Financial Intelligence System & chatGPT

Many asset managers feel like they are drowning in information flow about their portfolios. Given the many sources of information moving asset prices - global news, market sentiment swings, and regulatory changes, among others - many turn to chatbot to distill news into digestible insights. And while general-purpose chatbot deliver useful insights, they can also deliver inaccurate or irrelevant content. Using NLP analytics to enhance AI accuracy, MarketPsych created a dedicated financial intelligence system that filters, synthesizes, and summarizes the information affecting individual portfolios.

A variety of formats for information that conveys “signal” (not “noise”) are available, as depicted below:

The financial intelligence system described in this paper identifies material and timely asset-related information, summarizes it, and presents it in a readable format that is customized to each user’s workflow. The system pipeline is depicted in the figure below.

Note the several stages and the feedback loop in the pipeline. The process relies upon accurate media data obtained from a repository of NLP-tagged global media sentences, which MarketPsych calls “Radar Database.”

An example of a summarized portfolio news brief – covering the Chinese Energy Storage industry - is below:

Summarizing recent news about the Chinese energy storage industry can also be performed by commercial chatbot such as ChatGPT. However, chatbot based on web search frequently fail to find and identify useful recent news into their summaries.

In the infographic below, we show differences between a standard chatbot-created news summarization service and one bolstered by NLP tagging. In Appendix 1 we provide a detailed table comparing the 2 approaches and in Appendix 2, we provide annotated screenshots of MarketPsych Summaries against ChatGPT in Exhibits A through D.

To better appreciate the challenges faced by commercial chatbot, it helps to review the ChatGPT Web Search Pipeline which is outlined in the figure below. The weakness of the general chatbot approach is described further below in this section.

Financial intelligence requires consistent, comprehensive data retrieval from a curated database where every relevant article is captured and indexed. Unfortunately, web searches are inherently non-deterministic - the same query at different times yields different results based on SEO rankings, trending topics, and search engine algorithms.

Time-sensitive financial decisions require precise temporal filtering. Unfortunately, ChatGPT struggles with time-based queries like "show me all Apple news from the past week." Web search engines prioritize recent and popular content, rendering systematic historical retrieval of detailed news, breaking news, or thoughtful analysis difficult.

MarketPsych’s Summaries clearly outperform ChatGPT on the following US Defense industry summary, with recent and relevant updates on several companies in the US defense sector. ChatGPT was only able to surface one relevant (but uninteresting) event in total - L3Harris’ stock price decline - while MarketPsych's summaries mention L3Harris’ important newly-announced partnership with Joby Aviation.

MarketPsych’s Summaries also capture important overnight central bank news for bond and interest rate investors in the Americas, clearly outperforming ChatGPT, which was unable to find any recent central bank-related events, citing events from one to two months prior.

In the below example of summarization for U.S. data center company news, ChatGPT’s summary is a small subset of MarketPsych’s, which covers 4x more companies and events and invokes related market-moving macro factors such as US tariffs on AI Chip sales to China.

Integrating an NLP Engine into AI projects, such as news summarization, significantly boosts accuracy and utility. Such purpose-built summarization platforms are faster, more precise, and more adaptable than general model chatbot. MarketPsych’s NLP Engine combined with off-the-shelf financial news and document pipelines creates consistently relevant, timely insights for investors, as evidenced by the Radar Summaries & Alerts products offered through MarketPsych.

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