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Open nowFirst seen 3 days ago

Fraud Reviewer

Kate Worthington706 open roles

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Share of postings closed within
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  2. 4.5%3 days
  3. 12.1%7 days
  4. 19.1%14 days
  5. 35.6%30 days
  6. 52.7%60 days
This job: first seen 3 days ago

The posting

Fraud Reviewer

Job Summary

The Fraud Reviewer is responsible for identifying and investigating suspicious transactions and abnormal user behavior to mitigate fraud risk. This role analyzes transaction data, uncovers fraud patterns, and collaborates with cross-functional teams to strengthen fraud detection systems, improve operational processes, and support data-driven business decisions.

Key Responsibilities

  • Monitor and review suspicious transactions and user activities on a daily basis to detect potential fraud.
  • Analyze transaction data and customer behavior to identify fraud trends, anomalies, and emerging risks.
  • Investigate fraud cases and provide actionable insights to improve fraud prevention strategies.
  • Collaborate with Engineering, Data Science, and Product teams to translate fraud insights into fraud detection rules, automated monitoring systems, and enhanced business processes.
  • Develop ad hoc reports, dashboards, and analytical presentations to support management decision-making.
  • Recommend process improvements and control enhancements to reduce fraud exposure and improve operational efficiency.
  • Maintain accurate documentation of investigations, findings, and fraud trends.

Qualifications

We're looking for an analytical and detail-oriented Fraud Reviewer who thrives in a fast-paced environment and is passionate about combating financial fraud.

Requirements

  • Bachelor's degree in a quantitative discipline such as Data Science, Statistics, Mathematics, Economics, Engineering, or a related field.
  • At least 1 year of experience in Fraud Review, Fraud Operations, Fraud Analytics, Risk Management, or a related role within the financial services, fintech, banking, or payments industry.
  • Experience in Mystery Shopping, Risk Audit, or Operational Risk is an advantage.
  • Strong analytical and problem-solving skills with the ability to interpret complex datasets and identify fraud patterns.
  • Solid understanding of business processes and internal controls.
  • Proficiency in SQL is required; experience with other database management tools is highly preferred.
  • Advanced proficiency in Microsoft Excel or Google Sheets; experience with Python or other programming languages for data analysis is a strong plus.
  • Comfortable working in a dynamic, fast-paced, and data-driven environment.
  • Excellent communication skills with the ability to present technical findings in clear, concise, and business-friendly language.
  • Ability to collaborate effectively with cross-functional teams including Engineering, Data Science, Product, and Operations.
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