Operational Risk Analyst ORM at NCBA Group

Job Purpose Statement

• The role of the Risk Analyst is to analyze risk data that is collected from various sources, including risk registers, incident reports, and audit findings and be capable of using analytical tools to identify trends and patterns in the data to assess the overall risk landscape.
• The position also requires working with various cross functional LDFS units and Group Governance Units to proactively identify gaps in the current ecosystems, business units and processes, and advice Operational Risk-mitigating controls based on best practice. The analyst will be responsible for the development and management of mitigating controls for various digital financial services initiatives and monitoring the fraud alerts generated.
• The role entails Conducting comprehensive risk assessments across multiple business areas, using a variety of risk assessment techniques and tools and sharing timely reports for consumption of the various cross functional stakeholders.
• The role of the Operational Risk Analyst as well doubles to the review of all operational processes and systems on a day to day basis, identify and monitor high risk accounts and high-risk transactions through the Risk Management platforms and processes. The Risk Analyst will help to protect LDFS from risk events that lead to operational losses. He/she will be responsible for monitoring suspicious account activity by performing data analysis and detecting fraud trends and activities by conducting fraud investigations.

Ideal Job Specifications
 Academic:

• University degree preferably in Actuarial Science, Statistics, Economics, Finance or Business Administration or related fields.
• Proficiency and Practical experience in data analytics and use of relevant MIS, BI & MS Office applications and statistical computer languages e.g. SQL, R, Python.
• Strong IT skills and experience with office automation tools

Professional:

• Strong financial modelling, analytical and problem solving skills with an emphasis on data science and risk management.
• Experience working with and ideation and creation of data architectures.
• Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks.
• Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.) and experience with applications.
• Excellent written and verbal communication skills for coordinating cross functional teams.
• A drive to learn and master new technologies and techniques.
• Interpersonal skills to effectively communicate with and manage expectations of internal customers and other stakeholders who impact performance.
• Proficiency in ISO 9001 2015 is highly desired in regards to Quality Management System.
• Decisive and solution focused. Possess strong analytical skills with the ability to collect, organize and analyze significant amount of information with attention to detail and accuracy.
• Demonstrated ability to synergize, prioritize and drive results with a sense of urgency
• Self-motivated with a strong inquisitive mindset and quest for learning
• Self-empowerment to enable development of open communication, teamwork and trust that are needed to support true performance and customer-obsessed oriented culture.

Desired work experience:

• 5 years banking experience with at least 2 years covering Operational risk management
• Experience with risk management and reporting in a highly automated environment with large data analytics.