Artificial Intelligence (AI) as a tool to improve investment analysis processes

AI has really taken off and it has become a very popular theme, especially since ChatGPT was launched last year. Before delving into some of the applications that this tool could provide to investment firms, it is relevant to put into context what is ChatGPT?  ChatGPT is a language model that has been trained with a great amount of text data so it can perform a great variety of tasks related to natural language. Its capacity to understand the context and intention behind the users’ questions and consults make it a very useful tool to develop chatbots and improve accuracy in systems that search for information. ChatGPT was developed by OpenAI, an artificial intelligence research organization founded in 2015 based in San Francisco, California. 

Some benefits that Chat GPT and other large language models (LLMs) could bring into the investment analysis processes are: 

Large Database Processing. Analysts are often overwhelmed by the great amount of material that must be processed to analyze a company, like quarterly reports, press releases, investor calls, generating an endless flow of information. This forces investment teams to focus on deep research, in a limited time frame to make investment decisions. Therefore, driven tools such as ChatGPT and LLMs, could perform time-consuming tasks for analysts that drain disproportionate resources on tasks that may end up not being relevant, or may end up not being done at all.

Increased coverage of presentations, corporate reports and meeting summaries. Analysts typically cover dozens of companies in one or more sectors, while also monitoring competitors and potential investment candidates. During earnings season, it is impossible to participate in all the calls of the companies under coverage, as well as other related calls that may be of interest. In this sense, ChatGPT and LLMs can provide a solution, generating summaries with a high number of quality and accuracy. Also, these models make it possible to identify substantial changes in the text of corporate presentations, which could indicate a change in trend or strategy in the direction of the company and that will undoubtedly require further analysis. Furthermore, ChatGPT can condense Zoom transcripts and clean up raw notes into defined, easy-to-use formats, such as full sentences or key points. It can also be used to extract topics from longer, blurry text, which helps analysts instantly make sense of a rambling conversation.

Promote productivity. Beyond the technical issues, ChatGPT sets out a cultural challenge; where data science teams must actively promote its benefits and show tangible examples. Under this context, analysts need to figure out what they can automate, become familiar with the technology, and comprehend its limitations to obtain high-quality results. New LLM technologies provide easy access for anyone with basic programming knowledge. Then, once those logistics bottlenecks in the analysis processes have been identified, AI can be creatively implemented to create tangible efficiencies.

Finally, it has been speculated that all these new technological capabilities could eventually replace human capital. Nevertheless, we agree with the opinion of specialists in the sense that both variables of the equation are complementary. When combining the intellectual human power reflected in the experience to analyze companies and market trends with the ChatGPT processing power, we can increase the AI benefit, improve the efficiency of the analysis process, and ultimately, make better investment decisions.

Source: AB- AllianceBernstein

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