Information Package / Course Catalogue
Finance and Artificial Intelligence Applications
Course Code: MLY300
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

The aim of this course is to teach students how artificial intelligence technologies are applied in the field of finance. Students will learn how artificial intelligence and machine learning techniques can be integrated into public finance, tax management, financial auditing, and budgeting processes. Additionally, students will analyze potential applications of AI for financial decision-making and financial forecasting. The course aims to equip students with the skills to enhance efficiency and develop decision support systems using AI-based solutions.

Course Content

This course explores the integration of artificial intelligence (AI) technologies in the field of finance. Students will learn how AI and machine learning techniques can be applied in public finance, tax management, financial auditing, and budgeting processes. The course focuses on practical applications of AI to improve financial decision-making, automate financial tasks, and predict financial trends. Additionally, students will gain insights into how AI-based solutions can enhance financial efficiency and support the development of advanced decision-making systems. The course provides both theoretical foundations and practical tools for applying AI in finance.

Name of Lecturer(s)
Assoc. Prof. Sercan YAVAN
Learning Outcomes
1.The student will be able to explain the basic concepts and application areas of artificial intelligence in finance.
2.The student will be able to use artificial intelligence and machine learning techniques for analyzing financial data.
3.The student will be able to discuss the applications of artificial intelligence in public finance, tax management, and budgeting processes.
4.The student will understand how ethical and security issues are addressed in financial applications of artificial intelligence.
5.The student will be able to perform financial analyses and forecasting using AI-based decision support systems.
Recommended or Required Reading
1.Kaya, M. (2020). Artificial Intelligence and Financial Applications. Nobel Publishing.
2.Dunis, C. L., Middleton, P. W., & Karathanasopolous, A. (2021). Artificial Intelligence in Finance: Concepts and Applications. Elsevier.
Weekly Detailed Course Contents
Week 1 - Theoretical
Introduction and Basics of Artificial Intelligence; Definition of artificial intelligence, historical development, and its role in financial applications.
Week 2 - Theoretical
Artificial Intelligence and Machine Learning: Basic Concepts; Machine learning, deep learning, supervised and unsupervised learning methods.
Week 3 - Theoretical
Financial Data Analysis and Artificial Intelligence; Analyzing financial data using AI, modeling techniques.
Week 4 - Theoretical
Artificial Intelligence and Tax Management; Use of AI in tax declarations, payment tracking, and tax auditing.
Week 5 - Theoretical
AI in Budgeting and Planning; Use of AI-supported tools in budgeting processes, forecasting, and analysis.
Week 6 - Theoretical
Financial Forecasting and AI; Use of AI in generating financial forecasts, algorithms for prediction.
Week 7 - Theoretical
AI Applications in Public Finance; Integration of AI in public budgeting, spending, and borrowing processes.
Week 8 - Theoretical
Artificial Intelligence and Portfolio Management; AI applications in investment strategies, risk management, and portfolio analysis.
Week 9 - Theoretical
Artificial Intelligence and Financial Auditing; Use of AI and data analysis in financial reporting and auditing processes.
Week 10 - Theoretical
Ethics and Artificial Intelligence; Ethical issues of AI in finance, data security, and privacy concerns.
Week 11 - Theoretical
AI-Based Decision Support Systems; Use of AI-based decision support systems for investment, tax, and budgetary decisions.
Week 12 - Theoretical
Artificial Intelligence and Financial Markets; Impact of AI on financial markets, algorithmic trading, and market analysis.
Week 13 - Theoretical
AI and Economic Policy; Use of AI in creating economic policies, data-driven policy development.
Week 14 - Theoretical
General Review and Case Studies; Overall course review, student projects, and applied case studies.
Assessment Methods and Criteria
Type of AssessmentCountPercent
Midterm Examination1%40
Final Examination1%60
Workload Calculation
ActivitiesCountPreparationTimeTotal Work Load (hours)
Lecture - Theory143384
Midterm Examination112113
Final Examination124125
TOTAL WORKLOAD (hours)122
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
3
2
2
3
3
3
2
3
4
3
OÇ-2
2
4
3
2
3
2
3
3
4
3
OÇ-3
3
3
4
3
4
3
3
3
4
4
OÇ-4
2
3
2
4
2
3
2
3
3
2
OÇ-5
4
4
4
4
3
4
5
4
3
3
Adnan Menderes University - Information Package / Course Catalogue
2026