Payment Operations Card Fraud Prevention Analyst

Wise is a global technology company, building the best way to move and manage the world’s money.
Min fees. Max ease. Full speed.

Whether people and businesses are sending money to another country, spending abroad, or making and receiving international payments, Wise is on a mission to make their lives easier and save them money.

As part of our team, you will be helping us create an entirely new network for the world's money.
For everyone, everywhere.

More about our mission and what we offer.

In your cover letter, please answer the following questions. Please note that applications without a cover letter may not be considered.

1. What drives you to take on a role in the card fraud domain?
2. How are you hoping to bring an impact in this role?

Card payments represent a large part of the funds moved through Wise every day, and card fraud disputes are an inevitable part of that. Our Card Fraud team supports Wise’s mission in a highly impactful area. We have an operational team handling Card Fraud disputes across four countries around the globe, working closely with our dedicated Engineering, Product, and Data Science teams.

As a Card Fraud Prevention Analyst, you will help protect Wise customers and reduce fraud losses by analysing fraud patterns, developing and optimising prevention strategies, and supporting initiatives that improve our fraud detection capabilities.

You’ll combine data analysis, fraud knowledge, and technical skills to identify opportunities, build and monitor fraud rules, investigate emerging fraud trends, and contribute to longer-term improvements across our prevention capabilities.

Here’s how you’ll be contributing to the Card Disputes team;

Reducing Card Fraud Loss

• Analyse Card Fraud dispute trends, independently query databases, and perform data deep dives to identify fraud patterns and prevention opportunities.

• Develop, test, and implement Card Fraud prevention rules, including rule scope validation and post-implementation monitoring.

• Optimise fraud rules to reduce fraud losses while maintaining a strong customer experience and minimising unnecessary transaction declines.

• Monitor the performance of fraud prevention strategies and identify opportunities to improve rule precision, recall, and overall effectiveness.

• Work closely with Product and Engineering teams to improve the customer experience associated with fraud declines, alerts, and controls.

• Contribute to Card Fraud prevention projects aligned with the team’s KRIs, KPIs, and OKRs.

• Provide data, analysis, and fraud prevention recommendations during incidents when required.

• Clearly communicate Card Fraud prevention strategies and analytical findings to stakeholders outside of the fraud prevention team.

Card Fraud Prevention and Risk Management

• Help protect Wise cardholders from unauthorised card usage, scams, payment instrument fraud, and account takeover fraud.

• Create and optimise Spend fraud prevention rules to reduce customer monetary loss, Spend fraud BPS, scheme-related costs, and unrecoverable fraud losses.

• Use machine learning scores and other risk signals within fraud rules to improve fraud detection performance.

• Identify emerging fraud patterns and recommend appropriate prevention strategies.

• Contribute to longer-term projects targeted at reducing Card Fraud.

• Work with Spend Product and Engineering teams to identify opportunities to improve fraud prevention tooling and the customer journey.

• Stay up to date with fraud trends highlighted by card schemes, governmental organisations, industry sources, and the media.

• Understand the trade-offs between fraud prevention, customer experience, approval rates, and product costs.

Analytics and Prevention Strategy

• Use data to identify areas of elevated fraud risk and opportunities to improve existing prevention strategies.

• Perform analytical deep dives into fraud trends, rule performance, customer impact, and emerging attack patterns.

• Monitor relevant Card Fraud KPIs and identify changes or trends requiring investigation.

• Help ensure that prevention work is aligned with the team’s OKRs, KPIs, and overall strategy.

• Identify gaps in existing Card Fraud prevention strategies and propose data-backed improvements.

• Share analysis and findings with the wider team to support prioritisation and decision-making.

• Collaborate with other analysts and stakeholders on fraud prevention initiatives and investigations.

• Contribute reusable analysis, queries, documentation, and learnings that improve the effectiveness of the wider team.

KPI and Performance Measurement

• Monitor Card Fraud prevention KPIs and performance metrics.

• Analyse changes in fraud performance and investigate underlying drivers.

• Identify problematic areas based on KPI performance and recommend appropriate actions.

• Support improvements to dashboards, reporting, and data accessibility for the Card Fraud team.

• Provide relevant data and analysis to the Card Fraud Operations team when required.

• Identify potential product issues and improvement areas through analysis of fraud and customer-impact metrics.

• Work with relevant stakeholders where additional data, tooling, or engineering changes are required.

Incident Management

• Provide relevant data and insights to stakeholders during Card Fraud incidents.

• Investigate fraud patterns during incidents and identify potential prevention gaps.

• Develop and test prevention strategies to mitigate emerging fraud risks.

• Implement or support implementation of fraud prevention rules required in response to incidents.

• Monitor the effectiveness and customer impact of prevention actions implemented during incidents.

• Escalate risks that sit outside of the Card Fraud domain or agreed risk appetite to the appropriate stakeholders.

• Support incident coordination where required.

• Your verbal and written English skills are excellent. If you speak other languages, that’s a bonus.

• You have strong attention to detail and are comfortable taking initiative.

• You are comfortable working with routine activities while adapting quickly when fraud patterns or priorities change.

• You are able to work independently while collaborating effectively with others.

• You are comfortable making decisions based on data and evidence.

• You can manage multiple priorities in a fast-moving environment.

• You have a genuine enthusiasm for the FinCrime industry and an interest in fraud prevention.

• You have hands-on experience with SQL or a similar querying language and are comfortable working with large datasets. 

• You have experience using Python for data analysis, automation, or investigative work.

• You have experience working with fraud, FinCrime, risk, analytics, or prevention strategies.

Your Analytical and Technical Abilities

• You can think through analytical problems and understand the potential impact of Card Fraud prevention rules on both the Spend product and our customers.

• You can deliver quality analysis that clearly addresses a business or risk problem.

• You are comfortable working with complex datasets and identifying the key factors behind changes in fraud performance.

• You can identify fraud trends and propose practical prevention ideas based on your analysis.

• You can write SQL or similar analytical code independently and produce clear, legible work that can be understood and reused by others.

• You can test fraud rule conditions and investigate rule or risk-engine related issues.

• You understand how fraud prevention decisions can affect multiple metrics, including fraud loss, customer experience, approval rates, and product costs.

• You are comfortable learning new data analysis techniques, tools, and fraud prevention methods.

• You can communicate analytical findings clearly to both technical and non-technical stakeholders.

• You are curious about why fraud strategies perform the way they do and are motivated to continuously improve them.

For everyone, everywhere. We're people building money without borders  — without judgement or prejudice, too. We believe teams are strongest when they are diverse, equitable and inclusive.

We're proud to have a truly international team, and we celebrate our differences.
Inclusive teams help us live our values and make sure every Wiser feels respected, empowered to contribute towards our mission and able to progress in their careers.

If you want to find out more about what it's like to work at Wise visit Wise.Jobs.

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