Global investment bank seeks an AVP level Model Strategy Manager as pat of their expanding Model risk strategy function based in Manchester.
The Team support the Chief Risk Officer to develop and maintain the model suite supporting risk measurement and
management within Business Banking. As part of model ownership, we
manage the existing suite of models across the model lifecycle to
ensure that they remain appropriate for use and comply with internal
and external model risk requirements. We also work with key
stakeholders to develop and prioritise the risk grading strategy and
associated model map. We also monitor the performance of the models
and work with Model Development, Validation and other stakeholders to
assess limitations and agree and implement any mitigants/model
changes. The team co-ordinate regulatory submissions including the
annual CRR attestation and requests for regulatory approval of models/
model changes alongside regular reporting to Risk Management, Capital
and Model Risk Management Committees.
This is a dynamic role working with technical specialists to
understand the business strategy and translate this to a risk grading
strategy leveraging existing and new data sources and modelling
techniques to develop models to support the department.
Overall purpose of role
The overall purpose of this role is to support the Head of Risk
Grading Strategy in fulfilling their Model Owner responsibilities and
delivering the strategic plan for the team. The role holder will also
work with technical experts across the business to support the
development and implementation of the risk grading strategy for
Business Banking Credit Risk and provide analysis and technical
insight to support prioritisation decisions.
Model Management across the Model Lifecycle: Understand the models,
their use, performance, limitations and mitigants and co-ordinate the
completion of model governance and model management tasks as outlined
within the Group Model Risk Policy and update the relevant systems and
Reporting: Maintain and run the suite of regular reporting which
ensures that the model risk profile is communicated at key forum and
Projects: Support the Team Head in providing Model Owner input and
support for the co-ordination and control of model projects and
regulatory tasks e.g. annual CRR self-assessment and regulatory
Act as a delegate for the Team Head as required.
Regulatory Knowledge: Keep abreast of regulatory changes, new
modelling techniques and data sources to ensure compliance and
identify horizon risks.
Understanding of model risk and the fundamental principles of the CRR
Regulations relating to IRB models.
Understanding of governance and control principles and proven ability
to apply these.
Experience with, or knowledge of, model development from either work
or academia. This experience should ideally relate to risk models.
Excellent analytical skills, specifically the ability to digest and
interpret technical material and present this to key non-technical
stakeholders in a way that can be understood.
Self-motivated with the ability to multi-task and prioritise across
different activities and to be comfortable with change and a dynamic
Essential Skills/Basic Qualifications:
Educated to degree level in a quantitative subject or with appropriate
work experience to demonstrate a strong mathematical knowledge and
understanding of the practical application of statistical modelling
techniques and the management of these models;
Embrace change and able to apply strategic priorities to delivery of
own workload and proven ability to easily switch between projects
following changes of priority.
Effective networking skills to establish themselves as a subject
matter expert and a credible participant in model projects.
Experience with, or knowledge of, statistical analysis, from either
work or academia.
Desirable skills/Preferred Qualifications:
Knowledge of IRB PD, EAD and LGD modelling requirements and the
Ability to explain technical concepts to non-technical users.
Good organisational skills and a focus on delivery.
SAS/SQL/Python desirable but at the minimum proficient in Excel and PowerPoint
Awareness of data extraction, manipulation, and considerations of data
preparation for analytical purposes.
Morgan McKinley is acting as an Employment Agency and references to pay rates are indicative.