Senior Associate - Credit Risk Modelling (Consulting)

We help clients meet the increasing demands of regulators, shareholders and other stakeholders to ensure robust and reliable approaches to governance, risk management and compliance with regulations. We provide a full suite of governance, risk management and compliance services covering the assessment, design and implementation of governance, risk management, compliance and internal control frameworks, performing board effectiveness assessments, risk assessments, development of risk appetite, tolerances and early warning systems to internal audit department evaluations and set-up and outsource internal audits.

We are currently seeking for Senior Associate based in Ho Chi Minh office with the details of the vacancy below:

Key Responsibilities:

• Develop and enhance Probability of Default (PD), Loss Given Default (LGD), and Exposure At Default (EAD) models in accordance with Basel or IFRS 9 standards.

• Conduct thorough validation of model performance, including PD, LGD, and EAD models, and carry out portfolio stress testing to assess model robustness against adverse economic conditions.

• Generate, analyse, and standardise portfolio risk and capital reports, including scorecard performance reports and booking profiles. Provide insightful credit risk advice to senior management, regulators, and other key stakeholders.

• Analyse and evaluate product and credit programmes by reviewing and estimating risk parameters, assessing product pricing and structure, and ensuring compliance with regulatory requirements.

• Develop, review, and maintain comprehensive Basel II credit risk-related documentation, policies, and procedures to ensure a robust governance framework.

• Implement Basel/IFRS9 models, manage the scoring and capital computation engines, oversee the analytics datamart, conduct User Acceptance Testing (UAT), and support the overall deployment of models.

• Undertake advanced data analysis and modelling to support business decision-making, leveraging techniques including statistical analysis, machine learning, and predictive modelling.

• Develop and maintain robust dashboard that facilitate timely and accurate insights for stakeholders, enabling data-driven strategies to enhance business performance.

• Stay abreast of emerging technologies, including cloud computing and Generative AI (GenAI), and explore their potential applications within the organization to optimize operations and drive innovation in risk management practices.

• Conduct training sessions for team members and stakeholders, ensuring a thorough understanding of models and methodologies, while also engaging in research and development of new models and applications.

Requirements:

• Graduate degree in a quantitative programme, such as Statistics, Mathematics, Actuarial Science, Financial Engineering, etc. Business, Finance and Economics degrees with a strong quantitative focus and highly relevant working experience will be considered. Econometric focus and analysis will be considered as a strong positive. Post graduate degree is an added advantage.

• More than 3 years of working experience in credit risk modeling and management or consulting or risk vendor experiences.

• Experience for models’ development and/or validation for both Corporate and Retail will be an added advantage.

• Having FRM or CFA is a plus.

• Strong PC skills: Python, R …; SQL query and database familiarity; MS Office applications, including advanced spreadsheet and VBA. Knowledge of Core banking is a plus.

• Analytical mind with sound business insight, excellent communicator (verbal and written), highly meticulous, and self-motivated.

• Self-starter, flexible with a proven ability to work well in teams, as well as being able to function with minimal supervision. People management experience is a plus.

• Enable the candidate to be a credible counterpart to business managers and senior management, and the ability to develop on-going ‘trusted advisor’ relationships based on the ability to understand, analyse, discuss and address key business challenges raised.