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Fraud Analyst.FPI - MBP.Client Experience and Conduct Group-MBPKLTD
Job Purpose
- Conduct thorough post-transaction reviews of suspected fraud cases (e.g., account takeover, identity misuse)
- Analyze case-level data using basic SQL or visualization tools to identify emerging fraud trends and propose hypotheses for rule enhancements to the strategy team
- Extract, summarize, and report on key fraud metrics including loss patterns, alert volumes, and operational bottlenecks through dashboards or scheduled reports
- Maintain MIS for FP&I for the bank as per regulatory and group standards.
- Review and analyze system / data base logs of Mashreq Pakistan Systems for fraud cases.
- Prepare Daily trends of various legs including but not limited to EFM Systems, Tickets etc.
- Prepare Dashboards for EFM, ticketing systems, Transaction Monitoring to measure the associated risks.
- Deep dive into key areas for process automation.
- Analyze data for rule setting to minimize/mitigate fraud risk through effective utilization of fraud detection tools.
- Be a back up for Transaction monitoring system for fraud detection when applicable.
Key Result Areas
- Implement Dashboards for daily trends for management visibility.
- Profiling of accounts to abnormal activities for fixtures/changes in journeys/processes where applicable
- Assist in fraud prevention & detection measures to implement strategies.
Knowledge, Skills and Experience
- Bachelor 4 years, preferably in computer Science.
- Proficient in data science & machine learning.
- 01 years of experience in fraud detection, risk management, payments, or a related field (preferably in fintech, banking, or e-commerce)
- Able to write simple SQL queries or use dashboards (Power BI) to extract and interpret case-level analyses.
- Strong analytical and investigative skills with attention to detail.
- Understanding of regulatory requirements.
- Ability to think critically and work efficiently in a fast-paced, high-growth environment
- Excellent written and verbal communication skills
- Comfortable working in a fast-paced, execution-driven environment
- Conduct thorough post-transaction reviews of suspected fraud cases (e.g., account takeover, identity misuse)
- Analyze case-level data using basic SQL or visualization tools to identify emerging fraud trends and propose hypotheses for rule enhancements to the strategy team
- Extract, summarize, and report on key fraud metrics including loss patterns, alert volumes, and operational bottlenecks through dashboards or scheduled reports
- Maintain MIS for FP&I for the bank as per regulatory and group standards.
- Review and analyze system / data base logs of Mashreq Pakistan Systems for fraud cases.
- Prepare Daily trends of various legs including but not limited to EFM Systems, Tickets etc.
- Prepare Dashboards for EFM, ticketing systems, Transaction Monitoring to measure the associated risks.
- Deep dive into key areas for process automation.
- Analyze data for rule setting to minimize/mitigate fraud risk through effective utilization of fraud detection tools.
- Be a back up for Transaction monitoring system for fraud detection when applicable.
Key Result Areas
- Implement Dashboards for daily trends for management visibility.
- Profiling of accounts to abnormal activities for fixtures/changes in journeys/processes where applicable
- Assist in fraud prevention & detection measures to implement strategies.
Knowledge, Skills and Experience
- Bachelor 4 years, preferably in computer Science.
- Proficient in data science & machine learning.
- 01 years of experience in fraud detection, risk management, payments, or a related field (preferably in fintech, banking, or e-commerce)
- Able to write simple SQL queries or use dashboards (Power BI) to extract and interpret case-level analyses.
- Strong analytical and investigative skills with attention to detail.
- Understanding of regulatory requirements.
- Ability to think critically and work efficiently in a fast-paced, high-growth environment
- Excellent written and verbal communication skills
- Comfortable working in a fast-paced, execution-driven environment
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