Divisional Head : Data Science & Credit Analytics

Divisional Head: Data Science & Credit Analytics

Responsible for the review and approval of Consumer Banking credit proposals in accordance with the Bank's risk appetite, maintaining a balance between returns and risk exposure aligned with the broader Excelerate25 strategic objectives.

Lead the Data Analytics and Credit teams to drive business performance using existing and new data sources and techniques. Role Responsibilities:

1. Lead and coordinate the formulation, aggregation, and cascading of the Risk Appetite for Credit Risk, including approval governance for Consumer Banking.
2. Monitor, report, and oversee remediation of breaches.
3. Develop methodologies for measuring Credit Portfolio Management within Consumer Banking, leveraging models and processes defined by Group Risk.
4. Evaluate credit portfolio trends and conduct detailed analyses to optimize credit risk calculations, ensuring compliance with credit granting mandates.
5. Provide requirements and design inputs for credit risk recognition, measurement, and reporting for projects like Credit Management System and IFRS 9 impairment.
6. Lead a team of credit approvers to ensure high credit quality using various assessment tools.
7. Oversee loan impairments and compliance with IFRS 9 requirements.
8. Enhance the Credit Measurement Framework, including rating models (PD) and LGD/EAD measurement in collaboration with Group Risk.
9. Develop and improve Credit Reporting & Monitoring frameworks to meet stakeholder requirements.
10. Ensure timely and accurate Credit Risk reporting.
11. Support the Chief Risk Officer in Board Risk Committee responsibilities, including preparing information packs and responding to data requests.
12. Partner with the CRO to review and enhance Group Credit Policies & Standards, ensuring they reflect best practices and regulate risk assets.
13. Advise the business on risk appetite, tolerance levels, and regulatory compliance to support sound decision-making.

Leadership & Direction:

1. Lead Data Science and Credit Analytics services within Consumer Banking, fostering a collaborative and accountable culture.
2. Implement strategies, plans, and policies aligned with international best practices and group requirements.
3. Drive evaluation of credit functions focusing on rating, risk, and portfolio management to optimize decision-making and minimize costs.
4. Monitor model performance to ensure alignment with risk appetite.
5. Oversee credit activities including granting, management, analytics, and collections.
6. Review and ensure compliance with credit frameworks and policies.
7. Collaborate on audit findings and implement credit control measures.
8. Maintain current credit risk systems like Moody's Risk Analyst, FERMAT GEM, and ACAS.
9. Negotiate and coordinate efforts across the business to achieve outcomes.
10. Stay informed on SARB and Basel credit risk regulations and advise accordingly.

Credit Committee Management:

1. Schedule and facilitate credit committee meetings.
2. Prepare agendas, review minutes, and follow up on actions.
3. Manage credit pack submissions and monitor risk indicators.
4. Provide ad hoc analysis and investigate credit quality issues.

Data, Insights & Reporting:

1. Leverage data to diagnose issues and identify improvement opportunities.
2. Provide insights and trend analyses to leadership.
3. Monitor credit management dashboards and interpret metrics.
4. Ensure the stability of credit analytical platforms and respond to regulatory queries.
5. Evaluate and report on the performance of credit management functions.
6. Develop effective reporting processes aligned with legal and regulatory standards.

Data Science Capabilities:

1. Lead Data Science initiatives to meet strategic objectives.
2. Collaborate with stakeholders and ensure ongoing development of data scientists.
3. Enable a suitable environment for modeling and solutions development.
4. Develop standards, best practices, and policies for data science.
5. Leverage internal and external data partnerships.
6. Iterate solutions using pilots and prototypes.
7. Collaborate with IT on architecture and implementation.
8. Obtain sign-off from relevant committees for models and solutions.

Policies, Processes, and Procedures:

1. Partner with relevant teams to develop and enforce credit policies and procedures.
2. Identify improvement areas and review policies to align with bank objectives.
3. Ensure compliance with all regulations and internal policies.

Role Requirements:

• 10+ years in financial services with expertise in data science and credit risk analysis.
• Deep specialist experience in credit products, risk analysis, and data science.
• Senior leadership level.
• Full-time employment.
• Roles span Banking, Data Infrastructure, Analytics, and Financial Services.