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Trustworthy residual vehicle value prediction for auto finance.

Authors :
Kim, Mihye
Choi, Jimyung
Kim, Jaehyun
Kim, Wooyoung
Baek, Yeonung
Bang, Gisuk
Son, Kwangwoon
Ryou, Yeonman
Kim, Kee‐Eung
Source :
AI Magazine; Dec2023, Vol. 44 Issue 4, p394-405, 12p
Publication Year :
2023

Abstract

The residual value (RV) of a vehicle refers to its estimated worth at some point in the future. It is a core component in every auto finance product, used to determine the credit lines and the leasing rates. As such, an accurate prediction of RV is critical for the auto finance industry, since it can pose a risk of revenue loss by over‐prediction or make the financial product incompetent through under‐prediction. Although there are a number of prior studies on training machine learning models on a large amount of used car sales data, we had to cope with real‐world operational requirements such as compliance with regulations (i.e., monotonicity of output with respect to a subset of features) and generalization to unseen input (i.e., new and rare car models). In this paper, we describe how we addressed these practical challenges and created value for our business at Hyundai Capital Services, the top auto financial service provider in Korea. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
07384602
Volume :
44
Issue :
4
Database :
Complementary Index
Journal :
AI Magazine
Publication Type :
Academic Journal
Accession number :
174107427
Full Text :
https://doi.org/10.1002/aaai.12136