Snr Fraud Risk Analyst
Cape Town – Western Cape
PROVIDE crucial information and analytical support for the effective monitoring and control of risk exposure across a suite of consumer lending portfolios of a dynamic Financial Service Group seeking your expertise as a Snr Fraud Risk Analyst. You will be expected to provide ongoing analysis to understand efficacy of current rule sets, to make changes to current rules sets and to suggest new rules which would typically involve input from multiple business areas including the Fraud Department. The successful incumbent must possess a Bachelor’s tertiary qualification in Commerce/Science/Humanities with a focus on Stats/IT/Economics/Math or similar with 2 years’ experience in Credit Risk analysis on lending products, data manipulation and analysis using SAS, SAL or other Data Analysis tools and compiling reports based on information retrieved and analysed.
- Ongoing analysis to understand efficacy of current rule sets, to make changes to current rules sets and to suggest new rules which would typically involve input from multiple business areas including the Fraud Department.
- Ad hoc analyses to help understand and mitigate fraud events.
- Manage the transition from using fraud rules to using fraud scores. This could involve utilising Decision Science or a third party, depending on scope of work.
- Work closely with Fraud Department and ensure that the Risk and Fraud Department are always aligned on any rule or fraud-tool changes.
- Engage with the wider business to present analyses so as to give reassurance that the fraud tools are being effectively utilised to mitigate fraud.
- A Bachelor’s qualification in Commerce, Science, or Humanities with a focus on Statistics, IT, Economics, Mathematics, or similar is essential.
At least 2 years’ experience in the following is essential:
- Credit risk analysis on lending products.
- Data manipulation and analysis using SAS, SQL or other Data Analysis tools.
- Compilation of reports based on information retrieved and analysed.
- Fraud experience is advantageous.
- Business acumen.
- Strong analytical and problem-solving skills.
- Strong ability to interpret data and communicate this to influence key stakeholders.
- Good planning and organisation skills.
- Ability to manage deadlines and expectations.
- Expert attention to detail.
- Quality control of output data.