Russia Trains AI to Find the “Real” Price of Used Cars
The new system blends machine learning and expert input to solve one of the biggest pain points of the auto market — fair pricing.
Researchers at Perm Polytechnic University have developed an AI-powered platform that can accurately determine the market value of used cars in Russia — a tool that could reshape how dealers, banks, and insurance companies assess vehicles.
The system works in three stages. First, a CatBoost-based algorithm evaluates factors such as make, model, mileage, condition, and market trends. Then, human experts — including auto center managers and sales professionals — provide their assessments. Finally, the AI refines its pricing model through self-learning, adjusting to real-world expert corrections and new data over time.
90% accuracy — and counting
In pilot tests involving banks, car dealerships, and insurers, the system analyzed over 4,000 trade-in transactions and achieved an impressive 90.2% accuracy rate. The researchers say the technology will make it easier for buyers and sellers to agree on fair prices, while financial institutions can more precisely calculate vehicle collateral and insurance payouts.
By combining AI analytics with human expertise, Russia’s new pricing platform could bring rare transparency to the used car market — an industry long plagued by inconsistent valuations and opaque deal-making.
