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2ndSEMESTER 2024-25
Assessment of Part B (Financial Analysis)
BA Accounting – Year 2
Final
· Objective
Students will work in groups (4 students per group) to design and implement AI agent(s) that automatically generate the content ofa company valuation report. The report must include the same sections as theprevious years’ ACC102 assignment:
· Introduction and Company Background
· Industry Analysis and Corporate Strategy Analysis
· Financial Analysis (using financial statements and other public data)
· Financial Modelling and Equity Valuation
Instead of manually writing these sections, students must develop:
· One comprehensive AI agent that can generate all report sections,or
· Multiple specialized AI agents where each agent is responsible for one or more specific parts of the report (e.g., data collection, analysis, or visualization).
Additional submissions must include:
· AI Agent(s) Link: A live link or repository URL where the AI solution can be accessed.
· User Manual (in the format of video demo): A detailed guide explaining how to operate the AI agent(s).
· Product Report for Investors (in the format of ppt): A concise document targeting potential investors that outlines the AI solution’s capabilities (function), the underlying methodology (detailed prompts and plugins), and key financial insights.
The assignments related to the final project are listed as follows. The submission deadline for all the parts is23:59 pm25th May 2025.
· Assignment Requirements
1. AI Agent(s) Development
o Design Options:
§ A single integrated AI agent that automatically produces the entirecompanyvaluation report (including industry and company analysis, financial analysis, and valuation model), or
§ Multiple specialized AI agents where each one generates a specific section of the report (e.g., one agent for data collection, another for analysis, etc.).
o Functional Requirements:
§ Data Collection: Automate retrieval of financial and non-financial data (e.g., from WRDS, Yahoo Finance).
§ Data Processing & Analysis: Process the data and perform financial analysis and modelling.
§ Visualization: Generate charts and graphs as needed.
§ Report Generation: Compile the outputs into the standardvaluation report format.
o Submission:
§ Provide a functional link (or repository URL) to your AI agent(s).
2. User Manual:
o A clear guide detailing how touse the AI agent(s) to generate the results.
o Submission: avideo demo
3. Product Report for Investors:
o A document aimed at potential investors that highlights the AI solution’s benefits (function), its underlying methodology (prompts and plugins), market potential, and thesample valuation report generated by the AI.
o Submission: a ppt
4. Peer Review
o Each student will complete aconfidential peer review to assess individual contributions.
o Impact on Mark: 40% of the final individual mark is determined by the peer review scores. Students who do not review their team members will receive a penalty of 50% of their peer review score.
o The peer review is based on five criteria, as described in Appendix B.
o Example Calculation:
If the group receives an 80%for the group assignments (AI Agent(s), User Manual, and Product Report for Investors)and a student’s peer review score is 85%, then the final individual mark is calculated as:
Part B Final Mark = (80% * 60% + 80% * 40% * 0.85) * 95% + BMC(Pass:5%, Fail:0)
= 71% + 5% if pass BMC or 0% otherwise = 76% if pass BMC or 71% otherwise
Appendix C describes howpeer review scores are derived.
· Assessing assignment
The total mark for Part B is 100%, and Part B contributes 60% to the final module mark. 95% of the individual’s Part B mark is based on the overall group assignment mark, and 40% of thisis adjusted by the peer assessment. 5% of the individual’s Part B mark is based on the BMC certificate.
The groupassessment will be marked as follows: FAIL 0-39
ADEQUATE 40-49
SATISFACTORY 50-59
GOOD 60-69
VERY GOOD 70-79
EXCELLENT TO OUTSTANDING 80+
· Evaluation Criteria
Appendix A is the Assessment form for the groupassessment.
The allocation of marks to the groupassessment is as follows:
|
Criteria |
Marks |
|
AI Agent Design and Functionality |
|
|
§ Effectiveness of automation in generating each section of the report. |
15 |
|
§ Innovation in prompt design and workflow integration. |
15 |
|
Report Quality and Presentation |
|
|
§ Clarity of the AI-generatedresults. |
10 |
|
§ Structure and the professional presentation of the AI-generatedresults. |
10 |
|
Financial Analysis and Interpretation |
|
|
§ Depth of financial analysis,andaccuracy of financial modelling |
10 |
|
User Manual |
|
|
§ Completeness, clarity, and usability of the user manual. |
10 |
|
Investor Report |
|
|
§ Completeness, clarity, and usability of theppt |
30 |
Appendix A
Assessment Form for Group Report (ACC 102)
|
Project Group ID |
|
|
Project Title |
|
|
Criteria |
Max Point |
Mark |
|
AI Agent Design and Functionality |
|
|
|
§ Effectiveness of automation in generating each section of the report. |
15 |
|
|
§ Innovation in prompt design and workflow integration. |
15 |
|
|
Report Quality and Presentation |
|
|
|
§ Clarity of the AI-generated report. |
10 |
|
|
§ Structure and the professional presentation of the AI-generated report. |
10 |
|
|
Financial Analysis and Interpretation |
|
|
|
§ Depth of financial analysis, accuracy of financial modelling, and quality of sensitivity analysis. |
10 |
|
|
User Manual |
|
|
|
§ Completeness, clarity, and usability of the user manual. |
10 |
|
|
Investor Report |
|
|
|
§ Completeness, clarity, and usability of the investment report |
30 |
|
|
|
|
|
|
Total Mark for Group Assessment |
100 |
|
Name and Signature of Examiner (Date)
Appendix B
Peer Review
|
Performance criteria & definitions |
Strongly Disagree |
Disagree |
Neutral |
Agree |
Strongly Agree |
|
Attendance:Group member was present for group conference calls, internet chats, or other scheduled meetings/conversations for working on the project. |
1 |
2 |
3 |
4 |
5 |
|
Punctuality:Group members arrived at scheduled meetings on time; completed tasks on time. |
1 |
2 |
3 |
4 |
5 |
|
Contribution of ideas:Group members proactively suggested new ideas. |
1 |
2 |
3 |
4 |
5 |
|
Quality of Work:Group member’s assigned pieces were complete, thorough, covered the topic well and were accurate in terms of content (e.g., work did not need multiple revisions or rewrites to improve the quality) |
1 |
2 |
3 |
4 |
5 |
|
Interpersonal Relations:Group members positively supported others and contributed to group performance (e.g. helped the group move ahead, constructively resolved conflicts, were not destructive to group functioning, etc.) |
1 |
2 |
3 |
4 |
5 |
Appendix C
Peer Review
|
Group ID: |
Yellow Mountain |
Group mark: |
80% |
|
Student ID: |
George |
Student mark: |
75% |
Receiving
|
|
George |
Michael |
Lucy |
Wen |
Irene |
Total |
|
George |
|
50% |
75% |
60% |
70% |
2.55 |
|
Michael |
30% |
|
60% |
50% |
79% |
2.19 |
|
Lucy |
89% |
45% |
|
35% |
78% |
2.47 |
|
Wen |
30% |
70% |
40% |
|
56% |
1.96 |
|
Irene |
35% |
50% |
35% |
56% |
|
1.76 |
|
Total |
1.84 |
2.15 |
2.1 |
2.01 |
2.83 |
|
Receiving (normalised)
|
|
George |
Michael |
Lucy |
Wen |
Irene |
Total |
|
George |
|
20% |
29% |
24% |
27% |
1 |
|
Michael |
14% |
|
27% |
23% |
36% |
1 |
|
Lucy |
36% |
18% |
|
14% |
32% |
1 |
|
Wen |
15% |
36% |
20% |
|
29% |
1 |
|
Irene |
20% |
28% |
20% |
32% |
|
1 |
|
WebPA score |
0.85 |
1.02 |
0.97 |
0.92 |
1.24 |
|
|
Capped |
0.85 |
1.00 |
0.97 |
0.92 |
1.00 |
|
Individual marks:
|
George |
0.80 × 0.60 + 0.80 × 0.40 × 0.85 |
75% |
|
Michael |
0.80 × 0.60 + 0.80 × 0.40 × 1 |
80% |
|
Lucy |
0.80 × 0.60 + 0.80 × 0.40 × 0.97 |
79% |
|
Wen |
0.80 × 0.60 + 0.80 × 0.40 × 0.92 |
77% |
|
Irene |
0.80 × 0.60 + 0.80 × 0.40 × 1 |
80% |
Notes:
1The normalised marks are capped to ensure that no student can receive a mark higher than the student's group mark.
2Penalty will be imposed when a student does not submit a peer-evaluation form.
3More information aboutPeer Review is available at:
http://webpaproject.lboro.ac.uk/