The landscape of financial analysis is undergoing a transformative shift, driven by the rapid advancements in Artificial Intelligence. Among the leading contenders in this AI revolution stands Google Gemini, a ground breaking language model that surpasses many of its predecessors in terms of its ability to comprehend, reason, and generate human-like text. Unlike conventional AI models that may struggle with nuanced financial concepts, Gemini excels in understanding complex financial statements, interpreting market trends, and even predicting future market movements with remarkable accuracy. This sophisticated understanding allows Gemini to go beyond simple data crunching and delve into the intricate web of financial relationships, uncovering hidden patterns and insights that may be overlooked by human analysts. Gemini’s capacity to analyse vast amounts of information from diverse sources, such as financial news, social media, and regulatory filings, provides a holistic perspective on market dynamics. This comprehensive financial analysis with Google Gemini blog empowers financial professionals with a deeper understanding of the different kinds of analysis that can happen quickly and accurately at the same time.
GOOGLE GEMINI IN FINANCE: A VALUABLE ALLY, BUT USE WISELY
While Google Gemini offers a formidable arsenal of AI-powered tools for financial analysis, it’s crucial to remember that it is not a magic bullet. Human expertise remains indispensable throughout the analytical process. Analysts must meticulously review and interpret Gemini’s outputs, ensuring that the AI-generated insights align seamlessly with their own in-depth knowledge of the market, industry trends, and company-specific nuances. Gemini should be viewed as a powerful ally, augmenting human capabilities and enhancing the analytical process, rather than replacing the critical role of human judgment and decision-making.
TIPS FOR EFFECTIVE PROMPTS IN FINANCIAL ANALYSIS WITH GOOGLE GEMINI
- Be Specific: Clearly define objectives, scope, and timeframe. Use precise language.
- Provide Context: Include relevant data, industry trends, and macroeconomic factors.
- Structure Well: Use bullet points, headings, and proper formatting for clarity.
- Iterate: Experiment with prompts, analyse outputs, and refine based on results.
- Leverage Strengths: Utilize Gemini’s data analysis, predictive modelling, and natural language processing capabilities.
HOW GOOGLE GEMINI CAN ASSIST IN FINANCIAL ANALYSIS?
Let’s see how Google Gemini can be used in Financial Analysis.
1. Explaining Financial Concepts: Google Gemini can break down complex financial concepts into simpler terms, using analogies, metaphors, and real-world examples to make them easier to understand. It can also personalize explanations based on individual learning styles.
Example: Suppose we read somewhere that the ROE for a company is 20%. Google Gemini explains the term ROE in very simple language and explains it in layman’s terms as follows.
Google Gemini has provided an excellent explanation of ROE in straightforward terms, along with references to additional study materials for a deeper understanding. If you’re looking for the precise formula, you can further ask the following question.
To gain a deeper understanding of any financial concept, we can refine our questions as we learn. If an initial answer isn’t completely accurate, we can adjust our inquiries to focus on specific parts or rephrase the question to get a clearer explanation.
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2. Extracting and Interpreting Financial Statements: Google Gemini can significantly aid in interpreting financial statements by automating data extraction, identifying key trends, and generating concise summaries. Its advanced language and reasoning capabilities allow it to analyse complex information, identify potential risks, and even assist in financial forecasting. This can free up human analysts to focus on higher-level tasks and gain deeper insights into the financial health of a company.
Example: Suppose we want to extract the Income Statement figures for Apple Inc. for the financial years 2021, 2022 and 2023 and we want the Google Gemini to interpret the financial performance of Apple Inc. We can give the following prompt.
As requested above Google Gemini has extracted the Income Statement of Apple Inc. in tabular form. On cross-checking the numbers from the annual report of Apple Inc. we find that it has not extracted all the line items from the Income Statement, like the Other income/(expense), net, and Provision for Income taxes. However, it can accurately extract the key figures of revenue, cost of revenue, operating income, and net income for Apple Inc. Hence, Google Gemini can be used to extract key items of the Income Statement and give an interpretation based on the same. The interpretation provided by Google Gemini is based on general knowledge. One should refer to the annual reports or other reliable sources to know the exact reason for the revenue or profitability change.
Now let’s see an example, where we will try to extract exact product revenue details for Apple Inc. Suppose, an analyst wants to know the revenue for iPhone for the last 5 years as reported in its form 10K.
Above we can also notice that Google Gemini can give us exact numbers from the Form 10K of the company.
Note: Whenever we give Google Gemini a prompt requesting company-related data and its interpretation it gives us a short disclaimer regarding the reliability of the data. One should read that before completely relying on the AI-generated interpretation.
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3. Analysing Key Ratios: Google Gemini can accurately calculate ratios, compare performance to industry benchmarks, predict future trends, and even help identify potential risks. This allows financial analysts to focus on higher-level tasks and gain deeper insights into a company’s financial health.
Example: We want Google Gemini to give us a table with the Revenue, Revenue growth, Operating Margin, ROE, and TSR for Apple, Alphabet, and Microsoft from the year 2019 to 2023.
We can see above that Google Gemini has returned a well-structured table with all the ratios requested above. However, the user needs to once cross check the ratios and figures as the AI tool is still under development.
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4. Performing Trend analysis: Google Gemini simplifies trend analysis by aggregating data from various sources, detecting patterns, and applying predictive analytics to forecast future trends. It uses machine learning and natural language processing (NLP) to analyse historical data, identify anomalies, and extract insights from text, such as customer feedback or market news. With intuitive dashboards and automated updates, Gemini provides real-time trend tracking, helping businesses anticipate changes and make informed decisions.
Example: Based on the Income Statement of Apple Inc. we want to perform trend analysis of Revenue, Net Income, Operating Income and cost as a % of sales.
We can see how well Google Gemini has performed Trend Analysis for all the metrics. However, it is still under development to show the trend on a line chart.
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5. Comparing Companies: Google Gemini helps compare companies by analyzing financial metrics, ratios, and performance trends. It provides clear insights into key indicators like revenue growth, profitability, and valuation, offering side-by-side comparisons. By simplifying complex data and integrating with tools like Google Sheets, it enables detailed benchmarking, helping users identify strengths, weaknesses, and market positions of companies efficiently.
Example: We want to compare the current price ratios of Apple, Alphabet, and Microsoft.
Above we can see that Google Gemini has returned us the most recent price multiples of the companies requested above.
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6. Analysing and interpreting any Image: Google Gemini aids in analysing and interpreting images through advanced capabilities like object detection, image captioning, and PDF transcription. It can identify objects, generate detailed descriptions, and extract insights from complex visuals. These features enable applications in accessibility, automation, and data extraction, making image analysis more efficient and accurate.
Example: We have an image related to Alphabet Inc. Segment reporting and we want Google Gemini to analyse the image and give interpretation on the same. For this, we can give the following prompt to Google Gemini.
We can see that how well Google Gemini provides analysis on the image uploaded. However, as mentioned in its disclosure the interpretation is solely based on the image uploaded. One should read other sources for the full and correct interpretation.
Example: We have the following chart image representing different geographical segments of Adidas for 3 different category of products. We want Google Gemini to read and interpret the chart.
The prompt given to analyse the same is below.
Above we can see that the interpretation given on the basis of the image is 90% correct. For the Apparel section it gives slightly wrong interpretation. Since this AI platform is still undergoing development there are chances of it returning incorrect results. Hence, the user should always cross check the details. If the output is not as desired, the user can reframe the question till it gets the desired output.
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7. Risk Assessment: Google Gemini assists in risk assessment by analysing large datasets, identifying patterns, and providing insights into potential risks. It evaluates financial metrics, market trends, and operational data to detect anomalies or vulnerabilities. Additionally, Gemini can interpret risk factors from financial reports, compare industry benchmarks, and generate predictive models, enabling organizations to make informed decisions and mitigate risks effectively.
Example: An investor considering an investment in Netflix Inc. seeks to evaluate the associated risks. Here’s how Google Gemini can assist with the assessment.
Google Gemini has outlined all potential risks faced by Alphabet Inc., helping investors make well-informed decisions.
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8. Interactive Data Analysis: Google Gemini facilitates interactive data analysis by enabling users to explore datasets dynamically through natural language queries. It processes complex data, identifies patterns, and generates visualizations like tables for better understanding. By integrating with tools like Google Sheets, it allows for real-time data manipulation, making analysis more intuitive and accessible for decision-making.
Example: We have the sales data of a company for the Month of Dec. We want to analyze the person who has sold the maximum number of products. We will give the following prompt.
| Sales Person | Product Sold | Amount |
| Andrew | Television | 90,000 |
| Andrew | Refrigerator | 82,600 |
| Andrew | Oven | 12,980 |
| Andrew | Air Conditioner | 1,30,000 |
| Andrew | Toaster | 3,540 |
| Andrew | Mobile Phone | 59,000 |
| Andrew | Laptop | 1,05,020 |
| Andrew | Vacuum cleaner | 5,900 |
| Sam | Oven | 15,340 |
| Sam | Air Conditioner | 2,95,000 |
| Sam | Toaster | 2,950 |
| Sam | Laptop | 1,06,200 |
| Sam | Vacuum cleaner | 8,260 |
| Sam | Refrigerator | 76,700 |
| Linda | Toaster | 3,540 |
| Linda | Laptop | 88,500 |
| Linda | Oven | 4,130 |
| Linda | Air Conditioner | 1,77,000 |
| Linda | Heater | 4,720 |
| Linda | Tape recorder | 2,360 |
| William | Heater | 7,670 |
| William | Tape recorder | 2,950 |
| William | Oven | 15,340 |
| William | Television | 1,29,800 |
Further, we want to analyse which sale person has earned the company maximum sales amount.
We want to know the product name which is sold maximum number of times.
This way we can ask numerous questions to Google Gemini. Google Gemini is an excellent interactive platform. However, it may sometimes return false values since the AI chat box is still under development.
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9. Assisting in Forecasting: Google Gemini simplifies forecasting by automating data analysis, optimizing models, and enhancing collaboration. Its integration with tools like Vertex AI improves accuracy and efficiency, enabling precise, data-driven decision-making.
Example: Suppose we want consensus revenue for Alphabet Inc., Microsoft Inc. and Meta for the next 3 years, we will give Google Gemini the following prompt.
This feature in Google Gemini helps us to get the consensus forecasted revenue at a click of a prompt.
Example: We want to get the most recent analyst quotes with analyst name for Microsoft Inc. Hence, we give the following prompt.
Example: We want recent consensus rating and target share price for Microsoft Inc. Hence, we give the following prompt.
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10. Automating Financial Report Summaries: Google Gemini streamlines financial report summaries by leveraging advanced AI to extract key insights, identify trends, and generate concise, accurate summaries. It automates data analysis, highlights critical financial metrics, and simplifies complex information, enabling faster and more efficient decision-making. This reduces manual effort, ensures precision, and allows stakeholders to focus on strategic insights.
Example: We want a summary report on the financial performance of the company to be submitted to the CFO of the company. Hence, we can give the following prompt.
We can see that Google Gemini has very welldrafted a summary report with emphasis on Revenue performance, Net profit, and Operating profit. However, it has not calculated the ratios in the prompt as requested. We can give additional prompts to get the desired output.
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11. Assessing Market Conditions: Google Gemini helps assess market conditions by analysing vast datasets, identifying trends, and providing real-time insights using advanced machine learning. It processes economic indicators, consumer behaviour, and industry data to uncover patterns and predict market shifts. By automating analysis and offering clear visualizations, Gemini enables businesses to make data-driven decisions and adapt swiftly to changing market dynamics.
Example: As investors aiming to invest in the U.S. market, we seek to analyse the current macroeconomic conditions in the United States.
From above we can see that the report which Google Gemini gives us on macroeconomic conditions is very generalized. For more specific data one can give additional prompts.
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12. Assessing Industry Details: Google Gemini aids in assessing industry trends by analysing large volumes of data to identify emerging patterns and key drivers within specific industries. Using advanced machine learning and natural language processing, it highlights shifts in consumer behaviour, competitive dynamics, and market opportunities. By providing actionable insights and predictive analytics, Gemini enables businesses to stay ahead of industry changes and make informed strategic decisions.
Example: We want to write a report on Industry analysis for Alphabet Inc.
Google Gemini above has given a full-fledged description of its different segments and competitors in each of the segments. The report can be very useful for anyone who wants to understand the industry as a whole.
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13. Assist in using Excel for Financial Analysis: Google Gemini enhances financial analysis in Excel by automating data preparation, formula generation, and advanced calculations. It simplifies tasks such as creating financial models, analysing trends, and visualizing data through intelligent recommendations and real-time insights. Gemini’s AI capabilities help users optimize workflows, identify errors, and ensure accuracy, making financial analysis in Excel faster and more efficient.
Example: We want to understand the concept of NPV (Net Present Value) to calculate our company’s future cash flows using Excel. Google Gemini can help us with the formula of NPV using a hypothetical example.
From above we can see how Google Gemini can help us carry out any financial calculation in excel with step by step guide and formulas. However, in the above case the final result of NPV in the hypothetical example is wrong. Hence, we are giving an additional prompt to Google Gemini to cross check its results.
In the second prompt above, Google Gemini is giving correct results. Hence, the most important thing to note while using Google Gemini is to cross check the financial calculations before relying on the results.
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14. Assist in performing calculations using image upload: Google Gemini can assist with calculations using image uploads by leveraging its advanced optical character recognition (OCR) capabilities. It extracts data from images, such as handwritten notes, receipts, or printed tables, and converts them into editable, structured formats like Excel or Google Sheets. Once the data is extracted, Gemini applies machine learning to identify patterns, perform calculations, and generate insights, streamlining workflows and reducing manual effort.
Example: Using the table image below, we aim to calculate the total, average, minimum, and maximum sales values.
| Region | Units | Amount |
| North America | 100 | 5000 |
| India | 150 | 7500 |
| Africa | 50 | 2500 |
| Japan | 60 | 3000 |
| England | 70 | 3500 |
| China | 90 | 4500 |
| Germany | 60 | 3000 |
As shown above, Google Gemini has provided the total, average, minimum, and maximum sales amounts. However, these calculations may not always be accurate and should be verified by the user for correctness.
Example: To calculate NPV from the below data given the discount rate is 10%, we will give Google Gemini the following prompt.
| Years | Amount |
| 1 | 5000 |
| 2 | 7500 |
| 3 | 2500 |
| 4 | 3000 |
| 5 | 3500 |
| 6 | 4500 |
| 7 | 3000 |
Hence, we can see that Google Gemini apart from simple addition function can also perform complex calculations like NPV.
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15. Assist in reading and summarising videos: Google Gemini assists in reading and summarizing videos by leveraging advanced AI capabilities to analyse video content, including spoken words, visuals, and text. It uses speech recognition to transcribe audio, extracts key themes and insights, and generates concise summaries. This enables users to quickly understand the main points of lengthy videos, saving time and enhancing productivity.
Example: We want to hear a video on 5 reasons to Love Alphabet Stock. But since we are short of time, we want a summary of the video. We just have to put the URL of the video on Google Gemini chat box and ask it to write a summary of the video.
This feature of Google Gemini helps us save a lot of time and effort.
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LIMITATIONS OF GOOGLE GEMINI
While Google Gemini offers powerful tools for financial analysis, it does have some limitations, including:
- Might not understand generic prompts: Google Gemini may not always understand the prompt and may give false or generic results. Hence, the user should always reiterate the prompt or google search on how to give effective prompt to get the quality answer. Enhancing the prompt quality can get to the right answer in most situations.
- Data Accuracy Dependence: Results depend heavily on the quality and accuracy of the input data. Poor or incomplete data may lead to incorrect analyses. Always ask to double check calculations in particular.
- Limited Context Understanding: Gemini may struggle with nuanced financial contexts, such as regulatory changes or industry-specific accounting practices.
- Customization Challenges: Highly specialized or complex financial models may require manual adjustments, as Gemini may not fully automate intricate scenarios.
- Learning Curve: Users unfamiliar with AI tools might find it challenging to use Gemini effectively without proper training.
- Real-Time Data Limitations: Gemini may not always integrate with live financial data sources, potentially leading to outdated insights.
- Interpretation Risks: Automated insights may lack detailed explanations, requiring users to validate and interpret results carefully.
- Security Concerns: Handling sensitive financial data with AI tools raises potential risks around data privacy and compliance.
- Dependency on Internet Access: The tool’s functionality relies on connectivity, which might be a barrier in certain environments.
These limitations highlight the need for careful oversight and supplementary analysis when using Google Gemini for financial tasks.
CONCLUSION
Google Gemini is revolutionizing financial analysis by automating processes, improving accuracy, and delivering actionable insights. By enabling businesses to focus on strategy rather than manual data handling, it is becoming an indispensable tool for financial professionals. While it’s not without limitations, its advantages far outweigh the challenges, making it a powerful ally in navigating today’s complex financial landscape.
