Description
Model Development and Validation

• Develop, refine and implement credit risk models, including Probability of Default (PD), Loss Given Default (LGD) and Exposure at Default (EAD) for approval by management
• Validate and back-test models to ensure accuracy and compliance with the relevant regulatory standards e.g. IFRS 9.
• Perform stress testing and scenario analysis to assess model performance under different economic conditions and report outcome to management.

Data Analytics

• Identify trends and correlations in credit risk factors such as default rates and share output with management.
• Collaborate with the Data team to ensure quality and completeness of large data to use in the models

Model Performance Monitoring and Optimisation

• Periodically recalibrate models based on new data or shifts in economic conditions
• Leverage technology to enhance predictive accuracy where appropriate

Risk Assessment

• Analyse credit portfolio to identify high-risk segments and concentrations for management to make decisions based on the outcome of the analysis.
• Use advanced analytics tools like SAS or Python to monitor credit exposures and forecast performance
• Monitor the credit risk limits and approval risks aligned to the business objectives
• Recommend risk mitigation strategies such as adjusting credit limits or pricing model for management to consider
• Monitor credit approval exceptions and recommend process improvements
• Under the guidance of Credit and Operations Manager assist with the development and implementation of risk management strategies to mitigate identified risks.
• Conduct regular risk assessments and prepare detailed reports on findings which should be shared with the Credit and Operations Manager.
• Analyze and improve business processes to reduce risk and enhance operational efficiency.
• Develop and maintain a comprehensive record of risk management activities, including data flow diagrams and risk assessments.
• Review that the credit portfolio is well-diversified to mitigate the risk of high exposure to any single borrower, industry, or geographical area.
• Leverage technological advancements and data analytics to improve credit assessments and operational efficiencies.
• Provide input into the credit models enhancements to mitigate identified risks.
• Identify, evaluate, and monitor financial, operational, and regulatory risks.
• Assess the credit controls are aligned to business objectives and make recommendations for improvement to the Credit and operations manager.

Regulatory Compliance and Reporting

• Ensure all credit risk models meet regulatory requirements (e,g, IFRS 9).
• Prepare detailed risk reports for management.

Fraud Prevention and Mitigation

• Identify key fraud prevention mechanisms applicable to the lending and savings products.
• Implement and oversee anti-fraud measures to protect the company and its clients from fraudulent activities.
• Refer to Forensics department for investigations of suspected fraudulent activities in the operations -for appropriate action to be taken by the Forensics department.
• Give input to the Training department to educate staff on fraud identification of suspected fraudulent activities .

Stakeholder Engagement

• Build relationships with internal and external stakeholders to ensure a coordinated approach to risk management.
• Provide regular risk updates and reports to senior management and relevant stakeholders.
• Engage with internal auditors and regulatory inspectors as required.

Training and Education

• Conduct training sessions for staff on risk management best practices and regulatory compliance.
• Provide ongoing education and support to staff to foster a risk-aware culture within the organisation.

Requirements
Minimum Qualification

• Bachelor’s degree in Finance, Business, Economics, Risk Management, or related field. A postgraduate qualification in risk management or a related discipline is an advantage.
• Minimum of 3 to 5 years of experience in risk management, preferably within the financial services with micro-lending sector and/or saving and investment focus being advantageous.
• Professional certifications such as Certified Risk Management Professional (CRMP), Certified
• Information Systems Auditor (CISA), or similar are preferred.

Knowledge and Experience

• Technical expertise in credit risk models.
• Advanced analytical and statistical skills.
• Advanced analytics tools usage, like SAS or Python.
• Regulatory knowledge (IFRS 9 and Basel).
• Experience in dealing with regulatory bodies like the SARB, NCR, PA.
• Familiarity with the microfinance sector and its unique risks.
• Familiarity with investment sector highly beneficial.
• Previous experience in managing a team or leading risk management projects.
• Proficiency in MS Office and compliance management software.