Quantitative Analysis Wholesale Credit Risk - Statistical Modelling (R)

  • £exec+bens
  • London, England, United Kingdom
  • Permanent, Full time
  • Charles Levick
  • 26 Sep 16

QA Wholesale Credit Risk develop models for capital (Basel), impairment (IAS39/37, IFRS9), and stress testing (CCAR, PRA, EBA). Model outputs are utilised across a range of risk metrics, including RWA, pricing, Economic Capital, and for credit sanctioning. The model scope covers the Corporate and Investment Bank (CIB).

~~About QA
The Quantitative Analytics group is responsible for the research, development and implementation of cutting-edge, market leading quantitative models across all asset classes (Interest Rates, Credit, Equity, Foreign Exchange, Commodities, Emerging Markets and Counterparty Risk) and risk types (market, credit, counterparty).
 
About QA WCR
QA Wholesale Credit Risk develop models for capital (Basel), impairment (IAS39/37, IFRS9), and stress testing (CCAR, PRA, EBA). Model outputs are utilised across a range of risk metrics, including RWA, pricing, Economic Capital, and for credit sanctioning. The model scope covers the Corporate and Investment Bank (CIB). We are an equal opportunity employer and we are opposed to discrimination on any grounds.
 
Overall purpose of role
• Develop, document, and calibrate credit risk models in line with regulatory requirements, e.g. Basel/PRA
• Support end to end model calculation & non-statistical components of models
• Support user understanding and investigate ad hoc queries
• Enhance model management through automation and development of new approaches
 
Key Accountabilities Develop credit risk models (80%)
• Develop new credit risk models, managing the development through to final internal approval and regulatory submission
• Interpretation of regulatory modelling framework and develop models compliant to those regulations
• Validate performance of new models
• Document new models to required standards Manage stakeholders (20%)
• Work with other parts of the Bank to ensure understanding of model applications, limitations, uses and abuses
• Maintain open dialogue with other modellers and validation teams on model developments and reviews
• Address modelling queries from user community, looking at specific customer ratings and their calculation
 
Stakeholder Management and Leadership
• Good project management skills; ability to work and deliver within tight deadlines
 
Decision-making and Problem Solving
Essential
• Post graduate degree in a quantitative discipline, Mathematics, Statistics, Physics, Engineering, Econometrics
• Very strong knowledge of statistics, e.g. regression analysis, reject inference, decision trees, cluster & time-series analysis
• Strong numerical programming ability using a range of languages (R, C++, Python); working experience with SQL
• Track record of producing high quality written communication including results of research and presentations for technical and non-technical audiences
• Experience of developing & applying statistical models
 
Preferred
• PhD in a highly numerate discipline (Mathematics, Statistics, Physics, Engineering, Econometrics)
• Understanding of the quantitative techniques used in developing and validating PD, LGD, and/or EAD models
• Experience in statistical modelling and model testing
 
Risk and Control Objective
Ensure that all activities and duties are carried out in full compliance with regulatory requirements, Enterprise Wide Risk Management Framework and internal policies and Policy Standards
 
Person Specification
• Ability to quickly adapt to new environments & systems
• A keen eye for detail
• Self-starter: motivated and disciplined
• Able to work in isolation and within a team environment, as required