Course 2022-2023 a.y.

20722 - DATA ANALYTICS FOR FINANCIAL DISCLOSURES

Department of Accounting

Course taught in English
Go to class group/s: 31
CLMG (6 credits - II sem. - OP  |  SECS-P/07) - M (6 credits - II sem. - OP  |  SECS-P/07) - IM (6 credits - II sem. - OP  |  SECS-P/07) - MM (6 credits - II sem. - OP  |  SECS-P/07) - AFC (6 credits - II sem. - OP  |  SECS-P/07) - CLELI (6 credits - II sem. - OP  |  SECS-P/07) - ACME (6 credits - II sem. - OP  |  SECS-P/07) - DES-ESS (6 credits - II sem. - OP  |  SECS-P/07) - EMIT (6 credits - II sem. - OP  |  SECS-P/07) - GIO (6 credits - II sem. - OP  |  SECS-P/07) - DSBA (6 credits - II sem. - OP  |  SECS-P/07) - PPA (6 credits - II sem. - OP  |  SECS-P/07) - FIN (6 credits - II sem. - OP  |  SECS-P/07)
Course Director:
WANLI ZHAO

Classes: 31 (II sem.)
Instructors:
Class 31: WANLI ZHAO


Suggested background knowledge

For a fruitful and effective learning experience, it is recommended some preliminary experience in statistical analysis (such as summary statistics (visual and graphical), regression analysis, ANOVA, etc) as well as applying these analyses via Microsoft Excel. In addition, it is also recommended to have basic knowledge in accounting such as financial statements, auditing report, tax, etc.

Mission & Content Summary

MISSION

Managers need to make investment decisions, manage risks, and ensure compliance with regulatory policies and requirements. In a rapidly changing and competitive global market, accountants play a pivotal role in supporting managerial decision-making. This course introduces the tools and approaches of fulfilling the supportive functions of accountants from a data analytics perspective and a combination of financial and managerial accounting. Specifically, the course facilitates the appreciation of big data view on the complexity of the firm and the understanding of the relationships between the operations and financial statements. The course synthesizes theory and application to prepare students with the approaches of diagnosing problems and issues, analyzing relevant information, making responsible and ethical decisions, and reporting decision results and recommendations, incorporating both the qualitative and quantitative data from the firm, the intermediaries, and the capital market. The course focuses on analytical techniques and provides hands-on experience to develop business analytics skills.

CONTENT SUMMARY

The main topics of the course are as follows:

  • Introduction to the modern accounting environment and data analytics for accounting
  • Understanding and mastering the Data
  • Developing and implementing analysis plan and analyzing the findings
  • Communicating results and recommendations
  • Audit Data Analytics
  • Managerial Analytics
  • Financial Statement Analytics
  • Tax Analytics

Intended Learning Outcomes (ILO)

KNOWLEDGE AND UNDERSTANDING

At the end of the course student will be able to...
  • Recognize when and how data analytics can address business questions
  • Comprehend the process needed to clean and prepare the data before analysis
  • Identify and evaluate the veracity of sources of unstructured and structured data for use in analysis.
  • Recognize what is meant by data quality, be it completeness, reliability, or validity
  • translate a decision problem into a corresponding quantitative model

APPLYING KNOWLEDGE AND UNDERSTANDING

At the end of the course student will be able to...
  • Apply critical analytical thinking to identify and frame business problems for analysis
  • Perform basic analysis to understand the quality of the underlying data and their ability to address the business question
  • Demonstrate ability to sort, rearrange, merge, and reconfigure data in a manner that allows enhanced analysis
  • Identify and implement an approach that will use statistical data analysis to draw conclusions and make recommendations on a timely basis
  • Solve accounting and business related problems using appropriate analytics tools
  • Create visualizations of data to provide clear insights into accounting and other business data, to effectively communicate those insights, and to support recommendations
  • Recommend appropriate actions to address real-world problems in accounting practice
  • Discuss ethical issues as they pertain to the performance and use of data analysis
  • Write effectively to communicate analysis results in the framework of the business problem

Teaching methods

  • Exercises (exercises, database, software etc.)
  • Case studies /Incidents (traditional, online)
  • Individual assignments
  • Group assignments

DETAILS

 Exercises (Exercises, database, software etc.)

 Case studies /Incidents (traditional, online)

 Individual assignments

 Group assignments


Assessment methods

  Continuous assessment Partial exams General exam
  • Written individual exam (traditional/online)
 x    
  • Individual assignment (report, exercise, presentation, project work etc.)
 x    
  • Active class participation (virtual, attendance)
 x    

ATTENDING STUDENTS

With the purpose of measuring the acquisition of the above-mentioned learning outcomes, the students’ assessment is based on four main components:

1. In-class participation (20% of the final grade) aimed to test the students’ ability to interact in a constructive way and to think critically

2. In-class quizzes (20% of final grade) aimed to test the students’ progress in grasping the course materials

3. Written exam (30% of the final grade), consisting of exercises and open questions aimed to assess students’ ability to apply the analytical tools illustrated during the course

4. Group-based project (30%) aimed to gauge the students’ application of analytic tools and skills to a company assigned to each group. The project also needs to be presented to the whole class, testing the students’ ability to argue, explain, articulate, and defend their recommendations based on their analysis


NOT ATTENDING STUDENTS


Teaching materials


ATTENDING AND NOT ATTENDING STUDENTS

Last change 24/01/2023 07:54