Modelling Risk Analyst

About Discovery 

Discovery’s core purpose is to make people healthier and to enhance and protect their lives. We seek out and invest in exceptional individuals who understand and support our core purpose, and whose own values align with those of Discovery. Our fast-paced and dynamic environment enables smart, self-driven people to be their best. As global thought leaders, Discovery is passionate about innovating in order to not only achieve financial success, but to ignite positive and meaningful change within our society. 

About Discovery Bank 

Discovery Bank is a bank like no other – a shared-value bank, designed with our clients in mind. We’re all about sharing the value that clients create when they manage their money well, back with them through exceptional interest rates and rewards. Our Vitality Money programme measures how well clients manage their finances, informs them of what it means to be financially healthy, and empowers them with the knowledge to get enhanced rewards for managing their money well. If you’re adaptable, a problem-solver, always questioning the way things are done, passionate about doing what is right, and obsessed with providing a quality service experience, we have a job for you where you can be your best in an environment that’s safe and nurturing. 

Job Purpose

Discovery Bank has developed a broad range of models supporting its business and decision-making processes. These include its business case evaluation and enterprise valuation model, credit management (customer scoring, loan behaviour models, underwriting, impairment calculations), product pricing (including membership, rewards and Vitality Money), the valuing of exposures, financial instruments and positions, and various risk measurement models (e.g. interest rate risk)

The Model Risk Analyst is responsible for ensuring the potential loss to the Bank introduced by these models is minimised and is within its risk appetite and tolerance levels.

Some key risks related to models and algorithms include Improper estimation of parameters, invalid assumptions, poor data quality, inappropriate logic, poor model implementation and documentation.

Key outcomes may include but are not limited to:

• Key driver in the development, roll out and operationalization of the Bank’s Model Risk Management strategy, policy and frameworks; and their continuous enhancement. Successful implementation of these will improve the Bank’s ability to identify models that are not fit for purpose, consider and prioritise model development and enhancements requirements, while ensuring appropriate governance is maintained.
• Custodian of the key aspects of Model Risk: Inventory Management; Risk Assessment, Development, Implementation and Validation; Governance including document control and reporting.
• Provide assurance on the following aspects of robust model development and usage:
• Design (including data quality, traceability and preparation),
• Build (including assumptions, methodology and parameters and the usage of statistical techniques, the fitness of the model),
• Implementation and Documentation
• Usage (ongoing monitoring of the model and analysis of the outcomes)
• Sensitivity reviews, Scenario analysis and Stress Testing
• Embed the appropriates structures and control mechanisms to ensure that the models are able to consistently generate accurate, consistent and predictable results, thereby mitigating the risk of model error.
• Perform and report the results of model validation for new/rebuilt models to the Model Risk Committee and other relevant governance committees for approval.
• Create the model development and documentation standards for business in line with the Model Risk Management Framework.
• Manage the various risks through the model lifecycle.
• Stay abreast of developments in banking model development and prudential reporting practices.
• Conducting research on statistical/modelling techniques, advancements and potential enhancements to existing models.

Work Experience
 

• Interest in banking model development and validation (preferably retail and treasury). A minimum of 1 year's relevant experience in the South African banking sector would be advantageous.

Education / Qualifications / Accreditations with Professional Body

• Bachelor’s degree in mathematical, statistical or quantitative fields - e.g., financial mathematics, actuarial science, statistics, data science, etc. (or engineering).
• Honours degree is preferred
  
  

Technical Skills or Knowledge
 

• SQL or other data management tools certified/qualified to an advanced level.  Programming using Python/VBA/SAS or similar
• Highly analytical and strong quantitative skills
• Able to cope with the pressure, setbacks and the fluid nature of a start-up business
• Proficient in Microsoft products, particularly PowerPoint, Word, Excel.
• Ability to structure, manipulate and interpret large volumes of data (both structured and unstructured)
• Highly detail-oriented with the ability to shift between strategic and tactical approaches
• High levels of initiative and self-motivation
• Presentation skills, including proposal/recommendations document preparation experience
• Project management abilities

EMPLOYMENT EQUITY   
                             
The Company’s approved Employment Equity Plan and Targets will be considered as part of the recruitment process. As an Equal Opportunities employer, we actively encourage and welcome people with various disabilities to apply.