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Credit Model Validation Specialist, Digital Banking

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Job Summary

  • Singapore
  • Permanent
  • BBBH840658
  • Feb 17, 2023
  • Competitive
Job Description

Morgan McKinley is working in partnership with a one of the Digital Banks with strong footprints and relationship in the Asia region.

Role and responsibilities

  • Perform pre and post-implementation validations on credit risk models and FRS 9 models in line with best-practice standards
  • Employ statistical modelling methodology in performing validations and produce outcomes to be analysed from statistical as well as business perspective
  • Work closely with model developers and provide feedback and value-added advice on the models prior to presentation for approval to Management
  • Provide and engage in challenging and value-adding discussions to model developers in order to ensure models approved are of the highest standard
  • Manage electronic data, perform data extraction from databases or write specifications for data to be extracted by the IT team
  • Aware of Regulators' (MAS) requirements for IRB models and ensure adherence
  • Present and explain validation results to the respective management committee/s for endorsement and approval
  • Conduct occasional briefing sessions to external parties on validation related matters

Key requirements

  • Possesses a quantitative qualification with at least a Degree (or its equivalent) preferably in Statistics, Mathematics, Accounting, Finance, Banking, Economics, or other related/suitable quantitative discipline from a recognized University
  • At least 5 years working experience in similar / related functions or statistical modelling related functions
  • The candidate must be mathematically inclined with familiarity with statistical modelling techniques employed in modelling (for example logistic regression analysis and co-relation analysis)
  • Familiar with credit risk models used by the banks, such as Application and Behaviour scorecards for business use as well as capital models; namely Probability of Default (PD), Exposure at Default (EAD) and Loss Given Default (LGD)
  • Familiar with FRS 9 models
  • Experience in other model types such as Credit Concentration Risk and Pricing models is of added advantage
  • Highly-skilled in various Excel mathematical and data manipulation functions
  • Experience in data analysis and data manipulations using SAS software. Familiar with various database structures and proven ability to work with IT on data extraction
  • Exposure to the various types of portfolios managed by the banking group and experience in business/corporate loan origination and credit processing is an added advantage
  • Meticulous, organised and able to produce documentation of high quality, with clear and concise messaging
  • Self-assured and able to interact well with various working levels

If you are interested in the role and would like to discuss the opportunity further, please click apply now or email Hagen at for more information.

Only shortlisted candidates will be responded to, therefore if you do not receive a response within 14 days please accept this as notification that you have not been shortlisted.

Morgan McKinley Pte Ltd, EA License No: 11C5502

Lee Boon Hou (Hagen), Registration No: R1870932


Consultant Details

Consultant Details

Hagen Lee
Hagen Lee