Fraud Analyst handling transaction data analysis for potential fraud patterns in retail lending. Collaborating with teams to enhance fraud prevention measures.
Responsibilities
Monitor and analyze transaction data to identify potential fraud patterns using data analytics tools and methodologies.
Conduct deep dive investigations into suspicious activities, determine root causes and develop strategies to prevent future occurrences.
Assist in development and integration of fraud detection rules and strategies on workflow systems, enhancing client’s ability to proactively identify fraud risks.
Stay updated with industry trends, regulatory changes, and best practices in fraud detection.
Collaborate with stakeholders and cross-functional teams to provide insights into global fraud trends and enhance fraud prevention measures.
Requirements
Bachelor’s degree in computer science, finance, data science, or a related field.
3+ years of strong experience in analytics, preferably in banking domain
Strong analytical skills with proficiency in Python and SQL
Ability to work in a fast-paced environment, with strong attention to detail and a proactive mindset towards problem-solving.
Excellent communication and teamwork skills to translate business requirements into analytical solutions.
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