Prompts for finance and financial assistants

Prompts for Finance and Financial Assistants

How much has the work of a modern financial professional changed? With the advent of powerful neural networks and large language models, the financial sector is undergoing a true revolution. The ability to correctly formulate queries to artificial intelligence to receive instant and accurate answers is becoming a key skill. Experience shows that the effectiveness of working with AI directly depends on the quality of the prompt.

The purpose of this article is to show you how to use a competent financial prompt to improve the efficiency of your daily work. We will examine specific examples and tasks that your virtual financial assistant can take on. This topic is becoming increasingly relevant, as those who learn to use AI as a tool by creating high-quality queries will gain an undeniable competitive advantage.

Prompts for Calculations

Traditional finance has always required meticulousness and precision in calculations. From capital project evaluations to cash flow forecasting, mistakes are costly. A modern, clearly and structured prompt can instantly perform complex calculations that previously required cumbersome spreadsheets.

For example, instead of manually constructing a multi-stage discounted cash flow (DCF) model, you can provide the neural network with all the input data and receive a ready-made calculation. To achieve this, it’s crucial to include not only the numbers in your prompt but also the required methodology and output format. Experienced professionals note that this approach frees up time for more strategic tasks.

A clear prompt should include all variables, such as the required rate of return and calculation period. The model will automatically check for internal consistency if you request it in the query. For example, you can ask the assistant to check the sensitivity of the NPV to changes in the discount rate. Thus, artificial intelligence acts not just as a calculator, but as a powerful verifier of your preliminary calculations and risk analysis.

Prompts for Analysis

Qualitative analysis is the heart of financial decision-making. With the right prompt, you can turn ChatGPT or another large language model into your own high-speed analyst. It can quickly process massive amounts of data and highlight key trends. This is especially valuable when working with unstructured information, such as news reports or competitors’ annual reports.

For example, you might ask your assistant to perform a scenario analysis or compare the financial performance of five key competitors in your industry. The prompt here should be as detailed as possible to obtain the precise insights you need, avoiding generalities. Using artificial intelligence for this purpose not only helps collect data but also uncover hidden relationships, risks, and potential opportunities.

The analysis prompt can cover various aspects, helping you with market research:

• comparative analysis of company liquidity and solvency over the past three years;
• forecasting the impact of key rate changes on the cost of borrowed capital;
• scenario modeling of return on investment (ROI) under varying levels of demand;
• Structural analysis of operating expenses, highlighting the fastest-growing items.

If you want to properly and deeply immerse yourself in the world of financial prompting, you should consider specialized training programs. chataibot.pro offers courses that will help you master the creation of complex prompts and learn to leverage the potential of neural networks for deep big data analysis in your work. Their programs are developed by experienced practitioners and focused on real-world business problems, helping you move from theory to value creation.

Prompts for automation

Routine work is the bane of any finance department. Creating standard reports, preparing pivot tables, monitoring specific metrics—these tasks take time, but not creativity. This is where prompts demonstrate their greatest effectiveness, helping automate processes and free up employees for more important, strategic tasks.

You can create tasks so that the model regularly creates standardized reports or even generates templated emails to counterparties based on specified conditions. This approach significantly reduces the likelihood of human error, which is especially high in monotonous operations, and speeds up business processes. Your AI-powered assistant can become a fully-fledged tool for optimizing departmental work.

Automation using a well-designed neural network guide involves several steps:

1. Create a detailed prompt template for the monthly cash flow statement.

2. Integrate the prompt with source data to obtain up-to-date information.

3. Define output parameters so the report is always generated in a user-friendly format.

4. Set up automatic updating and sending of this report to stakeholders, which is an example of the effective use of prompts in finance.

Prompt Setting Tips

For your AI to truly become a financial assistant and work for you, you need to learn how to formulate prompts as precisely and contextually as possible. The better you formulate the query and describe the task, the higher the quality of the result you will obtain. It is generally accepted in the industry that the precise definition of the task determines a significant part of the success of the entire analysis.

Your prompt should be structured and contain not only the task itself but also the necessary context, information about the target audience, and the desired response format. Ignoring these elements often leads to irrelevant analysis or inaccurate calculations. We will look at how to formulate a prompt correctly, following engineering principles.

Here are a few key principles for creating a strong prompt for finance:

1. Define the role and context. Always begin the problem statement by specifying who the model should be (e.g., “You are a senior financial analyst”). This helps the neural network activate the appropriate vocabulary and level of expertise.

2. Set constraints and input data. Clearly specify the data to use and the methodologies to apply, and provide initial examples.

3. Specify the desired output format. Ask the model to generate a response in the form of a bulleted list, a pivot table, or a short executive summary.

4. Break a complex problem into subproblems. Instead of a single long query requiring complex analysis, it’s better to create a sequence of prompts, each of which solves a separate logical part of the problem.

5. Apply the “chain of thoughts” principle. Ask the model to write out the steps of its logical reasoning before providing a final answer: “Before giving your answer, show me the step-by-step logic of the calculation so I can verify it.”

How to Use

Using prompts in your daily financial work is a new philosophy for interacting with technology. Prompts become a bridge between your expertise and the computing power of artificial intelligence. They allow you to scale your knowledge and reduce execution time from hours to minutes.

A well-formulated prompt allows you to create complex financial models, conduct in-depth market analysis, and even assist in training new employees. It’s important to view an AI-powered chatbot not as a replacement, but as a universal assistant that takes on routine, time-consuming requests and fulfills them as quickly as possible.

If you’re ready to integrate these advanced tools into your work and turn artificial intelligence into an indispensable assistant, we recommend exploring the educational products on our website. The courses offer a systematic approach to mastering prompt engineering, helping you move from theoretical understanding to practical application of the model to solve real-world financial problems.

Partner Content

For those who want to go beyond just using individual prompts and implement artificial intelligence as a comprehensive automation tool, chataibot.pro offers advanced courses on prompt engineering. They provide detailed practical examples of creating end-to-end automated processes. This is an ideal opportunity for financial managers to take their work to a whole new level by creating effective prompt chains for neural networks.

Conclusion

Mastering prompt engineering skills is a critical step for any financial professional. We’ve covered in detail how prompts can automate calculations, deepen data analysis, and create efficient workflows. Neural networks are ready to become your most powerful tool. All that’s left is to learn how to correctly and clearly ask them questions. Start using this knowledge today to ensure your financial assistant is operating at its full potential.