Working at the heart of the bank, making it future-proof with predictive models
Paula Zajanckovskaja, Modelling Consultant
Credit risk models: the bank depends on them. They enable data-driven and adequate decision making. This is what makes Modelling Consultant Paula enjoy her work. Navigating her way through a complex web of internal and external stakeholders, she works hard to contribute to the development of the best possible predictive models. She comes from Lithuania, but Rabobank feels like home to her, thanks to the close community of like-minded data professionals she's part of. She wouldn't trade her job for the world and is happy to share why.
Being the linking pin
‘Working in the field of Data Science is truly one of the most exciting things you can do within the bank. As a Modelling Consultant I’m responsible for supporting the development and maintenance of Rabobank’s credit risk models. It’s an extremely versatile job because our models have a big impact and are interwoven with pretty much every business department and their processes. We are truly the heart of the bank and I’m in the middle of it all. The linking pin within a very extensive and dynamic stakeholder field.’
‘Important stakeholders are the colleagues who actually need to work with our credit risk models. Analysts, who determine whether and what type of loan a client gets, for example, or make capital calculations with the help of our models. We also work closely with the data team to make processes more efficient. For the implementation of the models, we turn to colleagues from IT. And for independent internal challenge, there are dedicated model validation and audit teams. Finally, there’s an external stakeholder from who we need approval: the ECB. The challenge for me is to keep close contact with all these stakeholders and make sure the process of model development runs smoothly within a complex quantitative and regulatory framework. Hereby ensuring that business needs are being met.’
The necessity of models
‘To explain the function of a model, I always refer to the essence of banking: helping people and society financially. By providing loans or credit facilities, Rabobank helps people to run their business or buy a house. But loans obviously carry risks. That’s where models come in. We use credit risk models to predict the probability that a client won’t be able to pay back their loan and what the expected loss would be for the bank, all based on data. A lot of data. So to make these estimations manually would be a very complex and inefficient exercise. Models are indispensable for banking. Without them, Rabobank would never be as efficient as it is now.’
Data Science at Rabobank
Data-driven, compliant decision making
‘To me, this job really matters. Models are the driving force behind the bank, because practically every aspect of banking depends on it, for example, client acceptance, pricing, capital calculations. They are used in everyday business processes, supporting effective, data-driven and compliant decision making for us to be and stay a future-proof bank. Therefore it’s a huge responsibility to make accurate and trustworthy predictions with our credit risk models. Not only the quality of our products depends on it, but the way we help clients and the way we fulfill our role in society as a financial institution.’
Analytics community
‘Another aspect that makes my work so valuable, is the team. We all have a different background in education, culture and age, but we also have a lot in common. What I love is that we challenge each other to stay on our toes. We are eager to learn, to teach and we encourage each other.’
‘Because of our shared talents, interests, and our close collaboration, I feel like I’m part of an analytics community within Rabobank. This feeling is a big part of what keeps me motivated and interested. I’m from Lithuania originally, and my family lives over there. But my team over here is so much fun, I see them as my work family. A family of highly intelligent and kind people. ‘