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

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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.