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Senior - M&V - UK

Senior - M&V - UK

ConfidentialBengaluru / Bangalore, India
30+ days ago
Job description

Job Description

#KGS

Roles & Responsibilities

  • Model validation / audit / review primarily for one or more credit loss forecasting models in either retail or wholesale domain primarily for IFRS9 / IRB models including PD / EAD / LGD component models.
  • Validation process involves understanding of the relevant regulatory requirements, development document, testing and benchmarking as well as development of challenger models using SAS, R or Python and report writing.
  • Assist with other model validation / audit / review activities in Underwriting scorecard, Credit Scoring, behavioral models, economic scenario models or automation activities related to validation when required
  • Model validation including assessing conceptual soundness, critical assessment of the testing performed by the model developers to support the integrity and accuracy of the model implementation and its fit-for-purpose, designing to evaluate the model's predictive power and its robustness uncertainty through the development and use of alternative benchmark models and compliance assessment against the relevant regulatory standards
  • Proactively work with seniors, AM and Managers for key deliverables in line with Project requirement
  • Responsible for key deliverables and engage with Partners / Directors to understand the project scope, business requirements and work with onshore and offshore teams to do successful delivery
  • Advising non audit clients on the impact of changing requirements in provision accounting standards (IFRS9) and helping clients validate or build credit risk measurement models.

Responsibilities

Job Description

#KGS

Roles & responsibilities

  • Conduct model validation, audit, and review primarily for credit loss forecasting models in the retail or wholesale domain, specifically for IFRS9 / IRB models, including PD / EAD / LGD components.
  • The validation process includes comprehending relevant regulatory requirements, reviewing development documentation, conducting tests and benchmarking, as well as creating challenger models using SAS, R, or Python, and compiling reports.
  • Provide assistance with other model validation, audit, and review tasks as needed, such as Underwriting scorecards, Credit Scoring, behavioral models, economic scenario models, or validation-related automation activities.
  • Perform model validation by assessing conceptual soundness, critically evaluating the testing conducted by developers to ensure the model's integrity and accuracy, and determining its suitability. Design evaluations to test the model's predictive power and robustness under uncertainty, develop alternative benchmark models, and ensure compliance with regulatory standards.
  • Collaborate proactively with seniors, AMs, and Managers to meet key project deliverables.
  • Take responsibility for key deliverables, engage with Partners / Directors to comprehend project scope and business requirements, and coordinate with onshore and offshore teams for successful delivery.
  • Advise non-audit clients on the implications of evolving provision accounting standards (IFRS9) and assist them in validating or developing credit risk measurement models.
  • Qualifications

    #KGS

    Required Skills

    Educational Qualifications

  • An advanced degree in Mathematics, Statistics, Economics, or other analytical disciplines.
  • A graduate degree plus an MBA in Finance, coupled with relevant experience or exposure.
  • Additional certifications such as FRM or CFA are preferred.
  • Work Qualifications

  • Total Experience : Preferred candidates will have 2-12 years of experience in Risk Management / Analytics at major banks, top tier consulting firms like Big 4 or captives of well known banks.
  • Proficient in programming languages : Python, SAS, and R.
  • Advanced skills in statistical and quantitative modeling, including linear regression, logistic regression, ARIMA, Markov Chain, Merton Model, CHAID, and other predictive modeling techniques.
  • In-depth knowledge of regulatory requirements pertaining to model risk management, such as SR11-7, SR15-18, PRA, and EBA guidelines.
  • Skills Required

    quantitative modeling, Sas, Linear Regression, Chaid, Regulatory Requirements, Arima, Python, Logistic Regression

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