Using ChatGPT for Finance
ChatGPT is the newest offering in the world of AI. Everyone I know of has heard about it and is either scared or excited about the possibilities. In this article, I wanted to explore how ChatGPT can be used in the field of finance and investments.
The most common use case is to learn about a concept. You just ask any question about any topic, and it gives you a well-informed answer with enough details to provide you clarity on the topic. However, it can do a lot more. OpenAI, the company behind ChatGPT opened its API for everyone. So, now you can integrate the ChatGPT API in your own software application and get the complete power of this large language learning model in your software. With time, we will see this being implemented by banks and other financial institutions in their processes.
Let’s look at some of the use cases.
With its ability to understand and process large amounts of data, ChatGPT can be used to analyse financial statements, market data and news to perform investment analysis and even predict stock prices. This will involve all the steps that you would take for any machine learning model including collecting and preprocessing data, and then training the ChatGPT model to understand the data and generate insights. Depending on your goal, you would be able to predict stock prices, identify emerging trends, and even provide buy/sell recommendations on stocks.
Financial Fraud Detection
ChatGPT can be trained to help detect and prevent fraud in financial transactions. It’s ability to recognize patterns can be used to identify unusual activity and alert the relevant authorities or even stop the transaction from going through. As an example, if a customer makes an unusually large transaction from a different location that his usual location, ChatGPT can identify and flag this transaction. Similarly, it can detect credit card fraud. For example, if a credit card is used multiple times from different locations in a short period of time, it can recognize this and take appropriate action. Similarly, it can also be used for detecting insurance fraud, such as someone filing multiple claims.
ChatGPT can also be applied to risk management to analyze various risks such as market risk, credit risk, and operational risk. We can train the model to analyze various market data such as stock prices, interest rates, commodity prices, etc. to identify potential risks. Similarly, it can be trained on loan data such as credit scores, financial statements and other relevant data to assess the borrower’s creditworthiness. It can also be used to analyze patterns in existing loans to identify the risk of default.
Customer service is an important part of any financial institution’s business. ChatGPT can be trained on the vast amount of content on products and services offered by them, and then it can act as a virtual assistant to help customers answer their queries.
As mentioned earlier, we can train ChatGPT to analyze loan applications and credit scores to assess the customer’s creditworthiness and ability to pay. This way banks can ass the risk of default in each application and decide whether to accept or reject loan applications.
ChatGPT can also be used to prevent money laundering. It can be used for detecting and reporting suspicious activities. Financial institutions can do so by implementing a ChatGPT powered chatbot that will chat with the customer and collect and analyze their transactional data. Let’s take an example. Let’s say a customer initiates a transfer of $100,000 to a recipient in another high-risk country. The chatbot can initiate a chat with the customer and ask them questions about this transaction such as the purpose of the transaction, the relationship with the recipient, and so on. Based on the training data, if the bot doesn’t the reasons legitimate and suspects the transaction to be of money laundering, then the chatbot can trigger a Suspicious Activity Report (SAR) and alert the compliance team.
ChatGPT will make creating chatbots really easy for financial institutions. With its ability to process natural language, ChatGPT can be trained on any kind of data and respond to users' queries just like a human would. This means that financial institutions can use it to create chatbots that interact with customers, answer their queries, and even help them fulfil certain requests.
While these were just some examples of using ChatGPT in finance, the actual use cases are endless. In the coming years, we will see how much financial institutions leverage this technology to make their products and services better and more useful.