{"schemaVersion":3,"canonical":"https://cufe-digital-finance-center.vercel.app/records/reports/riskatlas-database-capability-report-2026","webUrl":"https://cufe-digital-finance-center.vercel.app/reports/riskatlas-database-capability-report-2026","organization":{"id":"https://cufe-digital-finance-center.vercel.app/#organization","name":"中央财经大学人工智能与数字财经研究中心","nameEn":"CUFE Institute for AI & Digital Finance"},"record":{"id":"https://cufe-digital-finance-center.vercel.app/reports/riskatlas-database-capability-report-2026#webpage","type":"WebPage","contentType":"reports","url":"https://cufe-digital-finance-center.vercel.app/reports/riskatlas-database-capability-report-2026","recordUrl":"https://cufe-digital-finance-center.vercel.app/records/reports/riskatlas-database-capability-report-2026","textUrl":"https://cufe-digital-finance-center.vercel.app/text/reports/riskatlas-database-capability-report-2026","textUrlEn":"https://cufe-digital-finance-center.vercel.app/en/text/reports/riskatlas-database-capability-report-2026","urlEn":"https://cufe-digital-finance-center.vercel.app/en/reports/riskatlas-database-capability-report-2026","title":"RiskAtlas全球制裁与出口管制数据库建设与能力报告","titleEn":"RiskAtlas Global Sanctions and Export Controls Database: Construction and Capability Report","summary":"中央财经大学国家财经战略研究院发布《RiskAtlas全球制裁与出口管制数据库建设与能力报告》，介绍该全球制裁与出口管制数据库的建设背景、数据治理框架、质量体系、生产验收基线与AI原生服务能力。","summaryEn":"A capability report from NAFES describing the governance framework, data quality system, production acceptance benchmarks and AI-native services of the RiskAtlas global sanctions and export-control database, developed with research and engineering support from CUFE AI²F.","body":"## 报告来源与背景\n\n《RiskAtlas全球制裁与出口管制数据库建设与能力报告》由中央财经大学国家财经战略研究院发布，研究与建设支持单位包括中央财经大学人工智能与数字财经研究中心（CUFE AI²F）以及经济制裁和国别风险研究团队（国家财经战略研究院独立课题组）。报告于2026年7月20日首次发布，此后随数据库能力更新持续修订；本资料介绍对应的版本以2026年8月31日认证数据快照为基础。\n\nRiskAtlas是面向全球制裁、出口管制与跨境限制措施研究的数据平台，整理美国、英国、欧盟、联合国及其他多个法域发布的官方公开限制措施信息，支持实体检索、来源核验、研究分析与机器可读调用。\n\n## 数据库规模与覆盖\n\n截至报告所依据的数据快照，RiskAtlas收录124,527条官方来源记录，其中73,963条处于当前有效状态，50,564条为历史状态记录，覆盖24个发布法域，纳入38个持续更新的官方来源。报告说明，来源记录是数据库的基础统计单位，指某一官方名单或公告中的规范化条目；由于同一现实世界主体可能同时出现在多个法域或名单中，记录总量反映的是来源覆盖规模，不直接等同于全球唯一受限制主体的数量。\n\n## 数据治理逻辑\n\n报告将数据库的治理框架概括为来源优先、语境保留、字段规范、时间分层、候选关联与质量度量等相互衔接的环节：\n\n- **来源优先与语境保留**：以官方或政府运营渠道作为名单事实的主要依据，记录保留发布机构、法域、名单名称、更新状态和官方链接；对以单份公告发布、缺少统一合并文件的来源，按公告台账组织并保留文号、日期和措施状态。\n- **字段规范**：将不同来源对姓名、别名、对象类型、国家或地区、项目和日期的表达方式统一为规范检索字段，同时保留各来源的原始表达，供查询结果解释具体名单含义。\n- **时间分层**：区分官方列名、修订、生效或撤销日期与平台观测到变化的日期，分别服务于历史结构研究与持续监测；只有具备已核验正式事件的记录才标记为官方撤销或失效，单纯的名单缺席不自动视为撤销。\n- **候选关联的证据层次**：报告将主体关联分为名称信号、多字段一致和官方文件明示三个层级，明确名称相同或近似只构成候选线索，不构成同一法律主体、所有权或控制关系的认定。\n- **行业与战略主题标签**：组织类型的来源记录采用联合国《所有经济活动的国际标准行业分类》（ISIC Rev.5）标注主行业，并叠加半导体、无人系统、关键矿产、航空航天与防务技术、人工智能、量子技术、网络安全等独立战略主题标签；两类标签均要求证据充分才发布，证据不足时保持未分类，且不从制裁理由反推行业归属。\n\n## 数据质量体系\n\n报告从完整性、可追溯性、一致性、唯一性、及时性和统计可解释性六个维度说明数据库的质量管理方式，并引入“来源可得性”与“解析保真度”两项指标分别衡量官方来源本身提供的信息范围与平台处理这些信息的准确程度，避免把上游来源的结构性信息缺失误判为数据库的处理错误。\n\n## 生产服务与验收基线（2026年8月31日）\n\n报告披露了RiskAtlas API 1.9版本的生产验收结果：217项前端与契约测试全部通过，34项功能验收全部通过，7类API访问控制场景全部通过；在10万条记录的批量筛查测试中，峰值处理能力约为每秒5,857条，请求响应时间的95百分位为1.22秒；在持续一小时的10万条筛查测试中，请求响应时间95百分位为711毫秒，测试期间未出现请求错误，接口返回结果与数据库记录之间也未发现一致性差异。报告同时说明，这些指标反映特定测试条件下的受控验收结果，不构成面向具体客户的服务等级承诺，机构用户接入前应结合自有历史样本完成影子筛查和服务等级验收。\n\n## AI原生数据服务能力\n\n报告说明RiskAtlas以OpenAPI 3.1描述稳定接口（基址为/api/v1），将API主版本、响应契约版本、服务构建版本、数据发布版本、分类体系版本和分类器版本作为六个相互独立的维度分别管理，并提供与MCP（Model Context Protocol）兼容的只读工具入口，将实体检索、记录读取、状态时间线、来源核验、统计查询和行业分析组织为可供语言模型和智能体调用的服务；面向语言模型的检索可使用response_mode=compact参数以精简字段返回。\n\n## 引用与使用边界\n\n报告建议的数据库整体引用格式为：中央财经大学国家财经战略研究院经济制裁和国别风险研究团队. RiskAtlas全球制裁与出口管制数据库[DB/OL]. [检索日期]. https://atlas.scholarforce.ai/。报告明确指出，数据库中的名称重合、候选关联和统计汇总不构成法律主体认定、交易结论或法律意见，来源名单的法律效力应以发布机构的正式文件及其后续修订为准；引用具体数量时应同时说明统计对象、状态范围、法域或来源范围及数据快照日期。","bodyEn":"## Provenance\n\nThe RiskAtlas Global Sanctions and Export Controls Database: Construction and Capability Report was published by the National Academy of Financial and Economic Strategy (NAFES) at Central University of Finance and Economics, with research and engineering support from the CUFE Institute for AI & Digital Finance (CUFE AI²F) and the Economic Sanctions and Country Risk Research Team, an independent research group of NAFES. The report was first published on 20 July 2026 and has since been revised as the database's capabilities have developed; this record reflects the version anchored to the certified data snapshot of 31 August 2026.\n\nRiskAtlas is a data platform for research on global sanctions, export controls and cross-border restriction measures. It organises official public restriction information published across the United States, the United Kingdom, the European Union, the United Nations and other jurisdictions, supporting entity search, source verification, research analysis and machine-readable access.\n\n## Database scale and coverage\n\nAs of the snapshot underlying the report, RiskAtlas held 124,527 official source records, of which 73,963 were current and 50,564 held historical status, spanning 24 issuing jurisdictions and 38 continuously maintained sources. The report treats the source record as the database's basic unit of measurement — a normalised entry within a single official list or notice. Because a real-world subject may appear across multiple jurisdictions or lists, total record counts describe source coverage rather than a deduplicated count of globally unique restricted subjects.\n\n## Governance framework\n\nThe report organises its governance approach around source priority and context preservation, field normalisation, temporal layering, tiered evidence for candidate linkage, and industry and strategic-topic tagging. Official or government-operated channels serve as the primary basis for listing facts, with issuing authority, jurisdiction, list name, status and official links preserved on each record. Name matches alone are treated as candidate leads rather than identity determinations; only corroborated formal events support a \"revoked or lapsed\" status, and mere absence from a current list is not automatically read as revocation. For organisational records, primary industry is tagged under UN ISIC Rev.5 with independently maintained strategic-topic labels (including semiconductors, unmanned systems, critical minerals, aerospace and defence technology, artificial intelligence, quantum technology and cybersecurity); both types of tagging require sufficient evidence and are withheld rather than guessed when evidence is insufficient.\n\n## Data quality framework\n\nThe report describes quality management across completeness, traceability, consistency, uniqueness, timeliness and statistical interpretability, introducing separate \"source availability\" and \"parsing fidelity\" metrics to distinguish what official sources actually disclose from how accurately the platform processes that disclosed information — avoiding the misclassification of upstream structural gaps as platform processing errors.\n\n## Production acceptance baseline (31 August 2026)\n\nThe report discloses production acceptance results for RiskAtlas API 1.9: 217 of 217 frontend and contract tests passed, 34 of 34 functional checks passed, and all seven API access-control scenarios passed. A 100,000-record peak screening test reached approximately 5,857 records per second with a 1.22-second p95 request time; a one-hour sustained run of 100,000 screenings recorded a 711 ms p95, with zero request errors and no consistency mismatches between API responses and underlying database records. The report notes that these figures describe controlled acceptance testing under specific conditions and do not constitute a customer-specific service-level commitment; institutional users are advised to complete shadow screening and service-level validation with their own historical samples before production use.\n\n## AI-native service capabilities\n\nThe report describes a stable API base (`/api/v1`) documented with OpenAPI 3.1, with six independently versioned dimensions — API major version, response contract version, service build version, data release version, taxonomy version and classifier version — plus an MCP (Model Context Protocol)-compatible read-only tool endpoint that organises entity search, record retrieval, status timelines, source verification, statistics and industry analysis for use by language models and agents. A `response_mode=compact` parameter is available to return a reduced field set for language-model consumption.\n\n## Citation and usage boundaries\n\nThe report's recommended database citation reads: Economic Sanctions and Country Risk Research Team, National Academy of Financial and Economic Strategy, Central University of Finance and Economics. RiskAtlas Global Sanctions and Export Controls Database [DB/OL]. [access date]. https://atlas.scholarforce.ai/. The report states explicitly that name overlaps, candidate linkages and aggregate statistics do not constitute legal-entity determinations, transaction conclusions or legal advice, and that the legal effect of any listing follows the issuing authority's official documents and subsequent amendments. Citations of specific figures should state the statistical unit, status scope, jurisdiction or source scope, and the snapshot date.","inLanguage":["zh-CN","en"],"rights":"link-only","datePublished":"2026-09-06","dateModified":"2026-09-06","version":1,"authors":[],"corporateAuthor":"中央财经大学人工智能与数字财经研究中心","originalPublication":{"id":"https://atlas.scholarforce.ai/docs","type":"CreativeWork","title":"RiskAtlas全球制裁与出口管制数据库建设与能力报告","authors":["中央财经大学国家财经战略研究院经济制裁和国别风险研究团队"],"authorEntities":[{"name":"中央财经大学国家财经战略研究院经济制裁和国别风险研究团队"}],"publisher":"中央财经大学国家财经战略研究院","datePublished":"2026-07-20","url":"https://atlas.scholarforce.ai/docs"},"topics":[{"id":"https://cufe-digital-finance-center.vercel.app/topics/compliance#topic","url":"https://cufe-digital-finance-center.vercel.app/topics/compliance","name":"全球化合规"},{"id":"https://cufe-digital-finance-center.vercel.app/topics/finance#topic","url":"https://cufe-digital-finance-center.vercel.app/topics/finance","name":"财经"},{"id":"https://cufe-digital-finance-center.vercel.app/topics/technology#topic","url":"https://cufe-digital-finance-center.vercel.app/topics/technology","name":"科技"}],"regions":["中国","国际"],"report":{"recordMode":"source-record","keyFindings":["截至报告所依据的数据快照，RiskAtlas收录124,527条官方来源记录，其中73,963条当前有效，覆盖24个发布法域和38个持续更新来源。","数据库以来源优先、语境保留、字段规范、时间分层、候选关联和质量度量构成治理框架，仅在具备已核验事件时才将记录标记为官方撤销或失效。","组织类型记录采用联合国ISIC Rev.5行业分类标注主行业，并叠加半导体、关键矿产、人工智能等独立战略主题标签；证据不足时保持未分类，不从制裁理由反推行业归属。","2026年8月31日生产验收显示，API在10万条记录的一小时持续负载测试中请求响应时间95百分位为711毫秒，测试期间未出现请求错误或接口—数据库一致性差异。","报告明确名称重合、候选关联和统计汇总仅构成研究线索，不构成同一法律主体认定，法律效力以官方文件为准。"],"methodology":"报告基于2026年8月31日认证数据快照及同期生产验收测试结果，说明数据库的来源治理框架、字段规范方法、候选关联证据分级、行业与战略主题分类方法，以及涵盖前端契约测试、功能验收、API访问控制、峰值与持续负载测试的验收设计。","limitations":"报告明确来源记录数量反映来源覆盖规模，不等同于去重后的现实世界受限制主体数量；行业与战略主题分类、法人识别参照和名称重合统计均为研究与检索辅助线索，不构成法律主体认定；峰值吞吐等验收指标为特定受控测试条件下的结果，不构成面向具体客户的服务等级承诺。","downloads":[]},"sources":[{"title":"RiskAtlas文档中心：RiskAtlas全球制裁与出口管制数据库建设与能力报告","url":"https://atlas.scholarforce.ai/docs"},{"title":"RiskAtlas能力报告：《RiskAtlas全球制裁与出口管制数据库建设与能力报告》发布","url":"https://atlas.scholarforce.ai/news/riskatlas-database-report-2026"},{"title":"RiskAtlas全球制裁与出口管制数据平台","url":"https://atlas.scholarforce.ai/"}],"citations":{"apa":"中央财经大学国家财经战略研究院经济制裁和国别风险研究团队. (July 20, 2026). RiskAtlas全球制裁与出口管制数据库建设与能力报告. https://atlas.scholarforce.ai/docs"},"corrections":[]}}