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Fraud Prevention Forensic Analyst

1 month ago

Cape Town, South Africa Impact.com Full time

Our Company:

At impact.com we are passionate about our people, our technology, and are obsessed with customer success. Working together enables us to grow rapidly, win, and serve the largest brands in the world. We use cutting edge technology to solve real-world problems for our clients and continue to pull ahead of the pack as the leading SaaS platform for businesses to automate their partnerships and grow their revenue like never before. We have an entrepreneurial spirit and a culture where ambition and curiosity is rewarded. If you are looking to join a team where your opinion is valued, your contributions are noticed, and enjoy working with fun and talented people from all over the world, then this is the place for you

impact.com, the world’s leading partnership management platform, is transforming the way businesses manage and optimize all types of partnerships—including traditional rewards affiliates, influencers, commerce content publishers, B2B, and more. The company’s powerful, purpose-built platform makes it easy for businesses to create, manage, and scale an ecosystem of partnerships with the brands and communities that customers trust to make purchases, get information, and entertain themselves at home, at work, or on the go.

Your Role at impact.com:

The Fraud Prevention Forensic Analyst (FPFA) is responsible for supporting the Fraud and Compliance team through comprehensive data analysis, identifying fraud patterns and trends, and contributing to fraud detection strategy development across impact.com’s platforms.

Working closely with the Associate Manager, Fraud Prevention, the FPFA plays a critical role in analyzing large datasets to uncover suspicious behavior, refine fraud detection processes, and inform strategic decisions. This role requires expertise in data analysis and familiarity with fraud detection methods to contribute effectively to impact.com’s risk mitigation efforts.

What You'll Do:

Data Analysis & Pattern Recognition:

- Conduct in-depth analysis of transaction data, partner activity, and traffic sources to detect fraud patterns and trends.

- Regularly monitor platform data for irregularities, anomalies, or suspicious activity that may indicate potential fraud.

- Develop reports and dashboards to track key fraud metrics and performance indicators, providing actionable insights to the Fraud Prevention team.

Fraud Detection & Trend Analysis:

- Analyze and interpret data to identify emerging fraud trends and high-risk behaviors across digital content, partners, and traffic sources.

- Work with the Fraud Prevention team to establish key indicators for early fraud detection, using historical and real-time data.

- Present findings to the Fraud Prevention team, highlighting insights, risk areas, and recommendations to support strategic decision-making.

Collaboration & Support for Fraud Prevention Initiatives:

- Support the Associate Manager, Fraud Prevention, by providing data insights that inform team priorities, resource allocation, and fraud investigation strategies.

- Collaborate with cross-functional teams, including Technology, Compliance, and Product, to develop and refine fraud detection algorithms and tools.

- Assist in developing processes to automate fraud detection tasks, improving overall efficiency and accuracy in fraud prevention operations.

Reporting & Documentation:

- Create detailed fraud analysis reports, visualizing data and trends for monthly, quarterly, and annual reviews.

- Maintain clear documentation of data sources, methodologies, and findings for record-keeping, audits, and compliance reporting.

- Participate in continuous improvement initiatives by providing feedback on data collection, reporting tools, and fraud analysis techniques.

Ad Hoc Analysis & Support:

- Conduct ad hoc analyses to investigate specific fraud cases or support special projects as needed.

- Support fraud-related investigations by preparing data for presentations and team discussions, contributing to fraud prevention initiatives.

What You Have:

- Analytical Expertise: Proficient in data analysis, able to evaluate large datasets, detect anomalies, and interpret data to identify fraud patterns.

- Problem-Solving: Skilled in approaching complex problems analytically, developing creative solutions to address emerging fraud risks.

- Attention to Detail: High level of accuracy and detail-oriented approach in reviewing large datasets and spotting unusual behavior or trends.

- Communication Skills: Ability to effectively present data findings and insights to various stakeholders in a clear, concise manner.

- Collaboration: Works well with cross-functional teams, contributing to fraud prevention efforts and supporting team goals.

- Digital & Technical Proficiency: Familiarity with data analysis tools, fraud detection platforms, and content management systems.

Education and Experience:

- Bachelor’s degree in Data Science, Analytics, Statistics, or a related field.

- 3+ years of experience in data analysis, fraud detection, risk management, or a related field.

- Hands-on experience with data analysis tools (such as SQL, Python, etc) and visualization platforms (such as Tableau or Power BI) is preferred.

- Experience with fraud prevention tools, algorithms, or machine learning for fraud detection is advantageous.

Other Considerations:

- Hybrid Work: Flexibility to work remotely up to 3 days per week, requiring a secure and quiet workspace with a stable internet connection.

Benefits:

- Hybrid, Casual work environment

- Responsible PTO policy

- Training & Development

- Medical Aid and Provident Fund

- Restricted Stock Units

- Internet Allowance

- Fitness club fee reimbursements

- Technology stipend

impact.com is proud to be an equal opportunity workplace. All employees and applicants for employment shall be given fair treatment and equal employment opportunity regardless of their race, ethnicity or ancestry, color or caste, religion or belief, age, sex (including gender identity, gender reassignment, sexual orientation, pregnancy/maternity), national origin, weight, neurodivergence, disability, marital and civil partnership status, caregiving status, veteran status, genetic information, political affiliation, or other prohibited non-merit factors.

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