Quarterly Mark December 2023 - 6

ANDREW W. LO
is the Charles E.
and Susan T. Harris
professor at the
MIT Sloan School
of Management in
Cambridge, MA.
alo-admin@mit.edu
KEY FINDINGS
* The use of natural language processing (NLP) in finance has evolved
significantly over the past few decades with the growth of data,
storage, and computational power. NLP is now used for a wide range of
sophisticated tasks, including asset management, risk management, and
impact investing.
MANISH SINGH
is a PhD student in the
Electrical Engineering
and Computer Science
Department at the
Massachusetts Institute
of Technology in
Cambridge, MA.
smanish@mit.edu
CHATGPT
is a chatbot developed
by OpenAI, San
Francisco, CA.
* The development of deep learning-based large-language models like
GPT-3/ChatGPT have significantly advanced the applications of NLP
in finance. These models have the ability to understand and generate
human-like language, making them useful for various tasks, including
assisting in the writing of this article.
* Solving problems related to data bias, high computational needs, and
inaccurate responses generated by the models will make NLP models
even more accessible and indispensable.
ABSTRACT
Natural language processing (NLP) has revolutionized the financial
industry, providing advanced techniques for the processing, analyzing,
and understanding of unstructured financial text. The authors provide a
comprehensive overview of the historical development of NLP, starting
from early rules-based approaches to recent advances in deep learning-
based NLP models. They also discuss applications of NLP in finance along
with its challenges, including data scarcity and adversarial examples, and
speculate about the future of NLP in the financial industry. To illustrate the
capability of current NLP models, a state-of-the-art chatbot is employed
as a co-author of this article.
I
n the 1960s, a natural language processing (NLP) program called ELIZA was
developed by Professor Joseph Weizenbaum from the Massachusetts Institute
of Technology (Weizenbaum 1966), the first chatbot in the history of computer
science. It used a simple form of pattern matching to respond to certain keywords
and phrases, and although its capabilities were quite limited by today's standards,
its impact was unmistakable. As Weizenbaum explained, " Once my secretary, who
had watched me work on the program for many months and therefore surely knew
it to be merely a computer program, started conversing with it. After only a few
interchanges with it, she asked me to leave the room " (Christian 2013). In recent
years, deep learning techniques have enabled the development of advanced
chatbots like ChatGPT that generate even more human-like responses. The journey
from ELIZA to ChatGPT reflects the ongoing evolution of NLP, as researchers
continue to push the boundaries of what is possible with NLP and machine
learning (ML).
6 | From ELIZA to ChatGPT: The Evolution of Natural Language Processing and Financial Applications

Quarterly Mark December 2023

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