Fraud Analyst
Boku
Boku Inc. (BOKU.L) is the leading global provider of local mobile-first payments solutions. Global brands including Amazon, DAZN, Meta, Google, Microsoft, Netflix, Sony, Spotify, and Tencent rely on Boku to reach millions of new paying consumers who do not use credit cards with our purpose-built payment network of more than 300 local payment methods across 70+ countries. Every year, Boku processes over $10 billion in value for our customers. Incorporated in 2008, Boku is headquartered in London and San Francisco and has employees in over 39 countries around the world, including Brazil, China, Estonia, Germany, Ireland, Japan, Singapore, and the UAE. Boku is a truly global company that takes pride in its diversity and thriving equal opportunity workplace.
Role Purpose
As part of the Fraud team, the Fraud Analyst plays a vital role in safeguarding our merchants, partners, and platform from financial crime and abuse. This role involves monitoring transaction patterns, identifying unusual or suspicious activity, and conducting detailed investigations to detect and respond to fraud across our global payments network.
As part of a collaborative and agile team, the Fraud Analyst will work closely with cross-functional teams including Account Management, Compliance and Operations. The role offers the opportunity to grow expertise in digital payments fraud, contribute to key decision-making processes, and directly influence the company’s mission to enable safe, seamless, and trusted Local Payment Methods worldwide.
Key Responsibilities
Understand the business product and strategy and how this will impact fraud prevention. With the tools available we need you to:
- Prepare datasets for use in fraud analysis
- Use SQL analysis and data visualization to answer important business questions
- Monitor the performance of our risk engine system by configuring and optimising fraud rules.
- Proactively anticipate and manage emerging fraud by distinguishing between normal and suspicious activity
- Spot patterns and trends in fraud
- Be a first responder to our alerting processes
- Be ready to escalate any emerging fraud issues or anomalies
Work with stakeholders to get visibility into projects that may influence fraud risk. Our business is constantly changing. Our competitors are adapting and we need to stay ahead of the game. We need you to:
- Work with the team so that you understand what we can deliver
- Understand the different and constantly evolving fraud challenges that Boku and our partners face. Act as a source of information for other parts of the business
- Work with account managers to help meet our merchant and carrier partners’ needs for fraud prevention.
- Explain technical or analytical working to non-technical audiences in clear, concise language.
- Contribute ideas, cultivate ideas you hear, take guidance to drive good ideas forward: be that person that makes new things happen.
- Travel as necessary to Estonia, London, San Francisco, and possibly other locations if required.
Key Skills, experience and Competencies
- 2 to 3 years of relevant experience
- SQL Analysis - Proven experience using SQL (build, execute and troubleshoot queries) for data analysis in a working environment to answer business questions.
- Critical thinking – Ability to deconstruct data and information into smaller pieces and categories to draw conclusions.
- Attention to detail – thorough and accurate when completing tasks, no matter how big or small.
- Experience and a comprehensive understanding of fraud challenges within the payments industry.
- Excellent communication skills, with the confidence to present your knowledge and answers to a wide variety of internal and external stakeholders.
- Individual contributor – brings a proactive, can-do attitude and genuine enthusiasm for getting involved and driving projects forward.
- Growth-mindset and willingness to learn new skills.
- Experience with additional data analytics or data science technologies beneficial.
Qualifications (if required)
- Bachelor’s Degree (or equivalent) ideally in a numerical or analytical field.