Thesis Intern Financial Risk Management - Banking

Join the FRM Banking team to deliver extraordinary performance and impress your clients with knowledge and expertise. At Deloitte.

Job Description

• Develop and communicate a strategic and innovative vision for the financial services industry.
• Be able to engage with clients and provide advice on different aspects of financial institutions.
• Apply your skills in quantitative modelling and data analysis.
• Translate technical results into valuable stakeholder impact.
• Build an extensive network within the financial services industry and with like-minded people in the field of quantitative modelling.

Qualifications

When it comes to the technical aspects of the job, anything can happen. At the same time, you can inspire and motivate the team with new insights to deliver excellent results. You dare to try new things and you keep learning and developing, even if you experience setbacks along the way. We are looking for:

• You are in the final stage of your master's degree in econometrics, mathematics, economics, (quantitative) finance or another science master's degree.
• You are available at least 3 days a week for at least 3 months.
• You have a proposed thesis topic or are interested in the research area.
• You live in the Netherlands.
• You have an affinity with the financial sector.
• You have excellent analytical skills.
• You have an affinity for quantitative modelling and/or programming.
• You are a team player.
• You have good communication skills.
• You have a good command of Dutch and English, both written and spoken.

Additional information

FRM (Financial Risk Management) professionals help banks and other financial institutions manage risks arising from market risk factors such as interest rates and customer behaviour, as well as credit risk, where losses occur due to borrower or counterparty default. We use our extensive knowledge to help clients determine the capital they need to remain solvent in a crisis and to provide insight on how to mitigate risk, for example by adjusting assets and liabilities or using financial derivatives. We have identified the following thesis topic that we would like to explore:

ALM - Modelling NMDs (savings and current accounts) using Bayesian statistics:

In ALM modelling, such as for Non-Maturing Deposits (NMDs), we observe that a significant amount of expert knowledge is embedded in the models. This is often achieved by using experts to set the level or range for certain parameters in the model, while a frequentist approach is used for the other model parameters. Can estimating the model with expert-based prior knowledge and using Bayesian statistics improve ALM models and incorporate expert input into model calibration?

We are also open to your own ideas, so if you have a proposal for a thesis, don't forget to include it with your application.

You can apply directly via the following link: https://deloi.tt/4hvFlPN