境内金融科技产品及机构的态势感知与分类识别模型实验数据集

本数据集用于金融科技产品与机构的态势感知与分类识别研究，包含境内金融科技产品和机构的多种数据，包括分类数据、技术路径、业务场景等信息。数据精度为年度级别，空间范围涵盖中国境内主要的金融科技产品与机构，数据来源包括应用商店、企业官网、行业报告和工商登记信息等。采集方法主要采用自动化爬虫与API接口方式，并辅以人工审核与专家校对，确保数据的完整性与一致性。数据格式为JSON、XLSX、XML，便于后续处理与分析。质量控制方面，实施了全流程质控，包括数据去重、缺失值补全、标准化处理等，并结合专家审核与交叉验证，确保数据的高质量与可用性。本数据集的潜在利用价值在于为金融科技产品与机构的分类识别、风险评估及监测预警提供基础数据支持，能够为相关政策的制定、金融风险管理及技术创新提供数据依据和实践指导。

This dataset is developed for research on situational awareness, classification and identification of FinTech products and institutions. It includes multiple types of data of domestic FinTech products and institutions, such as classified data, technical paths, business scenarios and other related information. The data has an annual temporal resolution, and its spatial scope covers major FinTech products and institutions within the territory of China. The data sources include app stores, corporate official websites, industry reports, industrial and commercial registration records, etc. The data collection mainly adopts automated web crawlers and API interfaces, supplemented by manual review and expert proofreading to ensure the integrity and consistency of the dataset. The data is stored in JSON, XLSX and XML formats, which facilitate subsequent processing and analysis. For quality control, full-process quality control measures are implemented, including data deduplication, missing value imputation, standardization processing, etc., combined with expert review and cross-validation to ensure the high quality and usability of the data. The potential utilization value of this dataset lies in providing basic data support for the classification and identification, risk assessment and monitoring and early warning of FinTech products and institutions, and it can provide data basis and practical guidance for relevant policy formulation, financial risk management and technological innovation.