Fraud & Data Analyst at Eazzy Tranzact

Job Summary

• We are seeking a detail-oriented and analytical Fraud & Data Analyst to join our Risk Management team.
• The primary responsibility of this role is to identify, investigate, and mitigate fraudulent activities while leveraging data analysis to provide actionable insights.

Roles and Responsibilities

• Monitor and analyze transactions to detect suspicious activities and patterns indicative of fraud.
• Develop and implement fraud detection rules, models, and strategies.
• Investigate fraudulent activities, gather evidence, and take appropriate actions to mitigate risks.
• Collaborate with the compliance and legal teams to ensure regulatory requirements are met and adhered to.
• Prepare and present detailed reports on fraud trends, case investigations, and outcomes.
• Utilize data analysis tools to extract, analyze, and interpret data related to fraud detection and prevention.
• Identify key trends and insights from data to enhance fraud detection methodologies.
• Create and maintain dashboards and reports to track fraud metrics and KPIs.
• Develop predictive models and algorithms to proactively identify potential fraud.
• Work closely with other departments such as IT, Operations, and Customer Service to implement fraud prevention measures.
• Communicate findings and recommendations to senior management and other stakeholders.
• Provide training and support to staff on fraud detection techniques and best practices.
• Liaise with external partners, financial institutions, and law enforcement agencies on fraud-related matters.
• Stay updated with the latest fraud trends, technologies, and regulatory requirements.
• Recommend and implement enhancements to fraud detection systems and processes.
• Conduct regular audits and reviews of fraud detection measures to ensure effectiveness.
• Participate in risk assessments and contribute to the development of comprehensive risk management strategies.

Job Requirements

• Master's / Bachelor’s Degree in finance, Accounting, Statistics, Computer Science, or a related field. relevant certification is an added advantage.
• At least 5 years of experience in fraud detection, data analysis, or a similar role in the financial services or fintech industry.
• Proficiency in data analysis tools (e.g., SQL, Python, R), fraud detection software, and data visualization tools (e.g., Tableau, Power BI).
• Strong analytical and problem-solving skills with the ability to interpret complex data sets.
• Excellent written and verbal communication skills, with the ability to present findings clearly and concisely.
• High level of attention to detail and accuracy in all aspects of work.
• Strong sense of ethics and integrity in handling sensitive and confidential information.

Key Competencies:

• In-depth understanding of fraud schemes, detection methods, and prevention strategies.
• Proficient in data mining, statistical analysis, and predictive modeling.
• Ability to think critically and make data-driven decisions.
• Strong ability to work collaboratively with cross-functional teams and external partners.
• Commitment to staying current with industry trends, best practices, and technological advancements.