Credit Risk Modeller – AVP Jobs, UK
In this role, you will develop, validate document default probability ("PD"), loss given default (LGD) and exposure at default (EAD) models (behavioural scoring, credit grading and expert lender models) in line with Basel II Group Model Risk Policy requirements. You will also help to develop new models, document to require internal standards and present to technical committees for approval.
My client is looking for someone who can bring technical skills to the role but someone who can work closely with the business to support them in lending approvals.
Responsibilities include:
- To calibrate PD models dynamically (point-in-time through-the-cycle)
- To produce analyses to set input values for impairment calculations.
- To analyse and report on the performance EAD LGD models on a regular basis (MI production and database management), including investigating ad hoc queries.
- Develop new models, document to require internal standards and present to technical committees for approval.
- Undertake annual reviews of all models. Perform validations of existing credit risk models, covering model build and implementation. Present the findings to an approval committee relevant to the model's materiality
- Develop and produce monitoring packs / management information
- Undertake user testing for the implementation of new models
- Validation and monitoring of unidentified impairment methodology parameters
Skills required:
- An understanding of all types of credit risk models (PD LGD EAD), and their uses within a regulated bank.
- Good understanding of the Basel II or FSA requirements for the Pillar I AIRB approach to risk measurement.
- Good understanding of A-IRB Capital Calculation process.
- A high-level understanding of how non-statistical methods can be used for model development (e.g. expert lender models), as well as the application of statistical methods to Low Default Portfolios
- An in-depth understanding of the use of mathematical and statistical tools for credit risk model development, multi-factor regression, collinearity, concordance, ROC Curve, Gini etc..
- An ability to identify and analyse appropriate external data sources for model construction or validation.
- An ability to understand the relevance of appropriate data for use in high-level hypothesis testing.
- Able to produce high quality written communication including models documentation, results of research, and presentations for technical and non-technical audiences.
- Confident presentation of complex material to technical and non-technical audiences.
- Experience in the use statistics packages, such as SAS, Matlab, palisade, to perform analysis.
- Good level of programming ability.
- Strong understanding of robust and structured reporting platforms (SQL, SAS), ability to develop new reporting structures.
If you would like to apply for this role or find out more, please apply online or contact Anna Purves at Robert Walters on 0207 509 8745 or anna.purves@robertwalters.com quoting the Job Reference 1611500/APC