IntelPact - Contractual obligation extraction using artificial intelligence

IntelPact - 使用人工智能提取合同义务

• 批准号: 104100
• 金额: $ 6.33万
• 依托单位: COGNITIV+ LTD
• 依托单位国家: 英国
• 项目类别: EU-Funded
• 财政年份: 2017
• 资助国家: 英国
• 起止时间: 2017 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=104100
• 关键词: IntelPact; Contractual; obligation; extraction; using

"Companies are constantly challenged by the management of the ever-increasing contractual obligations, from payment schedules, delivery plans, to regulatory and compliance reporting. These tasks are currently done manually, going through every single contract, trying to detect the obligations by hand and somehow organising this information to be able to manage it.Currently, the only alternative to manual in-house contract management is professional service companies (lawyers or consultancies). Unfortunately, they also use the same methodology which means that they address the problem in a manual, non-standardised manner, allowing ample room for automation using innovative solutions.This project proposes the automation of the obligation extraction task using artificial intelligence, especially machine learning, natural language processing and smart contracts. Since the extracted information will be already in machine readable format we also propose the development of software the implements the workflows that have to do with obligation management(e.g. payment calendars, reporting notifications,etc.).The solution, accessed directly or as a service, will help legal, commercial and compliance professionals to accelerate contract review and analysis as well as avoid manual data entry into corporate systems allowing them to focus on higher value tasks. It will generate significant cost savings (50-90%) through the reduction of the time spent on manual tasks. On top of that, we expect significant operational risk reduction which will lead to reduced costs of litigation and potential penalties."

“从付款时间表、交付计划到监管和合规报告，公司不断受到日益增加的合同义务管理的挑战。这些任务目前都是手工完成的，要检查每一个单独的合同，试图手工检测义务，并以某种方式组织这些信息以便能够管理它。目前，替代手工内部合同管理的唯一选择是专业服务公司（律师或咨询公司）。不幸的是，他们也使用相同的方法，这意味着他们以手动、非标准化的方式解决问题，从而为使用创新解决方案的自动化提供了充足的空间。本项目提出利用人工智能，特别是机器学习、自然语言处理和智能合约，实现义务提取任务的自动化。由于提取的信息已经是机器可读的格式，我们还建议开发软件来实现与义务管理有关的工作流(例如：付款日历、报告通知等)。该解决方案可直接访问或作为服务访问，将帮助法律、商业和合规专业人员加速合同审查和分析，并避免手动将数据输入公司系统，使他们能够专注于更高价值的任务。通过减少花费在手工任务上的时间，它将产生显著的成本节约（50-90%）。最重要的是，我们预计操作风险将大幅降低，这将降低诉讼成本和潜在的罚款。”