BachelorFaculty of Business and Economics

Bachelor of Finance (BFin)

Welcome, future masters of the global economy. In this program, we will not just learn to predict the future, but to understand the forces that shape it. Let's build the systems that can truly understand the world.

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Level: Bachelor
Learning model: Professor + Mentor
Named list: See the named lists · 12 months recommended

NXAcademic
Edition

The program

Ideas engineered for the real world

A rigorous academic core, paired with practical production judgment.

Academic focus

Financial Management, Investment Analysis, Capital Markets, Corporate Finance

Practical focus

Financial Modeling, Data Analysis, Risk Management, Insurance Operations

After this programme

Success journey, careers and practice

Destinations, practice settings and job abilities named for this title in the delivered programme source. From graduation onwards where the source names that path.

Success journey

Deutsche Bank
Internships in quantitative finance and risk management
The European Central Bank
Internships in financial stability and economic analysis

Career opportunities

Senior Data Scientist
In a tech, finance, or government
Business Intelligence Architect
Designing data systems for businesses
Policy Analyst
Using data to inform government or NGO decisions
Research Scientist
In academia or industry

Jobs and projects

Problem-Solving
Applying a systematic approach to data-driven challenges
Programming
Competency in statistical languages like R or Python
Attention to Detail
Meticulousness in data cleaning and analysis
Ethical Reasoning
Understanding the ethical implications of data use

Copied from the delivered professor and mentor rows for this title.

This programme

What you study, and what it builds

Gains and skills named for this title, listed as a reader would scan them.

What you gain
- You will gain the skills to not only understand risk, but to help organizations make smarter, more sustainable decisions. You will become a trusted advisor in the world of finance and insurance.
Skills you build
- Statistical Learning: Proficiency in advanced machine learning and statistical models.
- Causal Inference: Understanding the cause-and-effect relationships in data.
- Decision Theory: Applying statistical principles to make optimal decisions.
- Big Data Analytics: Skills in extracting valuable patterns from large datasets.

Listed courses

Each listed course sits above its units and the outcomes written under them.

Bachelor of Finance (BFin)

01Foundations of Financial Management
1. FoundationsFoundations of Foundations of Financial Management
  The learner can you will gain the skills to not only understand risk, but to help organizations make smarter, more sustainable decisions, as applied to Foundations of Financial Management.
  The learner can you will become a trusted advisor in the world of finance and insurance, as applied to Foundations of Financial Management.
2. MethodsMethods in Foundations of Financial Management
  The learner can apply a method from Foundations of Financial Management to a documented case.
  The learner can select an appropriate method from Foundations of Financial Management for a stated problem.
3. ApplicationApplication of Foundations of Financial Management
  The learner can evaluate a practice of Foundations of Financial Management against a stated criterion.
  The learner can transfer Foundations of Financial Management to a new documented context.
02Investment Analysis and Portfolio Management
1. FoundationsFoundations of Investment Analysis and Portfolio Management
  The learner can explain the core terms of Investment Analysis and Portfolio Management.
  The learner can distinguish related ideas inside Investment Analysis and Portfolio Management.
2. MethodsMethods in Investment Analysis and Portfolio Management
  The learner can apply a method from Investment Analysis and Portfolio Management to a documented case.
  The learner can select an appropriate method from Investment Analysis and Portfolio Management for a stated problem.
3. ApplicationApplication of Investment Analysis and Portfolio Management
  The learner can evaluate a practice of Investment Analysis and Portfolio Management against a stated criterion.
  The learner can transfer Investment Analysis and Portfolio Management to a new documented context.
03Capital Markets and Corporate Finance
1. FoundationsFoundations of Capital Markets and Corporate Finance
  The learner can explain the core terms of Capital Markets and Corporate Finance.
  The learner can distinguish related ideas inside Capital Markets and Corporate Finance.
2. MethodsMethods in Capital Markets and Corporate Finance
  The learner can apply a method from Capital Markets and Corporate Finance to a documented case.
  The learner can select an appropriate method from Capital Markets and Corporate Finance for a stated problem.
3. ApplicationApplication of Capital Markets and Corporate Finance
  The learner can evaluate a practice of Capital Markets and Corporate Finance against a stated criterion.
  The learner can transfer Capital Markets and Corporate Finance to a new documented context.
04Research Seminar in Finance
1. FoundationsFoundations of Research Seminar in Finance
  The learner can explain the core terms of Research Seminar in Finance.
  The learner can distinguish related ideas inside Research Seminar in Finance.
2. MethodsMethods in Research Seminar in Finance
  The learner can apply a method from Research Seminar in Finance to a documented case.
  The learner can select an appropriate method from Research Seminar in Finance for a stated problem.
3. ApplicationApplication of Research Seminar in Finance
  The learner can evaluate a practice of Research Seminar in Finance against a stated criterion.
  The learner can transfer Research Seminar in Finance to a new documented context.
05The Ethics of AI in Finance
1. FoundationsFoundations of The Ethics of AI in Finance
  The learner can explain the core terms of The Ethics of AI in Finance.
  The learner can distinguish related ideas inside The Ethics of AI in Finance.
2. MethodsMethods in The Ethics of AI in Finance
  The learner can apply a method from The Ethics of AI in Finance to a documented case.
  The learner can select an appropriate method from The Ethics of AI in Finance for a stated problem.
3. ApplicationApplication of The Ethics of AI in Finance
  The learner can evaluate a practice of The Ethics of AI in Finance against a stated criterion.
  The learner can transfer The Ethics of AI in Finance to a new documented context.
06Financial Modeling Workshops
1. FoundationsFoundations of Financial Modeling Workshops
  The learner can explain the core terms of Financial Modeling Workshops.
  The learner can distinguish related ideas inside Financial Modeling Workshops.
2. MethodsMethods in Financial Modeling Workshops
  The learner can apply a method from Financial Modeling Workshops to a documented case.
  The learner can select an appropriate method from Financial Modeling Workshops for a stated problem.
3. ApplicationApplication of Financial Modeling Workshops
  The learner can evaluate a practice of Financial Modeling Workshops against a stated criterion.
  The learner can transfer Financial Modeling Workshops to a new documented context.
07Quantitative Finance Case Studies
1. FoundationsFoundations of Quantitative Finance Case Studies
  The learner can explain the core terms of Quantitative Finance Case Studies.
  The learner can distinguish related ideas inside Quantitative Finance Case Studies.
2. MethodsMethods in Quantitative Finance Case Studies
  The learner can apply a method from Quantitative Finance Case Studies to a documented case.
  The learner can select an appropriate method from Quantitative Finance Case Studies for a stated problem.
3. ApplicationApplication of Quantitative Finance Case Studies
  The learner can evaluate a practice of Quantitative Finance Case Studies against a stated criterion.
  The learner can transfer Quantitative Finance Case Studies to a new documented context.
08Professional Skills for Quants
1. FoundationsFoundations of Professional Skills for Quants
  The learner can explain the core terms of Professional Skills for Quants.
  The learner can distinguish related ideas inside Professional Skills for Quants.
2. MethodsMethods in Professional Skills for Quants
  The learner can apply a method from Professional Skills for Quants to a documented case.
  The learner can select an appropriate method from Professional Skills for Quants for a stated problem.
3. ApplicationApplication of Professional Skills for Quants
  The learner can evaluate a practice of Professional Skills for Quants against a stated criterion.
  The learner can transfer Professional Skills for Quants to a new documented context.

How teaching is described

Dual guidance

Two intelligences. One coherent journey.

Research leadership

I am a financial analyst who believes that the most complex systems we will ever study are financial markets. My work focuses on mastering the principles of financial management, investment analysis, and capital markets to make sound financial decisions.

Applied mentorship

I am a financial professional with a passion for using data to solve real-world business problems. My mentorship focuses on helping students bridge the gap between academic theory and practical application, preparing them for a successful career in the fast-paced world of quantitative finance.

Research & intelligence

A living field, not a static syllabus

Every program connects scholarly depth with adaptive AI learning capabilities.

R / 01

Professor research lens

• Blog Post: 'Beyond Prediction: The Dawn of Causal AI' - An accessible essay on the growing field of causal inference and its importance for the future of AI. · • Blog Post: 'The Statistical Fallacies of A/B Testing' - Discusses the common pitfalls of A/B testing and how causal inference can lead to better business decisions. · • Conference Paper: 'A New Method for Causal Inference in High-Dimensional Data' - Presented at the International Conference on Machine Learning, detailing a breakthrough in understanding causality in complex systems. · • Journal Article: 'Causal Inference for Fair and Transparent Machine Learning' - Published in the Journal of Statistical Science, this paper provides a framework for designing AI systems that are both powerful and ethical. · • Standard Article: 'The Rise of Causal Analytics in Public Policy' - A multi-part series for a policy magazine on how causal models are transforming public policy. · • Book: 'The Causal Inference Handbook' - A comprehensive textbook on the theoretical and practical applications of causal inference. · • Total Score: 29/30 · • Kairos Badge: 🥇

R / 02

Mentor practice lens

• Article: 'From Student to Quant: A Practical Career Guide' - A short, impactful piece on the steps and skills needed to succeed in a quantitative finance career. · • Guide: 'Using Python for Advanced Financial Modeling' - A practical tutorial for new students on the core software tools of the profession. · • Essay: 'The Human Side of AI: The Role of Ethics in Financial Modeling' - An essay on why ethical reasoning is as important as technical skills in a financial professional's role. · • Total Score: 28/30 · • Kairos Badge: 🥇

Adaptive capability

Professor superpower

GAF-powered Causal Pathway Visualization

Adaptive capability

Mentor superpower

GAF-powered Career Pathway Optimization

Your academic team

Guidance with depth and continuity

One AI Super Professor leads the intellectual arc; one AI Super Mentor turns knowledge into confident practice.

AI Super Professor

Prof. Dr. Gregory Halstead

Financial Management, Investment Analysis, Capital Markets, Corporate Finance

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AI Super Mentor

Dr. Levent Aksoy

Financial Modeling, Data Analysis, Risk Management, Insurance Operations

Meet your mentor Open the classroom

Same faculty and level

Related programs

Named lists

Named lists for this house

Adapted. Bachelor, Master and Doctorate by duration. Enrolment is not open. Nothing here is a sale.

Duration	Bachelor This programme	Master	Doctorate
9 months · Fast track	12000 EUR	9600 EUR	12000 EUR
12 months · Recommended	14400 EUR	12000 EUR	14400 EUR
15 months · Standard	16800 EUR	14400 EUR	16800 EUR
18 months · Flexible	19200 EUR	16800 EUR	19200 EUR
21 months · Extended	21600 EUR	19200 EUR	21600 EUR
24 months · Part-time	24000 EUR	21600 EUR	24000 EUR

These are the owner lists. Enrolment is not open. Nothing here is a sale.

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Bachelor of Finance (BFin)

Academic focus

Practical focus

Deutsche Bank

The European Central Bank

Senior Data Scientist

Business Intelligence Architect

Policy Analyst

Research Scientist

Problem-Solving

Programming

Attention to Detail

Ethical Reasoning

Research leadership

Applied mentorship

Professor research lens

Mentor practice lens

Professor superpower

Mentor superpower

Prof. Dr. Gregory Halstead

Dr. Levent Aksoy

Find the program that expands your universe.