Model Validation Professional

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 models used by MUFG in EMEA. This includes, among others, risk 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 we'll as at inception and changes. MRM provides regular model risk reporting to model oversight committees and the Board.

Position details

Purpose of the role:

Independent model validation of quantitative methodologies, both initial and periodic, across all asset classes and model types (derivative pricing models, credit and market risk, capital models, AI models, etc ) and in line with regulatory requirements and industry best practice. The validation regularly requires an independent implementation of the models and the implementation of alternative challenger models.

Roles and Responsibilities

• Initial and periodic validation of quant models
• Designing, modelling and prototyping challenger models
• Quantitative analysis and review of model frameworks, assumptions, data, and results
• 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

Essential:

At least a first relevant experience in quantitative modelling (model development or validation) in one or more of these topics:

• Market risk models
• Counterparty credit risk models
• Derivatives pricing models
• Corporate credit risk models (IRB, PD/LGD/EAD)

Optional:

• Capital models (Economic/Regulatory)

Competencies:

Essential:

• Good 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.
• Good knowledge of simulation and numerical methods
• Awareness of latest technical developments in financial mathematics, pricing, and risk modelling

Beneficial:

• Experience with C++ or C# or equivalent

Optional:

• Experience with AI models
• Up-to-date knowledge of regulatory capital requirements for market and credit risk

Education :

• A Postgraduate degree in a quantitative discipline (eg, statistics, mathematics, mathematical finance, econometrics)

Personal requirements

• 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