Intelligent Application of Automobile Financial Service in Artificial Intelligence Era

• Published in: Journal of physics. Conference series Vol. 1881; no. 2; p. 22081
• Main Author: Wang, Xinhua
• Format: Journal Article
• Language: English
• Published: Bristol IOP Publishing 01.04.2021
• Subjects: Artificial intelligence; Automobile industry; Data base management systems; Financial institutions; Financing; Internet of Things; Liability; Logistics management; Physics; Supervision; Supervisors; Supply chains; Theft; Vehicles
• ISSN: 1742-6588; 1742-6596
• DOI: 10.1088/1742-6596/1881/2/022081

In order to ensure the safety of financing collateral, financial institutions usually entrust third-party logistics companies to supervise the financing vehicles in stores, and the supervision cost is borne by the dealers. However, in recent years, with the increase of labor cost, the pressure on dealers’ income is increasing; and there are frequent cases of third-party supervisors and dealers colluding to sell financing vehicles without permission, It causes the loss of financial institutions’ pledge and the increase of bad debts; Orion supervises the company’s huge compensation liability risk. How to find a more economical and effective financing vehicle management and control mode to avoid personnel risk is a subject that needs in-depth discussion for financial institutions, major automobile manufacturers and dealers. This paper proposes the application of intelligent supervision mode, the use of Internet of things technology, with the help of OBD equipment, certificate key electronic supervision box, combined with the system database, to build a supply chain financial platform, realize the intelligent, real-time identification, positioning, tracking and management of vehicles, ensure 24-hour continuous monitoring, timely warning of abnormal state, alleviate regulatory loopholes, reduce the number of people For the reason of vehicle loss, theft, transfer sales and other risks. Through the questionnaire survey of three stores, more than 98% of the staff are satisfied with the intelligent supervision mode.