ABN AMRO is on the trend of greater use of statistical models. This development is driven in part by regulations, but the growing reliance on models manifests in all areas of the bank. For risk management purposes ABN AMRO has models in place for, among others, credit risk, market risk, operational risk, and liquidity risk, covering the entire balance sheet of the bank. These models use market and client data to predict the client behaviour and their risk profile based on the client characteristics, the economy and the market. Outside the risk management domain, model-based decision making becomes increasingly important and accepted. Our team, the Credit Risk Modelling team, is responsible for the (re)development of credit risk models for retail portfolios within ABN AMRO.
The Credit Risk Modelling team (re)develops credit risk models focused on retail clients (mortgages, SME, etc.) and non-retail clients (Corporations). By analysing client data from the past, existing models are updated and if necessary new models are developed. The resulting models predict the probability a retail client is unable to repay a credit, and consequently the expected loss for the bank. Based on that, the model determines the capital that ABN AMRO needs to keep at hand. In this way, the quality of the model has a big impact on the bank’s risk profile, and its profit and loss.
The team is a young and dynamic group with a very international and diverse background. This diversity, in terms of cultural background, gender, academic and working experience creates an optimal blend.
ABN AMRO Credit Risk Modelling is looking for enthusiastic and social Business Administration/MBA with quantitative skills or Econometrics/Quantitative Finance MSc. students to assist the team and the management with administrative tasks and a few ad hoc assignments, such as help in project planning, taking notes during expert meetings and assisting management in preparing for internal and external high-level meetings. In the long term, contributing to the modelling team on a content level will be considered.
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Optionally, in order to perform modelling tasks in a later stage, knowledge of programming languages (preferably Python) and statistical software (SAS) is required, as well as good analytical and quantitative skills.
Are you interested and do you match the profile? Please send your CV and motivation letter using the Apply button below.