Residual value risk in car leasing - A case study on residual value measurements

Sammanfattning: Background & Purpose: The lessor's risk of guaranteeing a residual value for a car has grown as leasing has emerged as a popular financing alternative. As there is no active market for such values, it is a matter of estimating a residual value with high measurement uncertainty. Prior research has focused on developing statistical models for estimating future residual values of cars. However, there is a lack of research which has had an operational perspective to the issue and examined how lessors actually handle the problem of estimating a reliable residual value. The purpose of this study is therefore to shed light upon how a lessor of cars practically handles residual value calculations. Methodology: We have conducted a single case study on a large company active within financing of cars, referred to as Financier AB. The material consists of six online video interviews including five managers with relevant knowledge and different perspectives on the issue of estimating a residual value of a car. Findings & Conclusions: In the study we draw several conclusions. We find that there is a lack of attention given to e.g., soft values in prior research, even though we demonstrate its relevance in practice. We also find that the case company does not use any statistical model when setting their residual values. This finding differs greatly from previous research in the area, where most researchers have developed different statistical models to estimate the residual value. From a fair value measurement perspective, we conclude that the residual value estimations vary between level 2 and 3 input depending on the leasing object and its position in the life cycle. Lastly, we conclude that there is a difference in objectives between earlier research encompassing residual value estimation and practice. Within earlier research, the objective has been to forecast a true future value of a car, while in practice the objective was to estimate a value which is workable from multiple perspectives.