Resale value preditcion Using Watson Auto AI
Project Complexity - Basic
Technology: IBM Cloud Application | Business Sector: Manufacturing
Project Description
With difficult economic conditions, it is likely that sales of second-hand imported(reconditioned) cars and used cars will increase. In many developed countries, it is common to
lease a car rather than buying it outright. A lease is a binding contract between a buyer and a
seller (or a third party – usually a bank, insurance firm or other financial institutions) in which
the buyer must pay fixed instalments for a pre-defined number of months/years to the
seller/financer. After the lease period is over, the buyer has the possibility to buy the car at its
residual value, i.e. its expected resale value. Thus, it is of commercial interest to seller/financers
to be able to predict the salvage value (residual value) of cars with accuracy.
Solution:
Considering the main factors which would affect the resale value of a vehicle a
regression model is to be built that would give the nearest resale value of the
vehicle. The main factors are the time in which vehicle got registered, number
of kms it drove, power, type of gear box, model of the car, any damage or
repair, fuel type etc. and the model processing is been done in Auto AI services
in IBM cloud and then the deployment is been done in Watson studio.
regression model is to be built that would give the nearest resale value of the
vehicle. The main factors are the time in which vehicle got registered, number
of kms it drove, power, type of gear box, model of the car, any damage or
repair, fuel type etc. and the model processing is been done in Auto AI services
in IBM cloud and then the deployment is been done in Watson studio.
