房谱云估价系统

房谱云估价系统基于城市全样本地产大数据（楼盘字典）的积累，提供精准到户的房地产自动估价，覆盖二手房估价与租金估价近100城1亿套套房源，实现了城市、行政区、街道、小区、楼栋与户的全覆盖。基于小区信息、楼栋信息、房屋信息、交易信息等多维数据，依托片区划分与各物业之间的关联关系建立估价理论模型，融合成交案例等评估主题数据，实现一房一价，整栋/整盘的自动估价以及价格指数。可靠全面的数据加上专业的评估模型形成靠谱、精准的房产评估值可助力金融机构、税务及司法部门等实时、客观把握最新价格信息和历史价格走势。可广泛应用于城市新房备案价、城市二手房参考价、城市租金参考价、房地产计税参考价制定等场景。在金融机构风控场景可精准、客观的评估抵押物的价值，提升贷款审批效率与智能风控水平。公众用户在进行房屋交易时，可方便、快捷的提供城市房地产价值（租金、售价）的查询达到精准引流获客的目的。

Fangpu Cloud Valuation System is built on the accumulation of urban full-sample real estate big data (property dictionary), delivering accurate household-level real estate automatic valuation services. It covers nearly 100 cities and 100 million housing units for both second-hand housing valuation and rental valuation, achieving full coverage across urban tiers, administrative districts, streets, residential communities, buildings, and individual households. Based on multi-dimensional data including residential community information, building information, housing information and transaction information, it establishes a theoretical valuation model relying on district division and the correlation between different properties, and integrates evaluation subject data such as transaction cases to realize one-price-for-one-house, automatic valuation for entire buildings/communities and price indices. Reliable and comprehensive data coupled with professional evaluation models generate credible and accurate real estate valuation values, which can help financial institutions, tax authorities, judicial departments and other stakeholders grasp the latest price information and historical price trends in real time and objectively. It can be widely applied in scenarios such as the formulation of urban new housing filing prices, urban second-hand housing reference prices, urban rental reference prices and real estate tax calculation reference prices. In the risk control scenarios of financial institutions, it can accurately and objectively evaluate the value of collateral, improving loan approval efficiency and intelligent risk control capabilities. During housing transactions, public users can conveniently and quickly inquire about urban real estate values (rental and sales prices), thereby achieving the goal of precise traffic diversion and customer acquisition.

搜集汇总

背景与挑战

背景概述

该数据集覆盖全国百城1亿套房源，通过多维数据建模实现户级精准估价，支持金融机构风控、政府定价及公众查询等应用场景。