Team Description

IFRS9 Modelling Team is responsible for the development and implementation of Credit Models that are used for IFRS9 Expected Loss Estimation for the Banking Book. The team is responsible for taking credit models through the full end-to-end process of model development: including taking models through the internal governance process for approval and implementing the models into a production environment.

Description of role and key responsibilities

·     Development of PD, LGD, EAD Models.

·     Responsible for developing/supporting the development of models as an end-to-end process. This includes: Scope model requirement, data review, portfolio analysis, develop model, engage key stakeholders, creating model documentation, take models through internal governance process for approval, and support the implementation of models.

·     Assist other team members in the development of Credit Models.

·     Other responsibilities also include: Creating an annual review of models, Reviewing the model performance, model calibration, back-testing models, and creating supporting analysis on models.

·     Research, design and implementation of best practice methodologies for quantifying credit risk in line with PRA Supervisory requirements on model development.

·     Proactively engage with Credit and the Business unit to support understanding of Credit Models by providing model training and model support.

·     Create documentation of model methodology, process and techniques used in the model development.

·     Practical experience with predictive modelling techniques such as logistic regression is desirable

·     Support model implementation within the bank's credit risk framework.

·     Resolve ADHOC model related issue

Core skills and knowledge

Technical Skills:

·     Degree / Masters in Statistical, mathematical, financial or economics / STEM Subjects

·     Good understanding of PD and LGD Models.

·     Minimum 5+ years of Model development experience, with hands-on experience of using Python / R language for PD / LGD model development

·     Strong Analytical skills: Quantitative problem solving and judgements. Ability to analyse, interpret and present complex analytical data, both verbally and in writing. Strong experience in developing practical technical solutions with limited data.

·     Strong interest in learning, understanding, and developing credit models and machine learning techniques

·     Model documentation and presentation skills: prepare high-quality analytical papers and present these papers in an effective manner appropriate to the target audience / key stakeholders.   

Soft Skills:

·     Willingness to learn and adapt to change quickly

·     Strong teamwork ethics

·     Self-motivated. Capable of working independently as well as within a team

·     Strong Communication Skills (Written, Verbal & Presentation skills)

Any other attributes that would be helpful, but not essential for the role.

·     Understanding of SQL

·     Good understanding of Git (GitHub/GitLab) is a plus

·     Proficient in Excel, databases/ SQL, and Microsoft Office

·     Stakeholder management experience/skills is a plus;