Machine Readable Intelligent SEC Data

OVERVIEW:

Intelligent SEC Data enables analysts and quantitative investors to unlock the power of machine-readable filings with FiscalNote AI Solutions.

Anvil, our next-generation AI platform, continually monitors
for new SEC filings in real time, and transforms the textual portions of those filings into a machine consumable representation that maintains section integrity while
removing extraneous information.

Document statutory hierarchy is maintained by creating a historical baseline for
back testing and cross-section analysis, as well as cross-company analysis

The data is delivered in a structured format that lets users perform
Natural Language Processing (NLP) against the data without having
to do document cleanup and structuring themselves.

Additionally, this data set offers specialized LDA topic models and takes advantage of Anvil’s unique resolution, entity, relationship and event extraction capabilities.

The data is delivered in a simple, structured format to let you immediately incorporate it into internal human facing applications, algorithms, and data science environments.

SCALE:

- Focused on US SEC Filings
- Detailed identifiers
- 10 Year plus history
- Continually Updated

PARTIAL SAMPLE OF KEY FIELDS / DATA TYPES:

- Company identifiers
- Dates
- Form type (3, 4, 5, 8K'S, 10-k's and 10q'S)
- Multiple LDA topic model vectors (models specially trained to specific sections of relevant SEC filings)
- Extracted entities, relationships etc.

TECHNOLOGY & METHODS:

Anvil, FiscalNote AI Solutions next-generation AI platform utilizes highly proprietary natural language understanding models, unique knowledge graph capabilities and our proprietary AI engines to extract and resolve and entities (companies, people, products etc.) and to apply various specialized LDA topic models for clustering. change detection and for identifying similarities both intra company and across companies. Data readily supports time series and an ability to rapidly compare and contrast individual companies, industry segments or user defined cohorts.

Full data provenance is always maintained. Readily fused with other data sets provided by FiscalNote AI Solutions to create additional factors and dimensions for both augmented analytical insights and quantitative modeling.

ABOUT FISCALNOTE AI SOLUTIONS

FiscalNote and FiscalNote AI Solutions is the premier information services company focused on global policy and market intelligence. By combining AI technology, expert analysis, and legislative, regulatory, and geopolitical data, FiscalNote is reinventing the way that organizations minimize risk and capitalize on opportunity. FiscalNote empowers more than 5,000 clients worldwide to monitor, manage, and act on the issues that matter most to them. To learn more about FiscalNote and its family of brands, visit FiscalNote.com and FiscalNote.ai or follow @FiscalNote.

概览：
智能SEC（美国证券交易委员会）数据依托FiscalNote AI解决方案，可帮助分析师与量化投资者充分挖掘机器可读SEC申报文件的应用潜能。
我们的下一代AI平台Anvil可实时持续监控新增SEC申报文件，并将申报文件中的文本内容转换为机器可处理的结构化表示——在保留章节完整性的同时剔除无关冗余信息。
通过构建历史基准数据集，该方案可保留申报文件的法定层级结构，支持回测、截面分析及跨公司分析。
数据以结构化格式交付，用户可直接对其开展自然语言处理（Natural Language Processing, NLP）工作，无需自行完成文件清洗与结构化处理。
此外，该数据集内置专属潜在狄利克雷分配（Latent Dirichlet Allocation, LDA）主题模型，并依托Anvil独有的实体解析、实体抽取、关系抽取与事件抽取能力。
数据采用简洁结构化格式交付，用户可直接将其集成至面向内部人员的应用程序、算法模型及数据科学工作环境中。

数据规模：
- 聚焦美国SEC申报文件
- 配备精细化标识符体系
- 拥有十年以上历史数据
- 支持持续实时更新

核心字段/数据类型示例：
- 公司标识符
- 日期信息
- 申报表单类型（涵盖3号、4号、5号表格，8-K、10-K及10-Q报表）
- 多组LDA主题模型向量（针对特定SEC申报章节专项训练的模型）
- 抽取得到的实体、关系等信息

技术与方法：
作为FiscalNote AI解决方案旗下的下一代AI平台，Anvil依托高度专属的自然语言理解模型、独特的知识图谱功能及自研AI引擎，实现实体（公司、人物、产品等）的抽取与解析，并通过各类专属LDA主题模型完成聚类、变更检测，以及识别公司内部与跨公司的相似度。该数据集可高效支持时序分析，同时支持快速对比单个公司、行业板块或用户自定义群组的相关信息。
全程保留完整的数据溯源信息，且可便捷与FiscalNote AI解决方案提供的其他数据集进行融合，从而生成更多特征维度，用于强化分析洞察与量化建模工作。

关于FiscalNote AI解决方案：
FiscalNote及FiscalNote AI Solutions是专注于全球政策与市场情报的顶级信息服务企业。其融合AI技术、专家分析能力，以及立法、监管与地缘政治数据，重新定义了企业规避风险、把握机遇的工作范式。FiscalNote为全球超过5000家客户提供赋能服务，帮助其监控、管理并应对自身最关切的各类议题。如需了解FiscalNote及其旗下品牌的更多信息，请访问FiscalNote.com与FiscalNote.ai，或关注@FiscalNote。

搜集汇总

背景与挑战

背景概述

该数据集通过Anvil AI平台将美国SEC文件实时转换为结构化机器可读格式，保留章节完整性并提供10年以上历史数据，支持实体提取、LDA主题建模和跨公司分析，可直接用于量化投资和NLP应用。