Information Package / Course Catalogue
Artificial Intelligence and Public Finance
Course Code: ML473
Course Type: Area Elective
Couse Group: First Cycle (Bachelor's Degree)
Education Language: Turkish
Work Placement: N/A
Theory: 3
Prt.: 0
Credit: 3
Lab: 0
ECTS: 5
Objectives of the Course

This course aims to teach the use of artificial intelligence technologies in public finance, their effects on public financial management, and their transformative potential for the future. It provides students with knowledge of the applications of artificial intelligence, machine learning, and data analytics in tax administration, public expenditures, budgeting, and fiscal auditing processes. Furthermore, the impacts of artificial intelligence on fiscal policies and its ethical, legal, and administrative dimensions are evaluated.

Course Content

The course begins with the fundamental concepts of artificial intelligence and data analytics. The process of digital transformation in public financial management is examined. Applications of artificial intelligence in tax administration, revenue forecasting, budgeting, monitoring public expenditures, and fiscal auditing are evaluated. The role of big data analytics and decision-support systems in public finance is discussed. In addition, the effects of artificial intelligence on the effectiveness of fiscal policies, along with issues of data security, ethics, and law, are examined. National and international case studies are analyzed.

Name of Lecturer(s)
Learning Outcomes
1.Explains the application areas of artificial intelligence technologies in public finance.
2.Analyzes the effects of artificial intelligence on tax administration, budgeting, and fiscal auditing processes.
3.Evaluates big data and data analytics applications from a public finance perspective.
4.Interprets the ethical, legal, and administrative dimensions of artificial intelligence applications.
5.Critically evaluates the effects of artificial intelligence on the effectiveness of fiscal policies.
Recommended or Required Reading
1.Organ, İ. & Bozdoğan, D. Yapay Zekâ ve Kamu Maliyesi. Ekin Yayınevi.
2.Agrawal, A., Gans, J. & Goldfarb, A. Prediction Machines: The Simple Economics of Artificial Intelligence. Harvard Business Review Press.
Weekly Detailed Course Contents
Week 1 - Theoretical
Introduction to Artificial Intelligence and Public Finance
Week 2 - Theoretical
Fundamental Concepts of Artificial Intelligence
Week 3 - Theoretical
Digital Transformation in Public Financial Management
Week 4 - Theoretical
Big Data and Data Analytics
Week 5 - Theoretical
AI Applications in Tax Administration
Week 6 - Theoretical
Revenue Forecasting and Analysis
Week 7 - Intermediate Exam
Midterm Examination / Research Presentations
Week 8 - Theoretical
Monitoring and Evaluation of Public Expenditures
Week 9 - Theoretical
Fiscal Auditing and Artificial Intelligence
Week 10 - Theoretical
Decision Support Systems and Automation
Week 11 - Theoretical
Artificial Intelligence, Ethics, and Data Security
Week 12 - Theoretical
The Future of AI in Fiscal Policy
Week 13 - Theoretical
Academic Paper Discussions and Case Analyses
Week 14 - Theoretical
Academic Paper Discussions and Case Analyses
Assessment Methods and Criteria
Type of AssessmentCountPercent
Presentation1%10
Assignment1%10
Midterm Examination1%20
Final Examination1%60
Workload Calculation
ActivitiesCountPreparationTimeTotal Work Load (hours)
Lecture - Theory144398
Midterm Examination110111
Final Examination110111
TOTAL WORKLOAD (hours)120
Contribution of Learning Outcomes to Programme Outcomes
PÇ-1
PÇ-2
PÇ-3
PÇ-4
PÇ-5
PÇ-6
PÇ-7
PÇ-8
PÇ-9
PÇ-10
OÇ-1
4
5
4
5
4
5
4
5
4
5
OÇ-2
5
4
5
4
5
4
5
4
5
5
OÇ-3
5
5
5
4
4
5
4
5
4
5
OÇ-4
5
4
5
4
5
4
5
4
5
4
OÇ-5
4
5
4
5
4
5
4
5
4
5
Adnan Menderes University - Information Package / Course Catalogue
2026