Client Overview
The client is a leading European bank working with automotive aftermarket players and wanted to have a predictive pricing bracket for quoting prices of cars to be bid on online and offline.
Business Challenge
- Making the application scalable and responsive
- Understanding multi industry requirements and correlating it
- Factors considerations for price derivation
Solution Highlights
- Random forest algorithm for grouping based on:
– Chassis number, size, effluent standard, and fuel type - Linear regression for numerical pattern analysis based on:
– Body color, equipment color, record updation date, registration date, mileage, gearbox, seller ID, insurance, and claims - Cross functional teams to understands the requirements of both finance and automotive industry segments
- Consider more than 100 critical points for price prediction
Benefits
- Correlation of both the business streams
- Top notch technology stack and algorithm
- Effective predictive pricing resulting in more sales
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