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Graduate School of Business Department of Accounting & Finance
Home/The Program
About the MSc

Accounting, auditing, and finance
for a data-driven profession.

The MSc in Data-Driven Financial Reporting, Auditing and Financial Management integrates professional accounting and finance education with analytics, computing, and artificial intelligence. It is designed for a workplace in which financial expertise increasingly depends on technical fluency with data.

A programme built to connect accounting, auditing, and financial management with analytics, computation, and practical professional relevance.
Programme Aims

Why this MSc exists now.

The Study Guide describes the programme as a state-of-the-art MSc that incorporates the latest developments in Artificial Intelligence and Machine Learning into the traditional domains of accounting, auditing, and financial management. The objective is not novelty for its own sake, but relevance to a profession that is becoming more data-intensive every year.

The programme aims to educate future professionals with advanced, up-to-date knowledge in accounting, auditing, and financial management, while equipping them with analytical and computational skills that enhance employability. It is intentionally positioned at the intersection of professional accreditation, academic rigour, and real-world applicability.

“What distinguishes this programme is that it embeds data analytics and computing throughout the learning experience, making graduates competitive and technically adept in an increasingly data-driven professional environment.”
Learning Outcomes

What graduates of the MSc are expected to demonstrate.

The Study Guide defines programme outcomes across five domains: knowledge, analytical reasoning, practical implementation, research design, and professional judgment.

A

Knowledge and understanding

Graduates systematically understand advanced accounting, auditing, and financial management theory, and can critically evaluate the role of digital technologies and AI in transforming professional practice.

B

Cognitive and analytical skills

They formulate data-driven solutions, interpret high-dimensional financial datasets, and compare alternative analytical models for predictive accuracy and suitability.

C

Practical and technical skills

They can design and implement analytical solutions, work with programming tools, and produce professional financial analyses and reports tailored to stakeholder needs.

D

Research competence

They are able to design and execute independent data-intensive research, applying econometric, statistical, and machine-learning methodologies with rigour and reproducibility.

E

Transferable and professional skills

They communicate complex findings clearly, work with autonomy and initiative, and apply ethical principles in accounting, auditing, data governance, and confidentiality.

Who should apply

Three profiles the programme is built to serve well.

The Study Guide explicitly positions the MSc for students with different academic and professional starting points, provided they are ready for serious quantitative and professional work.

The graduate from a diverse background

The programme welcomes university degree holders from different academic disciplines, not only accounting and finance. A preparatory course helps align everyone before the first semester begins.

The working professional updating for the AI era

Professionals in accounting, auditing, and financial management can use the MSc to refresh their practice for a workplace shaped by analytics, automation, and machine learning.

The research-minded applicant

The programme also prepares students for dissertation work, doctoral progression, and analytical roles in organisations that value evidence-based financial reasoning.

Programme At A Glance

How the MSc is actually delivered.

The programme structure in the Study Guide is specific: 90 ECTS, two taught semesters, a dissertation semester, English-language teaching, hybrid delivery, and a preparatory phase before classes begin.

ECTS
90
The degree is awarded after successful completion of 90 ECTS across two taught semesters and a dissertation semester.
Teaching structure
13 weeks
Each taught semester runs on a 13-week basis with timetabled sessions and monitored attendance.
Delivery mode
Hybrid
Live sessions take place on campus in Thessaloniki while also being live-streamed to support flexible participation.
Language
English
Teaching and assessment are conducted in English throughout the programme.
Study mode
Full-time
The default mode is full-time, though part-time study may be available following a formal request to the Secretariat.
Before term starts
Prep course
Students complete an intensive asynchronous preparatory training in mathematics, accounting, economics, finance, and programming.
Professional Recognition

Designed to align with real accreditation routes.

The Department highlights six professional bodies whose certifications and exemptions support graduates seeking recognition in accounting, auditing, management accounting, and internal control.

ACCAProfessional exemptions
ICAEWACA pathway
IESOELGreek CPA-auditor route
CIMACGMA recognition
IICInternal controls
IIAInternal auditing
The Student Journey

From preparation to dissertation, in five stages.

Before start

Preparatory training

Before teaching begins, students complete asynchronous preparatory units in mathematics and statistics, accounting, economics and finance, and programming.

Semester I

Foundations and common language

The first semester builds shared ground in computing for data science, financial reporting, data analytics, financial management, and one elective.

Semester II

Professional specialisation

Students move into taxation, auditing and internal control, management accounting, financial analysis, and a second elective module.

Throughout

Attendance and engagement

Attendance is monitored closely. Three unexcused absences in a module may trigger formal action, including the need to repeat the module.

Semester III

Dissertation and supervision

The final semester is devoted to the dissertation, carried out under academic supervision through topic selection, research design, data analysis, writing, and final submission.

Next Steps

Ready to move from overview to the actual structure?

Browse the curriculum, open the full module specifications, and begin the application when you are ready.

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