Credit Analyst Impairments & Analytics job at Absa Bank

Background information about the job or company (e.g., role context, company overview)

Empowering Africa’s tomorrow, together…one story at a time.

With over 100 years of rich history and strongly positioned as a local bank with regional and international expertise, a career with our family offers the opportunity to be part of this exciting growth journey, to reset our future and shape our destiny as a proudly African group.

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Job Summary

To deliver accurate Retail impairment forecasts and develop robust models and analytics that support scenario analysis, stress testing, and data-driven decision-making for the Retail business.

Responsibilities or duties

Contract Type: Fixed-term (8 months)

Key Accountabilities

Impairment, Provisioning and Modeling (80%)

Impairment and Provisioning. Involves the delivery of accurate projections of the Bank's Retail Impairment provision and the development of robust econometric.

Impairment Review & Update-IFRS 9 & FIA. Perform impairment calculation on the portfolio.

Collect relevant customer data from bank’s internal MI systems in order to run the impairment & provisioning models.

Communicate impairment & analytic results to both technical and non-technical audiences, using Microsoft Excel worksheets and PowerPoint presentations

Understanding business questions and formulating data analysis and modeling problems.

Prototyping data-driven predictive models and data analysis models.

Support the Retail Credit team by providing relevant and timely analysis for current projects and ad-hoc queries.

Data Analysis, Forecasting and Modeling of Portfolio Performance Statistics (20%)

Analyse and interpret both Performance and Applications data relating to Credit Risk processes

Provide analysis to support with business-as-usual activities such as Credit Risk strategy changes

Continuously strive to improve Absa decision support systems

Qualifications or requirements (e.g., education, skills)

Preferred Education

Bachelor’s degree in Quantitative or Mathematical Economics, Statistics, Data Analytics and Analytical Finance or a related field from an accredited University

Preferred Experience

3 – 5 years working experience in a similar role preferably in a financial institution.

Knowledge

Strong IFRS knowledge and strong experience in econometric modeling or risk forecasting

Experience in performing data analysis utilizing a standard statistical package such as SAS;

High level of modeling in MS Excel, ideally with experience in manipulating large data sets

Strong knowledge of portfolio dynamics and Credit Risk and credit portfolio life cycle dynamics.

Understanding of portfolio and sub-portfolio modelling practices and model performance measures.

Proven knowledge of analysing and interpreting data using statistical models and manipulating data using relevant programmes such as SAS/SQL.

Skills:

Strong communication skills and the ability to communicate complex concepts effectively at all levels.

A self-motivating team player who is able to define structure and prioritize work in order to complete assigned tasks on schedule in a timely and cost effective manner

Passionate about data analysis and how this contributes to the business

Ability to assimilate new information and quickly adapt to a new environment.

Self-starter who naturally assumes ownership of initiatives

Excellent planning & organization skills

Strong ability to view issues from a risk & control perspective

Ability to work well under pressure, working accurately with attention to detail, and meeting deadlines

Education

Higher Diplomas: Business, Commerce and Management Studies (Required)

• Delivery of accurate projections of the Bank's Retail Impairment provision and the development of robust econometric models.
• Perform impairment calculation on the portfolio.
• Collect relevant customer data from bank’s internal MI systems in order to run the impairment & provisioning models.
• Communicate impairment & analytic results to both technical and non-technical audiences, using Microsoft Excel worksheets and PowerPoint presentations.
• Understand business questions and formulating data analysis and modeling problems.
• Prototype data-driven predictive models and data analysis models.
• Support the Retail Credit team by providing relevant and timely analysis for current projects and ad-hoc queries.
• Analyse and interpret both Performance and Applications data relating to Credit Risk processes.
• Provide analysis to support with business-as-usual activities such as Credit Risk strategy changes.
• Continuously strive to improve Absa decision support systems.

• Strong communication skills and the ability to communicate complex concepts effectively at all levels.
• A self-motivating team player who is able to define structure and prioritize work in order to complete assigned tasks on schedule in a timely and cost effective manner.
• Passionate about data analysis and how this contributes to the business.
• Ability to assimilate new information and quickly adapt to a new environment.
• Self-starter who naturally assumes ownership of initiatives.
• Excellent planning & organization skills.
• Strong ability to view issues from a risk & control perspective.
• Ability to work well under pressure, working accurately with attention to detail, and meeting deadlines.

• Bachelor’s degree in Quantitative or Mathematical Economics, Statistics, Data Analytics and Analytical Finance or a related field from an accredited University.
• Strong IFRS knowledge and strong experience in econometric modeling or risk forecasting.
• Experience in performing data analysis utilizing a standard statistical package such as SAS.
• High level of modeling in MS Excel, ideally with experience in manipulating large data sets.
• Strong knowledge of portfolio dynamics and Credit Risk and credit portfolio life cycle dynamics.
• Understanding of portfolio and sub-portfolio modelling practices and model performance measures.
• Proven knowledge of analysing and interpreting data using statistical models and manipulating data using relevant programmes such as SAS/SQL.
• Higher Diplomas: Business, Commerce and Management Studies (Required).