Fraud Risk Management: Data Analyst

Lesaka Technologies

Johannesburg, Gauteng

Permanent

Closing Date 03 February 2026

Job Description

Lesaka Technologies, within the Consumer Division, is looking for a Fraud Risk Management: Data Analyst to support the identification, assessment, and mitigation of fraud, AML, and operational risks across the organisation. The role applies data analytics, technical tools, and risk-based methodologies to detect anomalous behaviour, support investigations, assess control effectiveness, and drive remediation initiatives that strengthen preventative and detective controls.

Key Responsibilities

Data Analysis

  • Perform in-depth data analysis to identify fraud risks, operational anomalies, and control weaknesses.
  • Collect, integrate, and analyse data from multiple sources, including transaction systems, customer databases, and external data feeds.
  • Clean, validate, and preprocess data to ensure accuracy and reliability.
  • Assess data quality and integrity to support investigations and regulatory reporting.

Risk & Remediation

  • Apply an understanding of the fraud and operational risk lifecycle from detection to closure.
  • Conduct root cause analysis on fraud incidents, operational failures, and control breaches.
  • Develop and manage remediation plans, including actions, owners, timelines, and success measures.
  • Track remediation progress and ensure timely closure of risk issues.

Investigation & Reporting

  • Support fraud investigations with data-driven insights and evidentiary analysis.
  • Analyse transactional and behavioural data to identify suspicious activity and emerging trends.
  • Prepare clear, concise reports and dashboards for senior management, risk, and compliance stakeholders.
  • Ensure reporting meets governance and regulatory standards.

Monitoring & Surveillance

  • Design and maintain monitoring and surveillance processes to detect suspicious activity and control breaches.
  • Support near real-time monitoring capabilities.
  • Review and prioritise alerts from fraud detection systems based on risk severity.
  • Recommend improvements to alert logic, thresholds, and escalation processes.

Risk Assessment & Mitigation

  • Develop and apply risk scoring methodologies.
  • Conduct risk assessments across products, processes, and systems.
  • Recommend and implement control and process improvements.
  • Maintain the Fraud Risk Register and track remediation actions.

Dashboards & Automation

  • Design and maintain Power BI dashboards providing insight into fraud risks, investigations, and remediation progress.
  • Develop and maintain SharePoint lists and workflow automation (e.g. Power Automate).
  • Ensure dashboard accuracy, performance, and usability.

Continuous Improvement

  • Identify emerging fraud trends and operational vulnerabilities.
  • Enhance fraud detection models and analytical approaches.
  • Stay informed on industry best practices and regulatory developments.

Stakeholder Engagement

  • Work closely with Compliance, IT, Operations, and Business teams.
  • Engage with regulators, law enforcement, and external industry partners as required.

Qualifications & Experience

  • BCom in Information and Technology Management
  • Risk Management (Fraud, Operational, or Enterprise Risk)
  • Data Analytics, Data Science, or Data Visualisation
  • Informatics or Information Systems
  • Business or Applied Analytics
  • Project Management (qualification or proven delivery experience)

Experience

  • 1–2 years’ data analysis experience in fraud, risk, operations, or financial services.
  • Experience working with large datasets to identify anomalies and trends.
  • Exposure to fraud risk, operational risk, compliance, or control environments.
  • Experience supporting remediation, audits, or issue management processes.

Technical Skills

  • SQL proficiency (BigQuery or similar preferred).
  • Experience with Power BI, Looker, Tableau, or similar tools.
  • Strong understanding of data quality, lineage, and system dependencies.
  • Ability to validate data used for risk and regulatory reporting.

Behaviours

  • Strong ownership and accountability.
  • Ability to manage multiple priorities simultaneously.
  • Comfortable working in fast-paced, evolving environments.
  • Strong communication skills across technical and non-technical stakeholders.

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