Company: EY ifb
Company background: EY ifb offers an array of full-service solutions to help banks and insurance companies in their finance, risk and digital transformation. We map the multi-layered demands of supervision, management, accounting and risk and embed them in advanced IT architectures (https://www.ey.com/en_gl/ey-ifb).
Contact: Markus Weick
Title: Manager
Country: Germany
Award Category: Curious Thinker
Tell us how you are inspired by the work you do?
Solving puzzles and problems has fascinated me since primary school. And using this to provide people with new insights has been at the heart of my working experience since. And I like keeping on learning myself and adding to my experiences. One example from last week: In the user interface of an Equity Risk Model application of a client I replaced the abstract parameters of a lognormal distribution by debt ratio and PD (Probability of Default). Mathematically it was a simple transformation. But it allowed the client to parametrize the model with practical parameters, he could relate to.
How has SAS played a part in your journey?
When I joined EY ifb, a leading Finance and Risk IT consultancy, in 2021 for me SAS was the Software of choice. This is because SAS is not just another software for which we support our customers through implementation, customization and so on.
SAS for me is also a valuable tool for my own risk analysis having worked in risk management for thirty years.
SAS provides me with the tools I need for complex Risk analysis through Monte Carlo Simulations.
The SAS System of user support and engagement has helped me not only in learning SAS but also with supporting the position of SAS in my company. My personal highlight was visiting SAS Explore in 2023 as a winner in the SAS Customer Recognition Awards, with a lot of interesting conversations.
What products do you use and how do you use them?
Beside data step and different procs in SAS Base, I have used Visual Analytics for a Climate Risk Stress Test and I am using increasingly SAS IML for an equity risk model.
In future I will dive into ALM, Machine Learning and CI to work on an Bank deposit management which integrates Treasury and Retail Banking functions.
What is your greatest lesson learned that you'd like to share with others?
Though I do some programming in Base SAS, I do mainly Risk Modelling. So my lessons are around modelling. They were formulated by thinkers of our times and I can confirm them out of my own risk management practise.
From my teacher at The University of Lancaster, UK, Professor Michael Pidd I took the adivse „model parsimonious!“, so extract the essential!
The Statistician and Modeller George Box is quoted with „All models are wrong, but some are useful“. So always keep the scope of application in mind.
Also one of Yogi Berra‘s Yogiisms has been a valuable advice: „In theory there is no difference between theory and practice - in practice there is“.
I want to conclude with an answer to the question wether modelling is Science or Art. Professor Aswath Damodaran answered it for his branch of Modelling, Valuation: It is a Craft.
