This paper investigates price uncertainty in private residential real estate transactions and examines how real estate broker selection and incentive structures affect transaction outcomes. Using unique data from a Swiss fintech company supporting property sellers, the paper analyzes divergences between broker valuations, listing prices and realized sale prices. The objective is to understand the sources of valuation uncertainty, the role of broker behavior and whether contract design can improve seller outcomes.
The analysis is based on transaction-level data from a Swiss fintech company that supports private property sellers in the sales process. The dataset includes multiple broker valuations, brokers' proposed prices, valuation model outcomes, listing prices, realized sale prices and broker incentive schemes. The study employs descriptive statistics, pairwise t-tests and regression analyses to examine valuation or price dispersion, strategic broker behavior and the impact of performance-based compensation.
The results reveal economically and statistically significant differences between brokers' valuations and realized sales prices, highlighting substantial valuation uncertainty in private real estate transactions. This highlights the importance of broker selection. Furthermore, we identify local broker competition as a potential source of price divergence. Moreover, stronger performance-based broker incentives are, within certain ranges, associated with significantly higher sale prices relative to fintech-based valuations.
The findings suggest that private property sellers should pay attention to broker selection and incentive design. Relying on a single broker valuation can lead to substantial opportunity costs due to undervaluation. Data-driven broker selection and performance-based compensation schemes may help better align broker incentives with seller objectives and improve transaction outcomes. Fintech solutions can help reduce information asymmetries and support more efficient pricing decisions.
This paper provides novel evidence on valuation uncertainty and broker behavior using unique transaction-level data from a fintech company. It jointly analyzes broker valuations, multiple model-based valuations, realized prices and incentive schemes within a unified framework. The study contributes to the literature by demonstrating how broker selection, strategic behavior and contract design interact to shape price outcomes in private real estate transactions.
