Senior Data Analyst (Fraud) at Kuda Bank

About the Role

• We are seeking a highly skilled and detail-oriented Fraud Analyst to join our dynamic Fraud Team.
• In this role, you will play a key part in managing fraud queries, proactively preventing fraud incidents, and ensuring the security of our customers' finances.

Key Responsibilities

• Identifying and investigating cases of fraud across our various channels.
• Analyze data and information to provide insights and recommendations.
• Implementing measures to mitigate fraud risks and prevent fraudulent activities.
• Conducting Fraud risk assessment on products and services.
• Fraud data analytics to identify current trends, patterns and threats.
• Monitoring all electronic transactions to detect suspicious patterns.
• Handling escalations and providing timely resolutions to fraud-related issues.
• Collaborating with internal stakeholders to identify trends and implement control measures.
• Providing investigative findings on reported fraud cases to customers.
• Perform other duties as required.
• Compiling and presenting detailed reports on identified fraud cases, including the methods used, the impact, and the recommended preventive measures.

Requirements

• Bachelor's Degree in a relevant field.
• Minimum of 4 years of experience in fraud analysis or a similar role.
• Strong analytical and problem-solving skills.
• Excellent attention to detail and ability to work with large volumes of data.
• Intermediate to advanced SQL (an advantage).
• Strong analytical and problem-solving skills.
• Experience working in a fintech or other fast paced environment.
• Proficient in Monitoring systems and rules tuning.
• Knowledge of fraud prevention techniques and technologies.
• Proficiency in using fraud detection tools and software
• Good communication skills and ability to collaborate effectively with cross-functional teams.
• Ability to work in a fast-paced environment and handle multiple priorities.
• Proficiency in SQL for querying databases and extracting data for analysis.
• Advanced skills in data analysis and the ability to use these skills to identify patterns and anomalies that may indicate fraud.