Meirav Peleg Landau
ChatGPT - The future of AI and its potential use in the financial sector
It was impossible to ignore ChatGPT (Generative Pre-trained Transformer) in the last few weeks. The most talked about advancement in AI deployment occurred on November 30, when OpenAI released ChatGPT, a chatbot described as “the most advanced, user-friendly chatbot to enter the public domain.”. Altman, OpenAI CEO, says ChatGPT reached 1 million users in less than a week!!
In the following article we will briefly explain what ChatGPT is and how it might (and will) be useful in financial markets.
ChatGPT: What is it?
An open-source, end-to-end dialogue system built on top of the GPT-3 language model, which is a powerful natural language processing (NLP) model that can generate human-like text from a few words of input.
ChatGPT is designed to enable developers to quickly build and deploy conversational AI agents for chatbots, virtual assistants, and other interactive applications.
According to Sequoia Capital, one of the most important American venture capital firms, generative AI is still in its infancy, and the application space is just getting started. Sequoia states that "this first wave of Generative AI applications resembles the mobile application landscape when the iPhone first came out—somewhat gimmicky and thin, with unclear competitive differentiation and business models...it’s hard to imagine a future where machines don’t play a fundamental role in how we work and create.", as described in their chart below:
Why is ChatGPT better than traditional chatbots?
Unlike traditional chatbots, ChatGPT provides more accurate and detailed responses than traditional chatbots. Because ChatGPT is trained with a large volume of data, it is able to learn and adapt to different conversational styles and contexts, making it more versatile.
What are ChatGPT's current weaknesses?
ChatGPT, like any other technology, has its limitations and weaknesses. These limitations and weaknesses will be addressed in future versions:
Since ChatGPT is a machine learning system, it is only as good as its training data, so poor quality training data can result in inaccurate or misleading responses.
It is not yet possible for ChatGPT to understand the full range of human language and meaning, so it cannot always provide a complete or accurate response to certain questions.
As a complex, large system that requires significant computing resources to run, ChatGPT can sometimes be difficult or expensive to use.
Because ChatGPT is programmed to provide logical and coherent responses, it can even be convincing when wrong. This could cause misinformation.
A chatGPT can be abused to write phishing emails, steal instructions, write malware and more
It is likely that these weaknesses will be addressed and overcome in future iterations of ChatGPT as the technology continues to advance and improve.
What is the best way for the financial industry to use ChatGPT?
ChatGPT technology can help the financial industry improve its operations and provide better customer service in a number of ways. Here are a few examples:
Customer service tasks can be automated using ChatGPT, such as answering frequently asked questions or providing detailed product information.
Analyze large amounts of data to gain valuable insight into financial firms' operations and make better-informed decisions.
Provide accurate and personalized answers to customer questions in real-time, so that inquiries can be resolved more quickly and efficiently.
Provide personalized product or service recommendations based on a customer's preferences and needs.
Produce human-like text that can be used in marketing materials to assist with content creation. With ChatGPT, you can create marketing campaigns, write product descriptions, or even create blog posts.
Allow customer service representatives to focus on more complex and high-value tasks by automating routine tasks.
It is difficult to predict the future of ChatGPT, as it depends on a wide range of factors such as advances in artificial intelligence and machine learning, market demand, and the development of competing technologies. It is likely, however, that ChatGPT and other language models will continue to play a major role in financial applications, including chatbots, virtual assistants, and process automations.