Natural Language Generation (NLG) and Natural Language Processing (NLP) are data science technologies that leverage complex algorithms, linguistic rules, and machine learning in order to generate human-like written content without any manual effort from humans.
NLG analyzes information and generates words, phrases, and sentences in order to communicate meaningful results. NLP, on the other hand, is focused on understanding the meaning behind words and text. It takes unstructured inputs such as text and speech and transforms it into structured sets of data that can then be processed to gain insights.
ChatGPT, an AI tool that has been in the news a lot recently, is a narrative-generating service that uses natural language processing and machine learning to generate responses to queries. It works by breaking down an input sentence into smaller chunks, analyzing each of them for meaning, and using a deep learning algorithm to generate the most appropriate response. The response is then returned to the user, resulting in incredibly smooth-flowing conversations.
ChatGPT utilizes Deep Learning, which is one of the most advanced forms of data science where computers learn to perform tasks by processing large amounts of data. Unlike machine learning, which uses pre-programmed rules and techniques to solve problems, Deep Learning relies on networks of algorithms that can adapt and improve themselves over time. This means that machines are able to recognize patterns in data they are exposed to without needing instruction from humans.
Advancements in NLG, NLP, and Deep Learning are rapidly changing the way data is analyzed and content is created. So, can ChatGPT help you invest? Helping in the research process, it could assist by providing a business description of a company, information about business segments, competitors, acquisitions made in the past, and you might be able to gain insights by asking it to describe the economic moat of a business.
However, there’s also a lot that ChatGPT cannot do when being used as an investment research tool. Currently, ChatGPT does not perform its own computations or analysis, and therefore cannot analyze a company's financial health, its dividend quality, the intrinsic share price value or calculate the price/earnings ratio, for example. ChatGPT relies on information derived from elsewhere on the internet.
We can already see that ChatGPT won’t be replacing human analysts and financial advisors just yet. Maybe someday, but… not anytime soon.
A number of global investment banks including Bank of America Corp., Citigroup Inc., Deutsche Bank AG, Goldman Sachs Group Inc. and Wells Fargo & Co. are clamping down on ChatGPT by imposing restrictions on their employees and financial advisors. This comes as no surprise in the heavily regulated world of finance, where third-party software use and written statements are under the scrutiny of the compliance departments.
So don’t worry, your financial advisor won't recommend that you buy a stock just because ChatGPT told them to do so. However, we will see certain aspects of these new data science technologies that will indeed play a valuable role in the financial industry in the future.
NLG is helping to revolutionize the way investors perform fundamental analysis, allowing them to quickly and easily analyze vast amounts of financial data. NLG can be used to streamline research analysis, transforming complex data into a more digestible format that enables investors to make more decisions. By simplifying the abundance of raw financial data, NLG is helping investors make better decisions faster than ever before.
AnalytixInsight uses NLG to generate research reports on 50,000 publicly-traded companies. With data processing capability of over 100 billion daily computations, we perform the financial computations that ChatGPT can’t do itself, and through NLG we create narrative flowing machine-created research reports on-demand. AnalytixInsight has already published more than 67,000 company research reports for data-giant Refinitiv’s users, using NLG to create narrative paragraphs with insightful analysis on a company’s dividend quality, earnings analysis as well as cash flow analysis for pre-revenue companies.
New AI tools such as Natural Language Generation and Natural Language Processing are beginning to play an important role in the financial industry. Although they aren’t about to completely replace humans any time soon, their attributes are increasingly assisting investors and research analysts crunch through the mountains of financial data that is consumed when making informed investment decisions. AI and NLG are making it faster, with fewer errors, and accessible to all.
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