Pre-Owned Car Market Of India – Changing Landscape

Till late 90s, very few Indians could afford a car and those who could, treated it like an extended member of the family. Selling the family car was not really an option — unless it was ready to be scrapped. And likewise, buying a pre-owned car was rare and rather frowned upon.

Cut to today, cars are as ubiquitous in India as the potholes on the roads they are being driven on. Buying or selling a pre-owned car is no longer a taboo — people are upgrading much faster, selling off existing cars and buying either premium pre-owned cars or brand-new ones. This change can be attributed to a burgeoning middle class with ever-increasing disposable income and higher mobility (relocating across cities, countries). As per industry estimates, 1.25 pre-owned cars were transacted for every new car transacted in India in 2018. In other words, pre-owned cars accounted for 55% of a total of 7.5 million car transactions in India. And as per forecast, pre-owned cars will account for ~75% of total transactions in India by 2025 (as is the case in the US & other mature markets) more than doubling from current ~4.2 million to ~9 million transactions a year.

However, despite the rapid increase in the size of the pre-owned car ecosystem, there are massive inefficiencies in this largely unorganized vertical in India.

Inefficiencies of pre-owned car ecosystem in India:

Unlike new cars where price and supply are almost fixed and managed by OEMs, pre-owned cars are very different beasts with huge uncertainty in both pricing and supply. The value at which a pre-owned car gets transacted completely boils down to the awareness, price sensitivity, patience and negotiation skills of different stakeholders in the transaction chain and has often very little to do with true price a given vehicle deserves. This uncertainty in price is also the key reason why financing penetration is as low as ~15% for pre-owned car transactions vs ~75% for new car transactions – asset price at the time of financing, expected depreciation over time and asset liquidity in case of default & repossession are all major challenges for mainstream banks.

Same is the case with the supply itself — a prospect seller today, may not be that keen on selling his/her car a few days later and vice versa. Not to mention, huge geo-arbitrage e.g. demand for a specific pre-owned model could significantly over-index in Outer Delhi while there would be a supply surplus of the same model in South Delhi.

We at CARS24 are trying to solve for these inefficiencies leveraging tech-enabled real-time digital auctioning & transaction platform; customer focus, pre-owned retail fronts; state of art ~200-point inspection process; and advanced ML techniques in pricing & buyer-seller matching algorithms.

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Naresh Mehta

Guest Author The Author is the Vice President of Data Science and Machine Learning at CARS24

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