5 coolest GPT3 prompts useful to finance and FP&A professionals
If you haven’t heard of Chat GPT-3 and how it will change industries, augment productivity and add value to businesses then read this article first!
In a nutshell, Chat GPT3 or Chat GPT-3 is a powerful artificial intelligence (AI) tool developed by OpenAI. It can be used to automate processes, create Excel macros, answer questions, language translation, financial modelling and even to teach you Python and how to create machine learning algorithms.
In a way it’s similar to a financial forecast, if the inputs are wrong or not clear, the outputs are not going to be valuable. Trash in, trash out.
So the “inputs” or “prompts” you use are very important. You can see 10 coolest GPT3 prompts useful to finance and FP&A professionals below:
1. Create an Excel Macro that uses EBITDA and financial forecasting
This macro changes the value of the cell named Company_EBITDA to 0. Then, uses the Goal Seek feature to set the cell named Financial_Forecast_Input1 to be equal to a value the user enters into a dialog box, by changing the value in the cell named Company_EBITDA. Finally, name the Macro Residual Company_EBITDA.
You can use this macro by going to the Developer tab in Microsoft Excel, clicking on Visual Basic and paste the code there. You can also run it by creating a button and assign this macro to it.
Please note that in order for this macro to work, the cells named “Company_EBITDA” and “Financial_Forecast_Input1” must exist in the workbook and the cells should have the correct name. Also, the workbook should be saved before running the macro.
Also, you may want to add some error handling to the macro in case the user enters an invalid input, or if the cells do not exist in the worksheet.
Prompt and Result:
2. Learn Python Programming and learn how to generate code for creating machine learning algorithms
In Finance and Accounting, everyone is talking about Python, and for good reason. With an exponentially growing community around data science, machine learning, AI, automation and more, Python is a language that opens programming access to the world. Python is meant to be one of the easiest programming languages to learn.
Prompt: Can you show me the python code for creating a linear regression machine learning algorithm?
This code will create a linear regression model using the LinearRegression class from the scikit-learn library. The model is trained on the X_train and y_train data, and then used to make predictions on the X_test data. The coefficients of the model are printed, and the mean squared error of the model’s predictions is also printed.
It’s important to notice that the above code is just a skeleton, you will need to adjust it for your specific use case by providing your own data, also you may want to try different ways of splitting the data, or different evaluation metrics.
Also, please note that linear regression works well when the relationship between the input variables and the target variable is linear, if the relationship is non-linear, linear regression may not be the best approach.
3. Explain how to start using a 3 way financial model in Excel
Prompt: How can I start a 3 way financial model in Excel? What data do I need?
It’s important to note that creating a 3-way financial model in Excel requires a solid understanding of financial concepts and Excel. Also, the accuracy of your model will depend on the quality of the data and assumptions that you use.
It’s also important to keep in mind that this is a high-level overview of how to start a 3-way financial model in Excel, Depending on the complexity of the model and the information you want to include, you may need to consider additional steps.
4. Help you to understand how to create a waterfall chart in Excel or Tableau
Waterfall charts are heavily used in Finance and FP&A. They are very easy to understand but it can be tricky to learn how to create them at first. Luckily, AI can help!
Prompt: How to create a waterfall chart in Excel? OR Explain to me how to create a waterfall chart in Tableau
5. Create SQL code to retrieve EBITDA and NSV data from your data lake
First, a note: Structured Query Language or “SQL” for short is a programming language used to query and manipulate data stored in relational databases. The language is becoming increasingly popular in Finance and Accounting as we find more and more ways to use data.
Prompt: How to use SQL to retrieve data from table EBITDA_Table and join it with NSV_Table by Category?
