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The Junior Data Analyst (Fraud Management) supports the Fraud Management Team in monitoring, analyzing, and detecting fraudulent activities across KBZ Bank’s digital and branch operations. The role involves data extraction, reporting, and analytical support to help prevent potential fraud losses and enhance the bank’s fraud risk management framework.The Junior Data Analyst (Fraud Management) supports the Fraud Management Team in monitoring, analyzing, and detecting fraudulent activities across KBZ Bank’s digital and branch operations. The role involves data extraction, reporting, and analytical support to help prevent potential fraud losses and enhance the bank’s fraud risk management framework.

• Collect, clean, and analyze transactional and customer data to identify potential fraud patterns or anomalies.
• Support the preparation of regular fraud monitoring reports and dashboards for management review.
• Ensure accuracy, timeliness, and completeness of data used for analysis.
• Assist in tracking and monitoring real-time fraud alerts from fraud detection systems.
• Analyze flagged transactions to assess potential fraudulent activity and escalate findings to the Fraud Investigation team.
• Contribute to developing and refining fraud detection rules, models, and thresholds.
• Coordinate with relevant departments (IT, Operations, Legal, and Compliance) to obtain or validate data.
• Maintain documentation for analytical processes, data sources, and reporting templates.
• Contribute ideas to enhance fraud detection efficiency and improve data quality.
• Stay updated on new fraud trends, analytical tools, and data visualization practices.

• 2 years of experience in data analytics, banking operations, or fraud monitoring (fresh graduates with analytical skills are encouraged to apply).
• Understanding of banking operations and risk/fraud concepts preferred.
• Bachelor’s degree in Statistics, Computer Science, Information Technology, Data Analytics, Mathematics, or related fields.
• Proficiency in Excel (advanced formulas, pivot tables) and SQL for data extraction and analysis.
• Basic understanding of data visualization tools (e.g., Power BI, Tableau, or similar).