How to Generate Unique Insights from Unstructured Data using Natural Language Processing

Insights

The world has seen significant changes in technology and considerable pressure from regulatory bodies in the past decade. This, coupled with a highly competitive global landscape and pressure on margins, has led companies to focus on exploring new avenues of alpha generation or product differentiation.

By end-2019, 54% of the world’s population was able to go online. Content on products and services that corporations offer accounts for millions of records every day. Capital markets closely analyse numerical datasets that may be traditional or alternative. Textual data, often unstructured, requires even closer evaluation if it is to be successfully leveraged for financial analysis. A highly competitive market offers decision makers plenty of choices to choose from. Natural language processing (NLP) can extract insights from this vast universe of textual data, if the right implementation partner/s are selected, ROI is tracked meticulously and an incremental gains-based approach is adopted.

Key Takeaways

•The world’s internet users generate over 240bn emails, 6m blogs, and 700m tweets a day –
a flood of unstructured data in textual format. For decision makers in the capital markets,
this presents an opportunity to generate unique investment insights.

•A careful selection of reliable platforms integrated with a bespoke NLP solution would enable the
acquisition and analysis of textual data for enriching coverage of the equity universe, portfolio \
monitoring, ESG investing and formulating investment strategies.

•Amid the COVID-19-induced crisis, buy-side portfolio managers and sell-side coverage
analysts need to take informed decisions much faster than in an organisation’s adaptive
cycle. In addition to robust quantitative analysis, implementing a contextual and
scalable text-mining engine would enrich investment decision making.

Authors

Deepak Stephen

Director, Head of Data Science

Deepak leads Acuity Knowledge Partners’ (Acuity’s) Data Science practice, responsible for driving practice growth and ensuring service delivery governance across global clients including asset managers, hedge funds, private equity firms, investment banks, commercial banks, corporates, and consulting firms. He oversees a global team of data scientists and analysts across India, Sri Lanka, Costa Rica, and the UK.

Deepak has been with Acuity for over 12 years, actively driving practice strategy, product management, solution design and implementation of research and analytical services for global buy-side and sell-side clientele. Prior to joining Acuity, Deepak worked at Genpact as a Manager with the Analytics business unit, and with RR Donnelley and Sharekhan (BNP Paribas) in their capital markets businesses.

Usman Ahmad

Chief Data Scientist, Specialised Solutions

Usman is the Chief Data Scientist at Acuity, responsible for AI/ML strategy and implementation for key client relationships. He joined Acuity in 2018 and has over 10 years of experience in delivering analytical and risk management solutions to global capital markets participants using state-of-the-art platforms. Prior to joining Acuity, Usman worked at Lloyds Bank, Goldman Sachs and UBS in front-office and middle-office functions. He holds a Master’s degree in Mathematics and Computer Science from Imperial College London

Natural Language Processing (NLP) to Generate Truly Unique Insights from Unstructured Data