Our long experience at SumUp Analytics has clearly revealed that NLP users have common characteristics including a need to identify novel content, value what makes it novel, and overcome language barriers. We discuss how NLP and next generation text analytics has made significant progress in addressing these challenges. Finance professionals can now leverage these new technologies to consume large-scale text information more quickly, efficiently, and comprehensively. 80% of data is unstructured (in the form of text), growing at 50% per year. While it is overwhelming & comes with many challenges, many financial professionals recognize the opportunity to leverage text-data. We have worked with clients ranging from financial services companies to social media companies to the U.S. government on how they're incorporating text-data into their research, compliance, risk processes. We provide 3 practical applications of NLP/text-data where clients have seen success including researching trading signals from text data, incorporating NLP to increase efficiency in compliance process, and using text-data to build ESG investment products.
Emmanuel is CEO and co-founder of SumUp Analytics, an AI startup based in San Francisco developing an ultra-fast, large-scale text analytics platform. Prior to co-founding SumUp Analytics, Emmanuel served as Head of Research for Mortgages and Securitized Credit at BlackRock and was a member of the Systematic Fixed Income investment committee. While at BlackRock, he oversaw investment solutions ranging from multi-strategy hedge-funds to smart beta products, ETFs and long-only institutional solutions, totaling ~$65 billion of AUM. He also co-invented BlackRock first smart-beta fixed-income solution: FIBR. Emmanuel was a proprietary trader at Societe Generale in New York before BlackRock and started his career in finance at Caisse des Depots et Consignations. Emmanuel holds an MFE from UC Berkeley and an MSc in Applied Math from Ecole Centrale Lyon.