Key Responsibilities

Fraud & Operational Risk Management (First Line)

• 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.

Fraud Monitoring & Detection

• 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.

Data Analytics & Technology Enablement

• 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.

Investigations & Case Management

• 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.

Remediation & Control Enhancement

• 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.

Compliance & Financial Crime

• 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.

Qualifications & Experience

Minimum Requirements

• 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.

Advantageous

• 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.

Key Competencies & Skills

Technical & Analytical

• 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.
  

Risk & Fraud Expertise

• 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.

Behavioural & Professional

• 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.