Manager - Credit Risk
|Job Title:||Manager - Credit Risk|
|Contact Name:||PwCRecruiting Team|
|Job Published:||June 11, 2019 19:06|
RMS Experienced Senior Associate/ Manager – Credit Risk Modelling (focus on IFRS 9 and IRB Models)
About the team
The world of Risk and Regulation is changing; join us on the journey and be part of creating a new and relevant financial services industry.
Our Financial Services Risk and Regulation (FSRR) team is made up of over 80 partners and 1300 professional staff and our number and capabilities are expanding every day. Within FSRR, the Banking Models proposition involves advising leading banking groups on a wide variety of risk, value and capital management issues. These include:
Credit risk modelling including IRB modelling
IFRS9 provision modelling
Credit risk stress testing
Model validation and assurance
Model governance and review
About the role
The role will involve working with our existing team of approximately 60 banking model specialists to build on our current portfolio of projects in credit risk modelling and validation and increase our capacity and offering in the area of credit risk stress testing. This will include:
Advice and support in relation to IRB capital models; providing model build services, performing CRR (capital requirements regulation) attestation and advising our clients as they develop IRB capital models for the impending regulatory changes.
Support to Model Validation teams; carrying out full range of validation activities including assessment of conceptual soundness, challenging underlying assumptions, validating data and assessing limitations of the models.
Taking a manager role on a number of IFRS 9 audits for our banking clients in the UK.
Providing advice to banks relating to future generations of IFRS 9 models and IFRS 9 forecasting.
Advising our clients on credit risk stress testing model approaches.
Interaction with stakeholders including credit risk managers, model development teams, internal stakeholders.
Helping to develop our internal IFRS 9 and IRB banking propositions to take to market
Maintaining an up-to-date view of regulatory and industry developments in relation to credit risk Basel modelling, IFRS 9 modelling and stress testing credit risk modelling, sharing this with the wider team and maintaining leading edge best practice in work performed.
Essential skills and experience:
Retail credit risk modellers with a minimum of 3 years model build experience.
Proficient in base SAS and statistical modelling packages.
Experience across scorecard PD modelling and IRB TTC (through-the-cycle) calibration techniques.
Experience in LGD IRB modelling across secured and unsecured portfolios, and in downturn LGD calibration techniques.
Experience in writing model documentation at standards required for regulatory submission.
Familiar with the CRR (capital requirements regulation) and the impending regulatory updates across the PRA, EBA and Basel Committee. In particular, knowledge of the Definition of Default and Hybrid PD regulatory updates.
Strong general knowledge of credit risk concepts.
Exceptional communication skills, with particular emphasis on communicating technical complexity to both technical and non-technical audiences.
Strong people management and client relationship skills including inter-personal sensitivity, influencing and negotiation skills.
Ability to develop good client/internal client handling skills, including relationship-building skills that lead to increased consulting opportunities.
Creativity and problem-solving skills in individual, team and collaborative consultant-client settings.
Strong commitment to both personal and team success.
Openness and willingness to share ideas and knowledge.
Willingness to travel to client sites and other UK office locations.
Desirable skills/ attributes:
Degree (or equivalent) in technical subject plus further qualification (such as MSc, PhD or professional qualification in relevant subject/area, e.g., mathematical finance or technical research involving maths or numerical programming).
Knowledge of at least one of the following (or similar): SQL, R, Python
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