From complex regulations to understandable models
Marleen Cobben - Credit Risk Modeller
Clear and straightforward: that's what Marleen Cobben likes. Averse to superfluous information, she always seeks simplicity. Thus, she makes the complex understandable. As a Credit Risk Modeller, she believes in the simplest model: "Let's use data to take the complexity out of the models."
Banks are not complex
Her fascination with mathematical models began in her work as a scientist in Forest and Wildlife Management at Wageningen University. Why did she make that switch from science to finance? “I have a PhD in simulation modeling. In it, I combined ecology, evolution, climate change.”
“Science is a special world, really like finance. After my doctoral research, I found that I was not making much progress. I kept thinking pretty narrowly in my scientific domain and that bothered me. Then I started zooming out and looking around for something new. “
“Where I normally searched jobs with a keyword ‘ecological models,’ I now searched just ‘models.’ That’s how I saw a job opening at Rabobank.” Marleen laughs when she thinks back on it. “Yeah, I read the job posting and the idea of credit-risk modeling seemed pretty cool. But I actually had no idea what that meant exactly!”
“So I contacted Rabobank. And you know what the fun part is? The person I spoke to at the time is now my colleague. What she said really hit the right chord: ‘Banks are not that complex’. That down-to-earthiness immediately appealed to me. I’m a real quant in that regard. I love pouring data into a logical model, some magic over it and explaining clearly what I did. Indeed, if you look at it that way, it all doesn’t have to be very complex.”
Marleen talks about the beginning of her career at Rabobank: “On my first day here, I mostly walked around all the departments. Where should I go, what do I have to take care of? I felt it was rather hectic.” But she quickly picked up the thread as a Credit Risk Modeller. She explains that, in her own non-complex way: “A Credit Risk Modeller develops models, which account managers can use to assess credit applications. Together with a team of programmers, modelers and product owners, I specialize in implementing European legislation in those models. We ensure that Rabobank complies with the rules from Basel IV and CRR 3 . Both in determining credit risk and reporting.”
Data Science at Rabobank
A first day as a Credit Risk Modeller
“Our junior modellers often start with updates to our existing calculators and calculation rules. The legislation surrounding CRR3 is ongoing and the rules change regularly. As a junior, you will delve into documentation and regulations. You translate these into our prototypes that we create in Excel, for example. You will then work with the development team to create a working application based on the prototype. That way you learn the basic process in a short time.”
“Most of our people have studied econometrics. I think that is the academic training that best suits this work. But if you have a little penchant for numbers and can think in a visual and structured way, you’ll really know your way around with us. The regulation of Basel IV and CRR3 is something else, you really learn that on the job. You will never know everything by yourself so you work together a lot. You learn a lot from each other.”
She sits in her sunny study in Wageningen, where she interacts four days a week with the team, her peers and a variety of colleagues from the bank. “Yes that is surely the best part of my job, the contact with colleagues. As a Modeller, I know well what kind of products we sell and especially a lot about risk weight. But I know much less about the business surrounding it. If I read something I don’t know enough about, I look for a colleague who can tell me more. I then take great pleasure in talking for half an hour with a colleague about the ins and outs of such a product. By now I know how to find everyone!”
Understandable models
“What I love most about my job is that we all really build something together. We got to work implementing the European Regulations , by first reading line by line what they now say. You then have to simplify that for yourself and translate it to the situation for Rabobank. Next, we make the logic visible in calculators. Together with our Python developers, we ensure that we turn the complexity of regulations into understandable mathematical models. Which our account managers around the world can use to determine and assess credit risk. I love that I can contribute to that whole pipeline of complex regulations converted into understandable models and application forms for our colleagues.”
Marleen is aware of her role as a Credit Risk Modeller. Within the bank as well as society. “As a bank, we are at the center of society and have a responsibility there. Because we deal with credit risk, I think we are simultaneously protecting society from the power of banks. We are a part in the chain to ensure that the banks continue to function. I really feel that responsibility.”