Information for 2nd and 3rd year BSc EOR

Nicky van Foreest, Ruud Koning


1. MSc EORAs Overview

1.1. EORAS in short

In short: EORAS is the advanced data analysis master programme of FEB

1.2. EORAS illustrated by example

Illustration by example: Keep the city clean in a smart way by efficiently organizing waste collection.

  1. Collect and analyze data to determine when to empty underground waste containers (forecasting, queueing process)
  2. Determine efficient routes for the trucks to empty the containers (route optimization, data analysis to make map/one-way streets).

1.3. EORAS in steps

  1. Design/adapt rules to improve/control/change the behavior of systems (e.g. machines/population).
  2. Make models of the systems to analyze and predict the behavior under the proposed rules.
  3. Assemble data and turn this into information that can be used in the models, e.g., for forecasting.
  4. Evaluate (quantitatively) the efficacy of the information and the rules.
  5. Restart from Step 1.

1.4. Why chose MSc EORAS in Groningen?

  1. Unique mixture between data analysis (econometrics) and the application of data in decision making (OR, actuarial studies).
  2. Considerable freedom to make your own course portfolio to match with your personal/profesional current/future interests.
  3. The master is relatively small, hence opportunity for personal contact with staff.
  4. Groningen is the healthiest city of The Netherlands (Arcadis, 2022)

1.5. Why chose MSc EORAS in Groningen?


1.6. Is the MSc EORAS suitable for you?

  1. MSc EORAS requires considerable background and investment in mathematical modeling and probability/statistics.
  2. Combination of theory and empirical applications.
  3. Develop modeling skills.
  4. Is more than just number crunching: interpretation of quantitative results is very important.

2. Employability

2.1. Career perspectives

  1. Job prospective is excellent. Students find jobs within weeks after (or even before) completing the MSc EORAS.
  2. Students find jobs in consultancy firms, banks, insurance companies pension funds, government (supervisory authorities, competition authorities, central planning office), \ldots

2.2. LinkedIn connections with ex-students (of Ruud Koning)

Partner BCG, Aegon, pricing actuary Achmea, APG Asset Management, ASR, Data Analyst Ahold Delhaize,, ORTEC, PhD Student University of Oxford, Data Analyst LOGEX, professor at University of Groningen, designer at ATOS, senior policy advisor Dutch Healthcare Authority, supervisor national insurance groups at De Nederlandsche Bank, researcher ACM.

2.3. Relation to practice

  1. Courses and assignments include many practical cases which are based on company problems and company data.
  2. If you like, you can combine your thesis project with an internship at a company anywhere in The Netherlands or abroad.
  3. Program management (prof. dr. R.H. Koning and me) collaborate closely with Vesting (the student association) on employability, such as intern ships, jobs, alumni days.
  4. Students find a job very easily

3. MSc EORAS Program Organization

3.1. What are the Entrance requirements?

  1. BSc degree at BSc EOR level.
  2. Pre-MSc program for students with BSc in economics, industrial engineering and management, physics, engineering, mathematics, chemistry.
  3. Pre-MSc students should interact with students with a BSc EOR.

3.2. How is the program organized?

  1. 1st semester: preferred 5–6 courses, each 5 EC
  2. 2nd semester: 2–3 courses, each 5 EC, Master's thesis, 20 EC.
  3. Start in September or February.
  4. Nearly all Master's theses are based on internships at companies and business problems.

3.3. MSc EORAS, 3 profiles

  1. Actuarial Studies
  2. Operations Research
  3. Econometrics

3.4. What is Actuarial Studies?

  1. Risk management for the financial sector (insurance companies, pension funds, banks).
  2. Calculating insurance premiums for insurance and pensions.
  3. Modeling mortality and longevity risks.
  4. Modeling extreme events.

3.5. Actuarial Studies: Recent MSc Thesis titles

  • The Risks of Climate Change: An Insurance-based Perspective on Extreme Weather Events in The Netherlands. (EY)
  • Probability of default modeling under IFRS 9: A macroeconomic approach. (Deloitte)

3.6. What is Operations Research?

  1. Quantitative decision making for business problems.
  2. Solving complex optimization problems, for example logistic or planning problems.
  3. Finding heuristic (=approximate) solutions to very large problems, e.g., control and maintenance of wind mill farms..

3.7. Operations Research: Recent MSc Thesis titles

  • Combining fixed-line planning and dynamic routing for passenger transport. (2getthere)
  • Optimizing Maintenance Decisions for Systems with Deterioration-Dependent Production Rates.

3.8. What is Econometrics?

  1. Quantifying causal relations among economic variables.
  2. Forecasting economic variables, such as demand, unemployment, or inflation.
  3. Quantifying the consequences of economic or political choices.
  4. Assessing the consequences of interventions.
  5. Developing statistical theory to estimate econometric models.

3.9. Econometrics: Recent MSc Thesis titles

  • Global portfolio diversification from a eurozone perspective.
  • Estimating the Effects of Patient Intensity on Physician’s Time Spent on a Patient to Review Care Product Lead Times. (Logex)

3.10. Commonality in all three profiles

  • Avanced data analytics (on big data sets).
  • Human behavior and feedback play an important role.
  • Mathematical methods are similar.
  • Multi viewpoints are necessary to understand and model large practical problems.
  • Very often the thesis project is combined with an internship at a company.

3.11. How can I meet my main interests?

  1. Actuarial Studies, track:
    • Risk management
    • Quantitative finance
    • Statistics
  2. Econometrics, tracks:
    • Applied econometrics
    • Marketing
    • Quantitative finance
  3. Operations Research, tracks:
    • Systems analysis
    • Machine learning
    • Optimization and theory

Details on Brightspace

3.12. Example track, AS/Risk management

1.1 Dependence and Extremes in Risk Management
1.1 Optimization under Uncertainty
1.2 Models for Short Term Risk Management
1.2 Planning and Control of Stochastic Systems
2.1 Asset and Liability Management
2.1 Banking, Insurance and Risk Management
2.2 Data analysis and Machine learning
2.2 Quantitative Finance
2 Master's thesis Actuarial Studies

4. Remaining Questions?