Description:
Lesaka Technologies is a leading South African fintech group providing integrated payment, lending and financial services solutions to consumers and merchants. As we continue to scale our banking and fintech capabilities, we are strengthening our first-line fraud and operational risk function to ensure our products, systems and customer journeys remain secure, resilient and compliant.We are seeking a Senior Fraud & Operational Risk Analyst to play a critical role in protecting the organisation against fraud, financial crime and operational losses. This role is embedded in the first line and is responsible for identifying, monitoring and managing fraud and operational risk exposures across products, channels, systems and processes. The successful candidate will combine strong analytical capability with practical fraud investigation experience and a deep understanding of banking or fintech environments.
Key Responsibilities
Fraud & Operational Risk Management (First Line)
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Identify, assess, and manage fraud and operational risk exposures across products, channels, systems, and processes.
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Maintain and enhance fraud risk assessments, risk and control matrices (RCMs), and fraud risk registers.
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Design, implement, and monitor preventive and detective fraud controls aligned to risk appetite.
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Act as a first-line risk partner to business, product, technology, and operations teams.
Fraud Monitoring & Detection
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Develop, manage, and optimise transaction monitoring rules, alerts, and fraud detection logic across core banking and digital platforms.
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Analyse fraud trends, typologies, root causes, and emerging risks.
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Review fraud alerts and support escalation, containment, and decision-making processes.
Data Analytics & Technology Enablement
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Use data analytics to identify anomalies, patterns, and fraud indicators.
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Write and optimise queries using SQL and support analytics using Python and/or Java.
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Contribute to the development and enhancement of AI and machine learning-based fraud models (rules-based, supervised and unsupervised).
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Partner with technology teams to enhance core banking systems, fraud engines, and monitoring platforms.
Investigations & Case Management
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Conduct and support fraud investigations, including transactional analysis, evidence gathering, and root cause analysis.
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Prepare investigation reports, loss assessments, and management summaries.
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Support recovery actions, internal disciplinary processes, and referrals to law enforcement where required.
Remediation & Control Enhancement
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Drive remediation actions following fraud incidents, control failures, audits, or regulatory reviews.
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Recommend and implement control improvements, system enhancements, and process changes.
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Track remediation actions to closure and report on effectiveness.
Compliance & Financial Crime
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Support compliance with FICA, AML/CFT, fraud, and broader financial crime regulatory requirements.
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Assist with regulatory engagements, audits, and assurance reviews.
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Ensure fraud risk frameworks align with regulatory expectations and internal policies.
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Produce regular fraud risk, losses, trends, and KPI reporting for senior management and governance forums.
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Present insights, findings, and recommendations to stakeholders across risk, compliance, operations, and technology.
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Contribute to fraud risk strategy, policies, standards, and procedures.
Qualifications & Experience
Minimum Requirements
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Bachelor’s degree in Finance, Risk Management, Accounting, Information Systems, Data Science, or related field.
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3–5 years’ experience in fraud risk management, operational risk, financial crime, or analytics within a bank or fintech.
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Hands-on experience with fraud monitoring, investigations, analytics, and remediation.
Advantageous
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Postgraduate qualification or professional certification in Risk, Fraud, AML, or Data Analytics.
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Experience with fintech platforms, digital banking, or payments.
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Exposure to regulatory engagements, audits, or assurance reviews.
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Experience implementing or enhancing AI/ML-driven fraud solutions.
Key Competencies & Skills
Technical & Analytical
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Strong fraud and operational risk management capability.
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Advanced data analysis and problem-solving skills.
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Proficiency in:
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SQL
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Python
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Google Cloud Console
-
Looker Studio
-
Power BI
-
Azure
-
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Experience with AI and machine learning concepts for fraud detection (model development, tuning, validation, or implementation).
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Strong understanding of transaction monitoring systems, fraud engines, and core banking platforms.
Risk & Fraud Expertise
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Deep understanding of fraud typologies (card fraud, digital fraud, account takeover, internal fraud, payments fraud, etc.).
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Experience designing and maintaining Risk and Control Matrices (RCMs).
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Knowledge of banking and fintech operating models, products, and payment ecosystems.
Behavioural & Professional
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Strong investigative mindset and attention to detail.
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Ability to translate technical findings into clear business insights.
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Excellent stakeholder engagement and communication skills.
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Strong ownership, accountability, and ability to work independently.
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Ability to operate in fast-paced, agile environments.
Requirements:
-
Identify, assess, and manage fraud and operational risk exposures across products, channels, systems, and processes.
-
Maintain and enhance fraud risk assessments, risk and control matrices (RCMs), and fraud risk registers.
-
Design, implement, and monitor preventive and detective fraud controls aligned to risk appetite.
-
Act as a first-line risk partner to business, product, technology, and operations teams.
-
Develop, manage, and optimise transaction monitoring rules, alerts, and fraud detection logic across core banking and digital platforms.
-
Analyse fraud trends, typologies, root causes, and emerging risks.
-
Review fraud alerts and support escalation, containment, and decision-making processes.
-
Use data analytics to identify anomalies, patterns, and fraud indicators.
-
Write and optimise queries using SQL and support analytics using Python and/or Java.
-
Contribute to the development and enhancement of AI and machine learning-based fraud models (rules-based, supervised and unsupervised).
-
Partner with technology teams to enhance core banking systems, fraud engines, and monitoring platforms.
-
Conduct and support fraud investigations, including transactional analysis, evidence gathering, and root cause analysis.
-
Prepare investigation reports, loss assessments, and management summaries.
-
Support recovery actions, internal disciplinary processes, and referrals to law enforcement where required.
-
Drive remediation actions following fraud incidents, control failures, audits, or regulatory reviews.
-
Recommend and implement control improvements, system enhancements, and process changes.
-
Track remediation actions to closure and report on effectiveness.
-
Support compliance with FICA, AML/CFT, fraud, and broader financial crime regulatory requirements.
-
Assist with regulatory engagements, audits, and assurance reviews.
-
Ensure fraud risk frameworks align with regulatory expectations and internal policies.
-
Produce regular fraud risk, losses, trends, and KPI reporting for senior management and governance forums.
-
Present insights, findings, and recommendations to stakeholders across risk, compliance, operations, and technology.
-
Contribute to fraud risk strategy, policies, standards, and procedures.
-
Bachelor’s degree in Finance, Risk Management, Accounting, Information Systems, Data Science, or related field.
-
3–5 years’ experience in fraud risk management, operational risk, financial crime, or analytics within a bank or fintech.
-
Hands-on experience with fraud monitoring, investigations, analytics, and remediation.
-
Postgraduate qualification or professional certification in Risk, Fraud, AML, or Data Analytics.
-
Experience with fintech platforms, digital banking, or payments.
-
Exposure to regulatory engagements, audits, or assurance reviews.
-
Experience implementing or enhancing AI/ML-driven fraud solutions.
-
Strong fraud and operational risk management capability.
-
Advanced data analysis and problem-solving skills.
-
Proficiency in:
-
SQL
-
Python
-
Google Cloud Console
-
Looker Studio
-
Power BI
-
Azure
-
-
Experience with AI and machine learning concepts for fraud detection (model development, tuning, validation, or implementation).
-
Strong understanding of transaction monitoring systems, fraud engines, and core banking platforms.
-
SQL
-
Python
-
Google Cloud Console
-
Looker Studio
-
Power BI
-
Azure
-
Deep understanding of fraud typologies (card fraud, digital fraud, account takeover, internal fraud, payments fraud, etc.).
-
Experience designing and maintaining Risk and Control Matrices (RCMs).
-
Knowledge of banking and fintech operating models, products, and payment ecosystems.
-
Strong investigative mindset and attention to detail.
-
Ability to translate technical findings into clear business insights.
-
Excellent stakeholder engagement and communication skills.
-
Strong ownership, accountability, and ability to work independently.
-
Ability to operate in fast-paced, agile environments.