StellarCube strengthens transaction transparency with the AI-based Real Estate Care+
Taking part in the Incheon Startup Park big data and AI platform support program
SourceETNews (전자신문)
StellarCube is running its Real Estate Care+ service through the Incheon Startup Park big data and AI platform support program.
The program is overseen by the Incheon Free Economic Zone Authority and operated by the Incheon Technopark, providing infrastructure, consulting and technology development to companies in the region that need to apply big data and AI technologies, in order to help them advance their business models.
StellarCube's Real Estate Care+ service aims to increase the transparency of property transactions in the Incheon area and to prevent jeonse fraud, a form of deposit-based rental fraud.
The service uses POOM 2.0, Incheon Startup Park's validated big data and AI platform, to collect and analyze data generated in the property market and to detect and identify patterns of jeonse fraud. It also uses deep learning algorithms to analyze data and identify anomalies, with the aim of preventing such fraud.
The service is built on technology that uses AI analysis models to compare the highest and lowest prices and actual prices within a radius of up to 3 km around a listed property, presenting comparative market rates and predicted prices to detect inappropriate listings and outliers. It also applies technology that predicts the likelihood of jeonse fraud by learning from data related to risk factors, including a property's transaction history, market trends, other buildings owned by the landlord, financial arrears, unpaid national taxes and changes in registered ownership. An LLM model is applied for real-time property information and user consultation, improving convenience by providing information generated during the transaction process in real time.
A StellarCube representative said: "By building an urban data platform that collects a range of spatial and daily-life information about cities and provides analysis and predictive information for solving local problems and shaping policy, we aim to identify and address a variety of urban issues."