Card Fraud Prevention Analyst: Data-Driven Defenses

Wise Payments; Singapore; On-site; SGD 70,000 - 120,000; Full time

Job summary

Wise is building an entirely new network for the world’s money, and this Card Fraud Prevention Analyst role helps protect Wise customers by analyzing fraud patterns, developing prevention strategies, and supporting ongoing improvements to detection capabilities.

You will combine data analysis, fraud knowledge, and technical skills to identify opportunities, build and monitor rules, and communicate insights to stakeholders across Product, Engineering, and Data Science teams.

Qualifications

• Fluent written and spoken English with strong communication skills.
• Ability to work independently while collaborating with others.
• Comfortable making data-driven decisions and prioritising tasks.
• Hands-on experience with SQL or similar querying language and large datasets.
• Experience in fraud, FinCrime, risk, analytics, or prevention strategies.

Responsibilities

• Analyse card fraud dispute trends and identify prevention opportunities.
• Develop, test, and implement fraud prevention rules with monitoring.
• Optimise rules to reduce losses while preserving customer experience.
• Monitor KPI performance and improve rule precision and recall.
• Collaborate with Product and Engineering to improve fraud tooling and customer journey.
• Provide data and recommendations during incidents and communicate findings to stakeholders.
• Stay updated on fraud trends from schemes, regulators and industry sources.

Skills

SQL

Python

Fraud analytics

Attention to detail

Independent worker

Data-driven

FinCrime experience

Multitasking

Tools

SQL

Python

Job description

Wise is building an entirely new network for the world’s money, and this Card Fraud Prevention Analyst role helps protect Wise customers by analyzing fraud patterns, developing prevention strategies, and supporting ongoing improvements to detection capabilities.

You will combine data analysis, fraud knowledge, and technical skills to identify opportunities, build and monitor rules, and communicate insights to stakeholders across Product, Engineering, and Data Science teams.