Developing a "state of the art" reasoning engine to extract forward looking and actionable insights for financial institutions from unstructured data sets

开发“最先进”的推理引擎，从非结构化数据集中为金融机构提取前瞻性且可行的见解

• 批准号: 10054206
• 金额: $ 25.44万
• 依托单位: AUQUAN LTD
• 依托单位国家: 英国
• 项目类别: Collaborative R&D
• 财政年份: 2023
• 资助国家: 英国
• 起止时间: 2023 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=10054206
• 关键词: Developing; state; art; reasoning; engine

Information overload is a common problem, particularly in data-heavy industries like professional and financial services, specifically in regulatory compliance, where keeping track of regulatory developments across multiple geographies and asset classes is a major challenge. Unstructured text such as regulatory updates and the associated discussions, contain much valuable information that is often missed by data analysts and key decision makers, for example when assessing risk and implications on business operations.We aim to: 1) Spot all regulatory changes, and 2) Classify the changes under right categories (to be defined) so that they can be routed to the right teams. This is the intelligence enhancement part. No solution exists today to solve this problem, this is mostly done in house by a team of analysts who often manually go through all content online. This is often not exhaustive and can be inaccurate.Auquan will solve this significant, unmet, global need by developing technology that exhaustively extracts information from unstructured datasets and enhances the "so-what" of the data to reveal relevant insights without overwhelming the user with high volumes of data, ultimately leading to better decisions and more productive analysts. We also plan to investigate exciting wider use-cases for our technology outside the finance sector including in the insurance and legal sectors.

信息过载是一个常见的问题，特别是在专业和金融服务等数据密集型行业，尤其是在监管合规方面，在这些行业，跟踪多个地区和资产类别的监管动态是一项重大挑战。非结构化文本，如法规更新和相关讨论，包含许多有价值的信息，这些信息经常被数据分析师和关键决策者遗漏，例如在评估对业务运营的风险和影响时。我们的目标是：1)发现所有法规变化，2)将变化归类到正确的类别(待定义)，以便将它们发送给正确的团队。这是智力增强的部分。目前还没有解决这个问题的解决方案，这主要是由一个分析师团队在内部完成的，他们经常手动在线浏览所有内容。这通常不是详尽的，也可能是不准确的。Auquan将通过开发技术来解决这一重大的、未得到满足的全球需求，该技术可以从非结构化数据集中详尽地提取信息，并增强数据的“某某”，以揭示相关见解，而不会让用户因海量数据而不堪重负，最终带来更好的决策和更高效的分析师。我们还计划调查我们的技术在金融部门以外的令人兴奋的更广泛的使用案例，包括在保险和法律部门。