Enterprise Risk Management (ERM) is responsible for supporting the EMEA Chief Risk Officer to implement an effective risk governance framework across MUFG EMEA, and providing a holistic view of the risks facing MUFG in EMEA, including environmental and social risk management.
The Model Risk Management (MRM) within ERM is responsible for model governance and the validation of all risk models used by MUFG in EMEA. This includes risk models used for regulatory capital purposes, as well as market, credit, operational, economic capital and stress testing models which are used for risk measurement and decision-making purposes. MRM works closely with Risk Analytics and Front Office quants to ensure that all risk models are validated on a periodic basis as well as at inception and changes. MRM provides regular model risk reporting to model oversight committees and the Board.
MAIN PURPOSE OF THE ROLE
Independent model validation of risk quantitative methodologies, both initial and periodic, across all asset classes and risk types (credit risk, market risk, economic capital, stress testing models, etc. ) and in line with regulatory requirements and industry best practice.
- Initial and periodic validation of quant models
- Quantitative analysis and review of model frameworks, assumptions, data, and results
- Designing, modelling and prototyping challenger models when required
- Testing models numerical implementations and reviewing documentations
- Checking the adherence to governance requirements
- Documentation of findings in validation reports, including raising recommendations for model improvements
- Ensuring models are validated in line with regulatory requirements and industry best practice
- Tracking remediation of validation recommendations
- Preparation of model risk reporting for Model Oversight Committee and Board
SKILLS AND EXPERIENCE
- Experience in risk-modelling of banking book portfolios (model development or validation)
- Knowledge of corporate credit risk models (IRB, AIRB, PD/LGD/EAD)
- Experience in market risk or/and counterparty risk modelling
- Experience with other risk models (Economic Capital, Stress Testing, etc.)
- Experience with derivatives pricing models
- Strong background in Math and Probability theory - applied to finance.
- Good knowledge of Data Science and Statistical inference techniques.
- Good understanding of financial products.
- Good programming level in Python or R or equivalent.
- Awareness of latest technical developments in financial mathematics, pricing, and risk modelling
- Modelling and pricing of financial derivatives
- Computer simulations and numerical approximation methods
- Experience with C++ or C# or equivalent
- Up-to-date knowledge of regulatory capital requirements for market and credit risk
- A Postgraduate degree in a quantitative discipline (e.g., statistics, mathematics, mathematical finance, econometrics)
- Strong problem solving skills
- Strong numerical skills
- A structured and logical approach to work
- Excellent attention to detail
- Excellent written and oral communication skills
- Ability to clearly explain technical matters
- A pro-active, motivated approach