The Credit Risk Modelling team is responsible for the development, oversight and embedding of credit risk measurement models for the bank.
The Quantitative Analyst plays an important role within the Credit Risk Modelling team to, develop the credit risk models to predict risk estimates such as PD, EAD, and LGD, and operational models to support credit risk decisions.
Areas the models will be used include :
Basel models to support the Capital Calculation
Acquisitions Management Areas of responsibility may include but not limited to Build, validate, document, implement, monitor and rebuild :
Credit risk models (retail loan origination models, business banking customer rating models, and loan behaviour scorecards)
Collective Provision and Expected Loss methodologies. This includes all inputs of Probability of Default, Loss Given Default and Exposure at Default (methodology).
Conduct detailed analytical work with a high level of accuracy in order to deliver high level results to senior management.
Develop ongoing improvements to the model reporting.
Responsible for managing issues through to resolution.
Define and specify key data requirements to support modelling approaches.
Document model technical manual , modelling choices made, and model methodology considerations. Working with the leaders of the Credit Risk Modelling team to ensure :
Models are effectively embedded into operational activities
The program of work for the department is documented and resourcing or delivery issues are well managed.
Identifying inefficiencies and proposing operational process improvements to enable better outcomes. Add value to deliverables with excellent problem solving, idea generation and strategic thinking.
Work closely with the wider Credit Team, Finance, Product Development and System Architects to optimize the best solution for the bank and group.
Personal Attributes and Skills
Resourceful and tenacious
Focused on driving results
Organised and process oriented; ability to multi-task and manage time effectively
Ability to convey complex data in a concise understandable manner and distil the key messages
Strong problem-solving skills
Ability to work effectively across varying levels of Management and multi-disciplinary teams
Good and clear written style.
Strong verbal and written reporting skills.
Quantitative / qualitative analytical skills Education and Experience
MSc / BSc (Hons) in Statistics / Actuarial Science / Financial Maths / Applied Maths
Programming capabilities in SAS / R / Python / VBA
At least 3-5 years of experience in relevant field (e.g. behavioural credit scoring, credit impairments under IFRS 9, regulatory capital requirements, credit risk management processes across the credit life cycle)
Retail banking experience
Strong track record of professional performance
Skilled in Microsoft products, particularly PowerPoint, Word, Excel and Access