Risk Modelling Analyst

Risk Modelling Analyst

Dexia

Brussels, Belgium

Mission Description

Within the Risk Department, you will work in the RMQD (Risk Models, Quantification and Defaults) team. You will participate in the development and use of the quantitative credit risk models, both at counterparty and portfolio level.

The models are used by the RMQD team for key strategic exercises, ranging from quarterly provision calculations, projections of the key risk measures in the financial plan & stress testing and the RAS/RAF framework. Stress testing goes beyond the credit risk scope and integrates stress on other risk types, in particular market and operational risk.

Dexia’s credit risk models take into account the changing economic environment and upcoming risks. You will be involved in the development and maintenance that includes:

• The development, maintenance and backtesting of the internal credit risk models, which are used for analyzing the counterparty-level credit risk in the Dexia Portfolio. This implies the construction of rating and PD migration models and LGD models, both long-term Through-The-Cycle and Point-In-Time macro-economic models;
• The calibration of the parameters of the internally developed portfolio management tool which assesses the portfolio tail risk (Credit Value-at-Risk). These include a.o. the calibration of stochastic PD and LGD, the asset correlation structure and global maintenance/updates of the portfolio management tool to reflect the portfolio’s risk dynamics;
• Apply these models for baseline projections, quarterly provisioning, as well as stress testing, portfolio analysis and other risk projections;
• Contribute to the global stress testing exercises and RAS/RAF framework, where credit, market and operational risks are jointly assessed;
• Ensure maintenance of the internal risk tools and their implementation, based on best practice coding and transparency for the end user.

This is a perfect first experience in the quantitative risk framework, in a multicultural environment within a highly motivated team. The model development is generally done in Python/Matlab, while the data treatment is mainly based on SQL.

Profile

• University degree with a strong quantitative orientation (mathematics, commercial engineering, statistics, physics, etc.);
• Preference for specific orientation in Financial Mathematics, Risk & Financial Engineering or similar with experience in one or more of the following domains:
  • Empirical statistics: regression analysis, nonlinear models;
  • Stochastic & Probabilistic methods applied to Finance;
  • Quantitative Portfolio Management;
  • Optimization techniques;
  • Risk measures & management.
• Profound knowledge of English and French are required.