (c) reduce the complexity of the repair decision and price estimation related to the insurance claim procedure, (d) address the challenges of customers of car insurance companies in organizing and filing in the necessary information for starting a new claims file, as well as (e) enhance the overall process transparency. Additionally, we detail the envisioned user flow and the user interface prototype.

Keywords: Artificial intelligence; Car damage; Car price estimation; Car insurance; Market research (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:spr:prbchp:978-3-031-50208-8_10

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DOI: 10.1007/978-3-031-50208-8_10

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