How a Compact Executive Education Program Can Become a Full MBA

Remigiusz and Konstantin, you are both graduates of the Data Science certificate program. Why did you sign up for it?

Remigiusz: Banking is a widely data driven business and specifically in my domain it gains even more importance. In our organization, the last years were marked by emergence of use cases related to advanced analytics. However, my decision to complete this course was not only work driven. In general, being confronted with data and its variety of application in businesses models, including big data, I was looking for a comprehensive program which could introduce me to an academic backed field of study.

Konstantin: Indeed, as banking industry professionals we’re on the front line in the need to understand and find efficient usage of our data and improved analytics. In the area of credit risk management, the usage of advanced statistics and analytics methods is a fact for years. However, the modern methods and model achievements open and provide new opportunities for which I’d like to be better prepared.

Were your expectations met? How can you already implement what you have learned in your daily work?

Remigiusz: I knew that WU’s Executive Academy holds the triple accreditation. Not many business schools achieved it, so my expectations were high. Today I can say that the program I chose met my requirements of quality, scope and schedule assisting the busy professionals. Moreover, the classmates represented various industries. I liked it as it extends the horizons. All I have learned can deliver interesting use cases, also specific to my industry. For instance, the predictive CRM models which we were taught can be applicable in banking as well as in any customer’s-oriented organization, nonetheless the machine learning models for fraud detection may be specific. More importantly we had many hands-on exercises which brought a clear guidance on how to do it.

Konstantin: The program is outstanding! Expectations were met and exceeded, in terms of being a perfect combination between learning the theory about all those multiple aspects of the methods and models involved in what we have nowadays as data science domains and having intensive ‘hand-on’ sessions in the modules where we could see them applied in practice. The practice includes also our own learnings and opportunity to try it, not watching someone else doing it. This is then much easier translated in the professional environment at work. Exitance of use cases and applicability in the area of banking and credit risk is high – speaking about predictive models for borrowers’ behavior as expected creditworthiness to the areas of achieving it with less intensive demand for customers’ data being provided manually by the customers and instead using Natural Language Processing (NLP) technologies and machine/deep learning methods (e.g. OCR) for ‘reading’ readily available documents instead. And not to forget the process mining methods we learned about in the program – they were directly applicable in our work environment, as our mini-project proved.

Your joint practice project was a great success - also from your company's point of view. Can you tell us a little bit about it? What is it about?

Remigiusz: In the project we explored how the process mining, meaning combination of data science methods and BPM, can turn into a meaningful use case. Generally, the banking processes create logs of process events which can be extracted from IT systems such as, say, loan processing applications. We leveraged the existence of such event logs in our company. It brought interesting results, new knowledge about the process, proved efficiency of such an approach and set the base for enhancement. The ambition is to apply it to the mass lending business.

Konstantin: Yes, it was a very interesting and insightful project for us. It demonstrated how with the same set of data that may already exist, an organisation like ours can find additional and much more revealing usage with the help of data science methods. It was very interesting and useful to see also of our management and peers in the organisation – objective analysis and presentation of the real process and its actual metrics vs. the intended one. Brings news from a different angle, sometimes good sometimes with a lot of opportunities to act to improve.

Recently, you decided to upgrade the 12-day certificate program to a full MBA? Why?

Remigiusz: The huge advantage of the Data Science program is that it makes one of the modules of the Professional MBA Digital Transformation and Data Science. Important to say is that there are more modules which one can join as a standalone. I my case I decided immediately to continue with Blockchain. I appreciate this possibility as it enables an individual learning path and gradual entering into the fully stack MBA. I will continue it as it is complementary to my profession and will provide a relevant upgrade to my skills and knowledge. The quality of learning which I experienced so far gives me a high level of confidence in this statement.

Konstantin: Such a transformation to a full MBA was in my mind from the beginning. Due to the timing of events in 2020 we started with the specialization modules first (which are available as standalone ones) and in our case this was the Data Science module, a big one. Once started, I was even more excited and convinced I shall continue with the rest and upgrade to the full MBA course. Simply put, the appetite comes with the good food. The amazing combination of academic lecturers and professionals from the various industries’ practices brings a lot of value that is not possible to achieve otherwise in such a short time. I’d like to mention also the flexible and professional organisation of all the sub-modules, on-site and remotely during the COVID-driven lockdowns and a bit complicated logistics. All of it made my decision to apply for the full MBA very easy.

For more information about the Professional MBA Digital Transformation & Data Science, please click here.