Reshaping equity research business with AI

Published on 22 May 13:20 by Sam Yip
Tags: AI   China   equity   finance   growth   industry   localization   machine translation   management   research   tools   translation  

TranslateFX Reshaping equity research business with AI

The traditional business of equity research, where analysts would recommend certain securities or sectors to institutional investors, has faced tremendous challenges in recent years. The rise in passive investing has put downward pressure on revenue generated by equity research, while the introduction of MiFID II in 2018, which calls for unbundling of fees, has further undercut the demand for equity research reports.

As a result, investment banks have been cutting back on research output and sales staff, with institutional investors becoming more selective about how much equity research they would budget for.

These changes in business landscape have necessitated the need for investment banks to adopt new operating models for their equity research businesses. In a report by McKinsey, certain business strategies have been recommended for the development of equity research business, and we at TranslateFX see tremendous benefits for investment banks to take advantage of AI and natural language processing for the implementation of these strategies:

Strategies How AI can help
Establishing a research footprint that capitalizes on strengths of coverage in sectors and regions, and extending reach through joint ventures.By leveraging machine translation, banks can scale up research coverage in different regions as well as offering localized products to global audience. For example, European and Chinese banks can set up joint ventures publishing bilingual reports for different audience. This is a typical way through which a research business can grow.
Understanding the scarcity and perishability of ideas, and what value clients place on research in different forms -- reports, analyst and corporate-management access, conferences, and other forms of information and analytics.

Natural language processing is a powerful tool for the analytics of data and information in different textual forms, and machine learning can help predict clients' preferences of delivery and service
Adopting new technologies to generate novel investment ideas.

There are a number of ways AI can help, including the automated reading of earning transcript to assess management sentiment, and the automated identification of non-intuitive relationships between securities and market indicators.

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