AI in Assessment Example: Level 4

Financial Analysis (Finance, 400-level)

At this level of the five-level AI Assessment Scale (Perkins, et al., 2024) students can use AI to complete any elements of the tasks, with students directing AI to achieve the assessment goals. Assessments at this level may also require engagement with AI to achieve goals and solve problems.

Course: FIN 400 – Advanced Financial Analysis

Assignment Title: Performing a Financial Analysis of a Company Using AI Tools

Due Date: [Insert Due Date]

Assignment Overview:
In this assignment, you will perform a comprehensive financial analysis of a selected company, utilizing AI tools to assist with data processing, report generation, and financial insights. The goal is to leverage AI to enhance the efficiency and accuracy of your analysis, allowing you to focus on strategic decision-making and drawing well-supported conclusions. You will direct the AI’s analysis, ensuring that the outputs are accurate, relevant, and aligned with your financial objectives.

Objectives:

To conduct a detailed financial analysis of a company using AI tools to process data and generate reports.
To critically engage with AI-generated insights, ensuring their accuracy and relevance for strategic decision-making.
To reflect on the role of AI in enhancing the financial analysis process, including how you directed and managed the AI tools.

Instructions:

Company Selection and Initial Data Gathering:
- Select a publicly traded company to analyze. Consider factors such as industry relevance, financial health, and availability of comprehensive financial data.
- Gather relevant financial data, including income statements, balance sheets, cash flow statements, and market data. This data will serve as the foundation for your AI-assisted analysis.
AI-Assisted Data Processing and Reporting:
- Use AI tools to process the financial data and generate initial reports. AI can assist in calculating key financial ratios, performing trend analysis, and generating visual representations of the data (e.g., graphs, charts).
- Direct the AI to focus on specific areas of interest, such as profitability, liquidity, solvency, or market valuation. Ensure that the AI-generated reports align with your analytical goals and provide a comprehensive overview of the company’s financial performance.
Strategic Analysis and Conclusion Drawing:
- Critically evaluate the AI-generated reports and use them as a foundation for your strategic financial analysis. Draw conclusions about the company’s financial health, performance trends, and future prospects.
- Consider how AI-generated insights can inform strategic decision-making, such as investment recommendations, risk assessment, or financial forecasting. Ensure that your conclusions are well-supported by both AI-generated data and your own analysis.
Reflection and Documentation:
- Submit the AI-generated reports alongside your final financial analysis. Document your process by explaining how you directed the AI tools, the specific tasks AI assisted with, and how you ensured the accuracy and relevance of the AI outputs.
- Write a reflection (3-4 pages) on how AI influenced your financial analysis. Discuss the benefits and challenges of using AI in financial analysis, including how you balanced AI-driven insights with your own financial expertise.
Final Submission:
- Submit your final financial analysis report (15-20 pages), including all key components such as company overview, financial analysis, strategic recommendations, and supporting evidence.
- Include the AI-generated reports and your reflection as appendices to your report. Ensure that the entire submission is well-organized, clearly written, and professionally presented.

Evaluation Criteria:

– Depth and Accuracy of Financial Analysis (35%): Demonstrating a thorough understanding of the company’s financial performance, with accurate calculations and well-supported conclusions.

– Effective Use of AI Tools (25%): Effectively using AI to process data, generate reports, and provide financial insights. The documentation should show thoughtful engagement with AI tools and a critical assessment of their contributions.

– Strategic Insight and Decision-Making (25%): Providing clear and well-reasoned strategic recommendations based on the financial analysis. The analysis should demonstrate strong financial judgment and the ability to use AI insights effectively.

– Reflection on AI Use (10%): Providing insightful and critical reflections on the role of AI in the financial analysis process, including an analysis of the benefits and challenges encountered.

– Writing and Presentation Quality (5%): Producing a professionally written and well-presented report, with attention to clarity, formatting, and adherence to academic standards.

Support Resources:

– AI Tools and Software: Access to AI tools such as [specify tools, e.g., Bloomberg Terminal, IBM Watson, AlphaSense] will be provided through the university’s finance lab. Training sessions on using these tools for financial data analysis and report generation will be available during the first two weeks of the assignment period.

– Workshops and Tutorials: Participate in workshops focused on AI in financial analysis, covering topics such as data processing, trend analysis, and integrating AI insights into strategic decision-making.

– Office Hours: Schedule office hours with your instructor to discuss your financial analysis approach, AI tool use, and strategies for integrating AI insights into your report.

– Library Resources: The university library offers access to financial databases and journals, including case studies on AI applications in finance. Librarians can assist you in finding relevant research and data sources.

– Peer Collaboration: Engage in peer review sessions where you can present your AI-generated reports and receive feedback on how to refine and enhance your financial analysis.

Academic Integrity:
Your final financial analysis report must reflect your original work, with AI tools used to support your analysis and decision-making process. Misuse of AI to generate unoriginal content or failure to critically engage with AI-generated outputs will be considered a violation of academic integrity. All AI tools and methods used must be properly documented and critically assessed in your reflection.

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