Credit Risk Manager Intern

The Group Investment Office (GIO) oversees the management of the invested assets of SCOR Group. Within the Group Investment Office, the Group Investment Risks and Control team is in charge, for the Group and the entities, of monitoring market and credit risks (quantitative and qualitative) borne by SCOR’s invested assets portfolios, as well as ensuring the compliance of the invested assets portfolios. The intern will join the Credit Risk team and contribute to the work related to the assessment and monitoring of credit risk under the IFRS 9 framework applied to the invested assets portfolios. Within an international environment and a wide range of asset classes (bonds, loans, securitized products, etc.), the intern will participate in the analysis of the methodologies and models used for credit risk evaluation. The main purpose of the internship is to propose a potential alternative simplified and comprehensive model for Expected Credit Losses under IFRS 9. The staging rules, the calculation of Loss Given Default, and the economic scenarios to be considered for conditional probabilities are not to be studied as part of the internship. However, a method for calculating conditional probabilities that incorporates economic scenarios must be proposed. The intern will be able to leverage on the current IFRS 9 framework and model, identifying bottlenecks, complexity and limitations. It is expected that the intern will consolidate these analyses into a comprehensive and well-structured research paper, including a quantitative analysis on a target portfolio representative of SCOR’s assets. This internship offers a unique opportunity to deepen methodological understanding of IFRS 9, work closely with experts in financial risk management, and develop solid knowledge of credit risk dynamics within a globally diversified investment portfolio. You will work closely with the other team members of the Group Investment Office and with various other stakeholders (asset managers, accountants, IT, Group Risk coverage team, auditors…).

Credit Risk & IFRS9 Conduct a comprehensive methodological review of the credit risk models (Default Probability, Loss Given Default, staging, , etc.), assess their assumptions, limitations, and potential improvements, and produce a structured paper on the subject, in IFRS 9 framework. Ability to simulate IFRS 9 accounting calculations using PD-based models, building on the findings from the preliminary methodological review.

Required experience & competencies Experience: Experience in Finance or Academic research in Finance is preferred Personal Competencies: Strong analytical capabilities, rigor Good interpersonal skills and multicultural awareness and sensitivity Good knowledge of credit risk modelling (probability of default, loss given default, exposure at default) Strong interest in financial markets Soft skills: Open and critical mindset, curiosity, creativity, proactivity Good team spirit, ability to work with different interlocutors with different skills Good culture of transparency, experience and knowledge sharing Digital Competencies: Python, MS office (VBA), SQL basic knowledge, Power BI. Not necessary but a plus: Bloomberg, Moody’s analytics solutions Required Education Student from a top engineering school or enrolled in a Master of Science (Bac+5) in Mathematics, Quantitative Finance, Actuarial science, Economics, or another quantitative field. PhD students with a strong interest in quantitative finance research are also welcome. Strong interest in credit risk research and methodological work. Strong writing and synthesis skills. Fluent in English, both written and spoken. High intellectual curiosity and appetite for rigorous analytical work.