Credit Analyst

BDO South Africa; Rosebank; Vor Ort; ZAR 300.000 - 420.000; Vollzeit

Zusammenfassung

BDO South Africa’s Financial Services Advisory practice invites aCredit Analyst to join the Credit Risk Solutions (CRS) team. The role focuses on quantitative credit risk modelling, model validation, data analytics and automation, with emphasis on IFRS 9 ECL reviews and credit risk model assessments.

You will work with senior credit risk specialists, audit engagement teams and client stakeholders to deliver high-quality quantitative analysis, model reporting and technical documentation, while

Qualifikationen

• Academic or practical exposure to quantitative analysis, statistical modelling, credit risk modelling or model validation.

Aufgaben

• Credit Risk Modelling and IFRS 9 ECL Reviews.
• Assist with independent reviews and reperformance of IFRS 9 ECL models across wholesale, retail and other lending portfolios.
• Support the assessment and validation of PD, LGD and EAD methodologies.
• Perform quantitative analysis of historical default data, recoveries, credit risk parameters and model outputs.
• Assist with assessing model assumptions, segmentation, calibration and performance.
• Support the review of staging, SICR criteria and forward-looking macroeconomic adjustments.
• Assist with the development, enhancement and testing of quantitative credit risk models.
• Model Validation and Quantitative Analysis: statistical analysis, benchmarking, backtesting and sensitivity testing.
• Compare model outputs against historical performance, external ratings and financial metrics.
• Identify model limitations and areas for improvement.
• Support methodology assessment and predictive performance.
• Document validation procedures and findings in working papers.
• Data Analytics, Pipeline Development and Process Automation: automation of data processing pipelines, end-to-end analytic workflows.
• Develop and maintain automated processes to improve credit risk calculations and testing procedures.
• Data quality assessments and reconciliations to ensure data reliability.
• Apply Python, R, SAS, SQL and Excel in data processing and reporting.
• Develop standardized analytical tools and reusable processes across engagements.

Tools

Python

R

SAS

SQL

Excel

Jobbeschreibung

Primary Purpose Of The Role

The

Primary Purpose Of The Role

The Credit Analyst will join BDO South Africa’s Financial Services Advisory practice within the Credit Risk Solutions (CRS) team, supporting specialist audit and advisory engagements across banks, financial institutions and corporate clients. The role will focus on quantitative credit risk modelling, model validation, data analytics and automation, with particular emphasis on supporting IFRS 9 Expected Credit Loss (ECL) reviews and the assessment of credit risk models. The Analyst will work closely with experienced credit risk specialists, audit engagement teams and client stakeholders to deliver high-quality quantitative analysis, model assessments and technical reporting, while developing practical experience in financial risk advisory, credit risk methodologies and specialist external audit support.

Key Responsibilities

• Credit Risk Modelling and IFRS 9 ECL Reviews
• Assist with independent reviews and reperformance of IFRS 9 ECL models across wholesale, retail and other lending portfolios.
• Support the assessment and validation of Probability of Default (PD), Loss Given Default (LGD) and Exposure at Default (EAD) methodologies.
• Perform quantitative analysis of historical default data, recoveries, credit risk parameters and model outputs.
• Assist with assessing model assumptions, segmentation, calibration and performance.
• Support the review of staging, Significant Increase in Credit Risk (SICR) criteria and forward-looking macroeconomic adjustments.
• Assist with the development, enhancement and testing of quantitative credit risk models.
• Model Validation and Quantitative Analysis
• Perform statistical analysis, model benchmarking, backtesting and sensitivity testing.
• Compare model outputs against historical performance, external credit ratings, financial metrics and other relevant benchmarks.
• Assist in identifying model limitations, inconsistencies and potential areas for improvement.
• Support the assessment of model methodologies, assumptions and predictive performance.
• Perform gap analysis and root-cause investigations to explain differences in model results.
• Document validation procedures, analytical findings and conclusions in structured working papers.
• Data Analytics, Pipeline Development and Process Automation
• Assist with the development, maintenance and enhancement of automated data processing pipelines supporting IFRS 9 ECL reviews, credit risk modelling and model validation engagements.
• Support the design and implementation of end-to-end analytical workflows, including data extraction, transformation, cleansing, validation, model execution and reporting.
• Develop and maintain automated processes to improve the efficiency, accuracy and consistency of credit risk calculations and testing procedures.
• Perform data quality assessments, completeness checks and reconciliations to ensure the reliability of financial and credit risk information.
• Apply Python, R, SAS, SQL and Excel to support data processing, model testing, workflow automation and analytical reporting.
• Support the development of standardised analytical tools and reusable processes across engagements.
• Identify opportunities to streamline existing procedures, reduce manual intervention and improve the scalability of analytical solutions.
• Dashboard Development and Management Reporting
• Assist with the development and maintenance of interactive dashboards and management information reports for credit risk analysis and monitoring.
• Develop visualisations to communicate credit risk exposures, ECL movements, model performance and key risk indicators.
• Support the integration of analytical outputs into automated reporting templates and dashboards.
• Assist with the development of portfolio-level reporting and analytical summaries to support risk assessments and management decision-making.
• Ensure dashboards and reports are accurate, clearly presented and supported by appropriate data validation and reconciliation procedures.
• Explore opportunities to enhance reporting efficiency through automation and data visualisation tools.
• Financial Risk Advisory and Valuations
• Assist with quantitative credit risk assessments for financial institutions and corporate counterparties.
• Support the analysis of financial statements, external credit ratings, borrower risk characteristics.
• Assist with financial instrument valuations, including debt instruments and financial guarantees.
• Support credit risk assessments relating to impairment, pricing and other financial risk matters.
• Contribute to research on credit risk methodologies, regulatory developments and industry practices.
• Audit Support and Engagement Delivery
• Support the CRS team in delivering specialist external audit and advisory engagements.
• Perform independent recalculations, quantitative testing and analytical procedures over credit risk models.
• Prepare clear, accurate and well-supported working papers in accordance with BDO methodology.
• Assist with identifying, investigating and documenting model differences and technical findings.
• Support the preparation of technical reports, presentations and client deliverables.
• Work collaboratively with engagement teams to meet agreed timelines and quality standards.
• Stakeholder Engagement and Professional Development
• Engage with internal teams and client stakeholders to obtain information and clarify analytical matters.
• Communicate technical observations, analytical results and findings clearly and professionally.
• Participate in technical training, research and knowledge-sharing initiatives.
• Develop an understanding of IFRS 9, IFRS 13, Basel regulatory requirements and relevant credit risk frameworks.
• Continuously enhance technical, programming, quantitative modelling and analytical capabilities.

Experience

Minimum requirements:

• No prior full-time professional experience is required.
• Relevant exposure gained through academic research, postgraduate coursework, internships or industry-sponsored projects will be considered.
• Academic or practical exposure to quantitative analysis, statistical modelling, credit risk modelling or model validation.
• Experience using financial or other complex datasets and at least one relevant analytical tool, such as Python, R, SAS, SQL or advanced Excel.

Advantageous

• Exposure to Probability of Default modelling, IFRS 9 ECL methodologies or other credit risk applications.
• Exposure to model benchmarking, backtesting, sensitivity analysis or automated validation processes.
• Experience with data processing, pipeline development, workflow automation or dashboard reporting.
• Demonstrated ability to apply quantitative techniques to practical financial or business problems.

Technical Knowledge and Frameworks

• Foundational understanding of credit risk measurement and modelling.
• Knowledge of statistical modelling techniques, including regression analysis and predictive modelling.
• Understanding of model validation, calibration, benchmarking and performance testing.
• Basic awareness of IFRS 9 ECL principles, including PD, LGD and EAD.
• Familiarity with data processing, ETL pipelines, workflow automation and analytical reporting.
• Understanding of data quality controls, reconciliation procedures and reproducible analytical processes.
• Awareness of Basel credit risk frameworks and financial instrument valuation concepts would be advantageous.

Core Competencies

• Quantitative and analytical reasoning.
• Statistical modelling and problem-solving.
• Credit risk modelling and validation.
• Data analysis and interpretation.
• Data pipeline development and process automation.
• Dashboard development and analytical reporting.
• Research and investigative skills.
• Technical accuracy and attention to detail.
• Effective written and verbal communication.
• Teamwork and collaboration.
• Adaptability and continuous professional development.
• Commitment to delivering high-quality client service.

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