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

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，特别是在监管合规方面，跟踪多个地区和资产类别的监管发展是一个重大挑战。非结构化文本（如监管更新和相关讨论）包含许多数据分析师和关键决策者经常错过的有价值信息，例如在评估风险和对业务运营的影响时。我们的目标是：1）发现所有监管变化; 2）将变化分类到正确的类别（待定义），以便将其发送到正确的团队。这是智能增强部分。目前还没有解决方案来解决这个问题，这主要是由一个分析师团队在内部完成的，他们经常手动浏览所有在线内容。Auquan将通过开发技术来解决这一重要的、未满足的全球需求，该技术可以从非结构化数据集中全面提取信息，并增强数据的“真实性”，以揭示相关的见解，而不会让大量数据淹没用户，最终导致更好的决策和更高效的分析。我们还计划在金融领域之外，包括保险和法律的领域，为我们的技术研究更广泛的令人兴奋的用例。

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.