RealEstate-Fraud-Detector

Real Estate Listings Analysis

Project Description
Using data from Yandex Real Estate service (archive of apartment sale listings in St. Petersburg and neighboring settlements over several years), we determine the market value of real estate properties. To achieve this, we conduct exploratory data analysis and identify parameters that affect property prices. This will enable building an automated system that can detect anomalies and fraudulent activity.

For each apartment on sale, two types of data are available. The first type is entered by users, while the second is obtained automatically based on cartographic data. For example, distance to city center, airport, and other facilities - this data is automatically retrieved from geo-services. The number of parks and water bodies is also filled without user participation.

Research Objectives
- Determine market value of real estate properties
- Identify key factors affecting apartment prices
- Build an automated anomaly detection system
- Detect potential fraudulent listings

Data Sources
- Yandex Real Estate service archive
- User-generated listing information
- Automated geographic and cartographic data
- Geo-service derived location metrics