Credit Risk Assessment Specialist
3 weeks ago
Position Overview: Reporting directly to the Head of Credit Risk, this role is centered on the evaluation and presentation of credit risk indicators, including essential performance metrics of the retail lending portfolio. The position will also involve the creation and improvement of regular reporting and Management Information Systems (MIS) for the organization.
Key Responsibilities:
- Develop, construct, and sustain credit risk reports.
- Examine and communicate portfolio KPIs to senior management, ensuring data accuracy.
- Analyze credit risk data in relation to historical and anticipated trends to clarify key portfolio variances and performance drivers.
- Conduct portfolio analysis, monitoring, and reporting.
- Execute system User Acceptance Tests (UATs) for credit risk-related systems, focusing on reporting tools.
- Utilize advanced analytics and data visualization to support credit portfolio management and business requirements.
- Perform regular analyses of portfolio performance, including limit utilization, to identify segments for credit limit reassessment.
- Collaborate with Collections to analyze customer repayment behavior, identifying potential fraudulent applications and escalating these cases for investigation.
- Assist in developing predictive models using machine learning to enhance credit decision-making and early warning systems.
- Implement, monitor, and maintain models within production credit systems.
- Partner with data engineers to build data pipelines for integrating new data sources.
- Advance discussions on governance and assurance concerning the application of artificial intelligence and machine learning in credit risk.
- Provide analytical and statistical data to support recommendations for enhancing credit policies, scoring, segmentation, simulation techniques, and management actions.
- Contribute to test scenario development and, based on outcomes, recommend adjustments to parameter settings and policy changes.
- Engage proactively with Credit Risk Managers regarding portfolio composition, trends, and anomalies.
- Support ongoing Credit Risk enhancement initiatives, including vendor selection and system implementations.
Ideal Candidate Profile:
- Bachelor's or postgraduate degree in Data Science, Computer Science, Mathematics, or a related quantitative field.
- A minimum of three years of relevant experience in banking, preferably in a risk, business, or product role within a retail lending context; five years of experience is preferred.
- Strong familiarity with the retail lending market and regulatory landscape.
- Proficient in the MS Office suite or equivalent; familiarity with Google Workspace is advantageous.
- Experience with machine learning frameworks, Python, and SQL is preferred.
- Ability to deliver high-quality analysis using both structured and unstructured data.
- A collaborative team player with strong problem-solving skills, effective communication, and stakeholder management abilities.
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