SEC 8-K Structured Credit Events and Distress Signals
收藏资源简介：
Terrain Credit Events is a real-time, deeply structured dataset of every credit event disclosed in SEC 8-K filings: new issuances, new facilities, amendments, defaults, restructurings, forbearances, and debt exchanges. The data spans the entire public market, from micro-cap distressed convertibles to mega-cap investment-grade debt. 8-K filings capture material events as they happen, falling between the quarterly cadence of 10-Q and 10-K reports. Because every event ties to the same borrower over time, you can follow a credit from origination through the amendments, waivers, and refinancings that follow, the full lifecycle, not just the deal at close. These are patterns that show up only when you read every filing systematically. A pre-built Cortex agent and semantic view ship with the product, ready for natural language analysis in Snowflake Intelligence. <p><br/></p> # What's included - **Credit events**: every event detected in SEC 8-K filings, classified by event type, instrument, seniority, deal purpose, size, and status - **Ticker, CIK**: for joining to your existing data - **Market cap tier**: micro, small, mid, large, mega, for filtering and peer comparison - **Counterparties**: standardized names with roles (lender, agent, borrower, advisor) and types (bank, private credit, specialty lender, underwriter, and more). Both canonical and as-filed names preserved. - **Pricing structure**: spreads, coupons, PIK features, benchmark rates, and maturity - **Amendments**: classified by what changed (pricing, maturity, covenants, collateral, commitment, incremental, PIK toggle, and more) - **Facility structure**: bilateral, club, small syndicate, broadly syndicated, insider/specialty - **Counterparty changes**: lender exits, additions, advisor engagements - **Distress signals**: a screening flag based on structural indicators across a company's filing history - **Summary**: a written analytical narrative for each event covering the deal terms, what it replaces or accompanies, and the company's credit trajectory across prior filings - **Theme tags**: AI infrastructure financings, private credit, potential liability management exercises (LME), M&A financings, and insider lending. The tag list evolves with the market. - **Sectors**: sector and sub-sector classifications built for credit analysis - **Source filing**: a direct link to each event's 8-K on SEC.gov for verification - **Cortex agent**: pre-built agent and semantic view for Snowflake Intelligence <p><br/></p> # How the data is built Terrain's AI analysts read every SEC 8-K filing as it is filed, working through the hundreds of pages of credit agreements, indentures, and exhibits to surface what matters for credit workflows. Our methodology and knowledge base draw on years of historical filings to inform how new disclosures are interpreted, where ambiguity gets resolved, and the structural detail off-the-shelf AI misses. Our validation framework makes corrections and helps significantly reduce mistakes. <p><br/></p> # How potential distress is determined The flag incorporates structural indicators like covenant waivers, forbearances, advisor engagements, below-par transactions, going-concern language, above-market rate increases, and PIK conversions, weighed against the company's filing history, since patterns like serial amendments and escalating concessions only emerge across filings over time. Routine refinancings and repricings don't trigger it. It's a screening signal, not a verdict on company health. <p><br/></p> # Who it's for and use cases Credit analysts, distressed and special situations investors, private credit and direct lenders, CLO managers, and anyone who tracks credit activity across the public market. Some examples of how the data is used: - Track credit deterioration through amendment, waiver, and forbearance progressions - Track competitive activity across the credit market: who's lending where, who's exiting, who's entering - Screen for distress signals across companies, sectors, and time - Surface refinancing pipelines by sector, maturity, and structure - Monitor portfolio companies as well as track peer credits, sector trends, and structural shifts - Build league tables for lenders, sponsors, agents, and advisors The taxonomy is a living framework that expands as credit markets evolve and new patterns surface in filings. <p><br/></p> # Example questions you can ask the Terrain Credit Analyst - Build league tables for banks, private credit lenders, and specialty lenders by deal count and volume - Which sub-sectors have the highest distress rates this quarter? Show me the top 20 - Build a sector table of closed deals this quarter showing total principal raised, split by facilities versus notes - Show me companies on their 4th or more amendment this quarter where leverage covenants were modified - Show me senior secured term loans maturing in the next 12 months sorted by maturity date - Show me companies that moved from bank syndicates to private credit this year - Show me super-priority facilities this year with counterparty details - Show me out-of-court restructurings this year with recovery rates below 70% - Show me amendments that added PIK toggle features this year by sector - Show me a breakdown of covenant amendments this quarter by covenant type (Cortex will break it down by leverage, interest coverage, liquidity, EBITDA, fixed charge, and more) - Show me AI infrastructure and datacenter financings this quarter - Show me distressed small and micro-cap credits this quarter - List forbearance agreements expiring in the next month <p><br/></p> # Trial access This listing is a free trial preview. It includes a rolling 45-day snapshot of credit events on a seven-day delay. The full product delivers real-time event capture and complete historical coverage, contact us for access. We'd love your feedback as you explore. <p><br/></p> # Built with you Terrain works closely with those who use or are interested in our products. The data evolves with the market. New themes, structures, and cuts shaped by how you work. Tell us what would make it more useful for you. <p><br/></p> # Get Started After installing the listing, query the data directly or open the pre-built Cortex agent in Snowflake Intelligence to ask questions in natural language. Reach out with questions about the data or full product access. Read our weekly credit roundup at [terrainlabs.substack.com](https://terrainlabs.substack.com) to see what we find in the data each week. <p><br/></p> # Considerations A few things to know before using the data: - Each row is a credit event linked to its source 8-K. A single transaction can surface across multiple filings as it progresses (announced, then closed), so filter by event type and status when aggregating to avoid double-counting. - Distress signals are screening flags, not determinations of company health. - Lenders on a deal do not necessarily fund the full principal. Syndicated facilities distribute capital across multiple lenders, often without individual allocations disclosed. - Found something that looks off? Please let us know, it helps us improve. <p><br/></p> # Disclaimer This data is for informational purposes only and is not investment advice. It is extracted from public SEC filings using AI. While our validation framework reduces errors, AI can make mistakes, and the data should be independently verified against source filings.
数据集概述：SEC 8-K Structured Credit Events and Distress Signals
基本信息
- 提供者：Terrain
- 定价：免费（提供试用预览）
- 更新频率：每日
- 时间覆盖：最近45天（每7天延迟一次快照）
- 数据来源：SEC 8-K 文件
- 交付方式：安全共享
- 许可条款：标准
数据集内容
该数据集深度结构化，收录了SEC 8-K文件中披露的所有信用事件，包括：
- 新发行与新设施：交易条款、工具、优先级、规模、状态
- 修订、违约、重组、宽限与债务交换
- 对手方信息：标准化名称与角色（贷款人、代理人、借款人、顾问）及类型（银行、私人信贷、专业贷款机构、承销商等），同时保留规范名称和文件原始名称
- 定价结构：利差、票面利率、PIK特征、基准利率、到期日
- 修订类型分类：定价、到期日、契约、抵押品、承诺额、增量、PIK切换等
- 设施结构：双边、俱乐部、小型银团、大型银团、内部/专业贷款
- 对手方变动：贷款人退出、新增、顾问聘用
- 困境信号：基于公司历史文件的结构性指标筛选标记
- 事件摘要：每笔事件的分析性叙述，涵盖交易条款、背景及公司信用轨迹
- 主题标签：AI基础设施融资、私人信贷、潜在负债管理、并购融资、内部贷款等
- 行业分类：面向信用分析的行业与子行业分类
- 来源文件链接：直接链接至SEC.gov上的8-K文件
- 预置Cortex Agent与语义视图：用于Snowflake Intelligence的自然语言分析
数据结构
- 核心表：
CREDIT_EVENTS_PREVIEW - 关键字段：
ACCESSION：SEC文件编号BORROWER：法律借款实体CIK：SEC中央索引键COMPANY_NAME：文件实体名称COUNTERPARTIES：标准化对手方简称数组COUNTERPARTY_DETAILS：结构化数据，含名称、角色、类型、备注COUNTERPARTY_TYPES：对手方类型数组COUPON_PCT_MIN/MAX：最低/最高固定票面利率CURRENCY：货币（USD、EUR、JPY等）- 其他字段涵盖交易状态、事件类型、优先级、利差、困境信号等
构建方法
- Terrain的AI分析师实时读取每份SEC 8-K文件，通过数百页的信用协议、契约和附件提取关键信息。
- 基于多年历史文件构建的方法论与知识库，用于指导新披露的解析，并减少错误。
- 采用验证框架进行修正，显著降低失误率。
困境信号判定依据
- 纳入的结构性指标包括：契约豁免、宽限、顾问聘用、低于面值交易、持续经营疑虑、高于市场利率增长、PIK转换等。
- 综合公司历史文件中的模式（如连续修订、逐步升级的让步）进行判断。
- 常规再融资与重新定价不会触发该信号。该标记为筛选信号，非公司健康状况的最终判定。
适用人群与用例
- 目标用户：信用分析师、困境与特殊情况投资者、私人信贷与直接贷款机构、CLO管理人及追踪公开市场信用活动的专业人士。
- 典型用例：
- 通过修订、豁免和宽限进程追踪信用恶化
- 追踪信用市场的竞争动态（谁在放贷、谁在退出、谁在进入）
- 按公司、行业和时间筛选困境信号
- 按行业、到期日和结构挖掘再融资管道
- 监控投资组合公司及同行信用、行业趋势和结构性变化
- 为贷款人、发起人、代理人和顾问构建排名表
潜在问题与注意事项
- 每行数据对应一个信用事件，关联其来源8-K文件。同一笔交易可能在多份文件中出现（如公告、完成），聚合时需按事件类型和状态筛选以避免重复计数。
- 困境信号为筛选标记，非公司健康状况的最终判定。
- 交易中的贷款人不一定提供全部本金；银团设施的资金分布可能不公开。
- 数据基于AI从公开SEC文件中提取，虽经验证框架减少错误，但仍需独立核实。
使用方式
- 安装后可直接在Snowflake中查询数据，或通过预置的Cortex Agent在Snowflake Intelligence中以自然语言提问。
- 提供试用预览，含45天滚动快照（7天延迟）；完整产品提供实时数据与完整历史覆盖。
