Job Summary:
The CRM Department Head is tasked to develop and implement policies, procedures and strategies of the Credit Risk Management function in line with organizational objectives, regulatory requirements and industry best practices in order to minimize the risk of default and ensure a high-quality loan portfolio. The role involves the development and monitoring of risk measurement models (ex. corporate and consumer credit scorecards, ECL, stress testing), monitoring and analysis of credit exposure against established risk appetite and limits, and credit reviews to provide assessments on asset quality.
Job Description:
- Formulates and recommends policies to manage the aggregate credit risk exposure arising from the Bank's asset portfolio including commercial loans, consumer loans, credit cards, and treasury products among others.
- Develops and generates tools to measure and monitor portfolio credit risk exposures such as portfolio credit limits, credit scoring, and analyses of probabilities of default.
- Monitors and recommends adjustments to credit risk models used for business decisions.
- Assesses and monitors levels of credit risk weighted exposure used in capital management.
- Ensures accurate and timely estimation and monitoring of expected credit losses for provisioning.
- Provides recommendations to management and board committees to address any high-risk credit exposures identified from measured credit risk metrics.
- Performs an unbiased assessment of the quality of individual credits and the aggregate credit portfolio, including appropriateness of credit risk rating, classification and adequacy of allowance for loan losses.
- Manages day to day activities of credit risk personnel, including training, and mentoring.
- Ensures compliance with all relevant regulations, standards and guidelines related to credit risk management.
Qualifications:
- Graduate of either Mathematics, Statistics, Finance, Business Management or other similar courses
- At least 7 years of experience in credit risk management (including quantitative risk analysis, risk modelling, and credit evaluation)
- Experience using statistical software like Knyme, R and Python programming is a plus
