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.
Job DescriptionWe're looking for a Transaction Health Senior Analyst to join our team in the Singapore office. This role is a unique opportunity to have an impact on Wise’s mission, grow as an analyst, help save millions more people money and work in a disruptive, fast-growing and fun environment.
Your mission:
Wise has already pioneered new ways for people to transfer money across borders and currencies. Our customers can also manage their hard-earned money with the world’s first platform to offer true multi-currency banking, and they can spend every day using our Wise debit card.
Card payments represent a large part of the funds moved to Wise daily, and card fraud disputes are an inevitable part of that. Our Card Fraud team thus supports Wise’s mission in a very impactful area.
We have an awesome operational team handling these Card Fraud disputes in four countries across the globe; a unified team that works very closely with our dedicated engineering and product teams.
As a Card Fraud Analyst, you get to support your team’s operational success and bring your expertise to upscale the domain; driving detection and prevention focused initiatives with long-lasting impacts will be part of your daily work.
Here’s how you’ll be contributing to the team:
Reducing Card Fraud loss (Spend product costs):
Analysing Card Fraud dispute trends, independently querying databases and doing data deep dives
Prioritising and delegating Card Fraud prevention workflows in line with our KPIs
Card Fraud prevention rule creation: rule scope validation, rule creation, and monitoring post rule implementation
Prioritising customer experience/impact from rule declines by writing rules with a high level of accuracy and quality that do not unnecessarily decline transactions causing a loss of revenue for Wise.
Working closely with Product and Engineering teams to drive optimal customer experience from fraud declines and alerts
Working closely with the Data science team on machine learning models
Leading long term Card Fraud prevention projects contributing to the KRIs/KPIs/OKRs.
Providing data and writing rules in relation to incidents, and managing incidents if needed.
Effectively communicate and explain Card Fraud prevention strategies to Wisers who are not on the fraud prevention team
Card Fraud Prevention and Risk Management
Protect our Wise cardholders from unauthorised card usage, scams, and payment instrument and account takeover fraud.
Spend fraud rule creation and optimisation to mitigate the impact of card fraud on Wise cardholders suffering monetary loss, Spend fraud BPS (scheme compliance & fees), and unrecoverable fraud loss (product cost)
Understand and implement machine learning scores within static fraud rules to improve rule precision and recall.
Work with data science on the optimisation and periodical retraining of the internal card fraud machine learning model.
Own longer term projects targeted at card fraud reduction.
Engage Spend Product and Engineering teams to drive rule engine improvements, with the focus of optimising the card fraud customer journey from rule declines to rule alerts and dispute submission.
Staying up to date with fraud trends highlighted by the card schemes, governmental organisations, and the media.
Team Direction and Analytics Management
Prioritise and delegate work for a small team of analysts, effectively driving the team to focus on highest leverage activities. Plan, structure and coordinate analyst work effectively, responding appropriately to challenges as they arise.
Ensure that card fraud prevention work is prioritised in line with our OKRs, KPIs, and overall strategy.
Deliver or materially contribute to the prevention of large scale card fraud waves or prevention projects, and is good at helping others overcome blockers
Lead projects and develop up to 1-2 analysts by coaching and supporting analysts in a manner that is aligned with their development needs and with the aim of increasing their impact
KPI & performance measurement management
Managing and ensuring KPI and performance metrics accessibility to Teams
Ensuring any required data is available to the Card Fraud Ops team - either by providing the data in an accessible manner or by driving engineering changes where necessary.
Strong collaboration with Leadership on KPI (maintenance & building)
Identifying the problematic areas based on KPI performance
Identifying product issues and improvement areas (cross team)
Incident Management
- Providing data and relevant insights to all stakeholders for the purposes of incident management
Able to identify card fraud prevention gaps and come up with strategies to mitigate risk and resolve the incident
Able to perform in an incident manager role if needed
Escalating risks sitting outside of the Card Fraud domain (or appetite) to external stakeholders
Qualifications
Your verbal and written English skills are excellent. If you speak other languages then that’s a bonus!
You have strong attention to detail, punctuality, and are comfortable taking initiatives.
You are good with routine but can also adapt and keep up with fast changes.
You are able to work independently but also know how important good team-work is.
You can make decisions in critical situations and have the ability to multitask.
You have a genuine enthusiasm for the FinCrime industry.
You have experience with SQL, or a similar coding language, and have experience with FinCrime prevention strategy creation and management.
Your Analytical and Strategic Abilities
Able to competently think through analytical tasks and fully understand the impact of card fraud rules on the spend product and on our customers.
Deliver quality analysis that addresses the business problem.
Comfortable with complexity and aware of key factors underlying a decision.
Able to propose ideas autonomously to deflect card fraud waves
Able to code both independently and in collaboration with other analysts, and write legible code that is usable by others.
Able to test fraud rule conditions autonomously and troubleshoot code and risk engine related issues.
Able to understand the interaction between metrics over multiple products/services across multiple teams and directs effort towards high leverage activities
Comfortable learning new data analysis techniques and methods.
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.
Keep up to date with life at Wise by following us on LinkedIn and Instagram.
Skills Required
- Excellent verbal and written English skills
- Strong attention to detail and punctuality
- Ability to take initiative and adapt to rapid changes
- Ability to work independently and collaboratively
- Ability to make decisions in critical situations and multitask
- Genuine enthusiasm for the financial crime prevention industry
- Experience with SQL or a similar coding language
- Experience creating and managing financial crime prevention strategies
- Ability to independently analyze data and understand card fraud rule impacts
- Ability to code independently and collaboratively using legible, reusable code
- Ability to test fraud rule conditions and troubleshoot code and risk-engine issues
- Ability to understand metrics across multiple products and services
- Ability to learn new data analysis techniques and methods
Wise Compensation & Benefits Highlights
-
Leave & Time Off Breadth — Global paid time off is presented as 33–36 days including local public holidays, plus three “Me Days,” with a paid six‑week sabbatical and stipend after four years. Work-from-anywhere for up to 90 days per year after six months further complements time away and flexibility.
-
Equity Value & Accessibility — RSUs are granted to all employees, enabling broad ownership in the company. Equity is positioned as a standard, company‑wide component of total rewards.
-
Parental & Family Support — Parental leave is described as generous across markets, with U.S. pages listing up to 18 weeks fully paid for birthing parents and 8 weeks for non‑birthing parents. Additional family‑oriented supports such as onsite Mother’s Rooms and abortion travel benefits are noted in certain locations.
Wise Insights
What We Do
Wise is a global technology company, building the best way to move and manage the world's money. With Wise Account and Wise Business, people and businesses can hold 40 currencies, move money between countries and spend money abroad. Large companies and banks use Wise technology too; an entirely new network for the world's money. Launched in 2011, Wise is one of the world’s fastest growing, profitable tech companies. In fiscal year 2025, Wise supported around 15.6 million people and businesses, processing over $185 billion in cross-border transactions and saving customers around $2.6 billion.
Why Work With Us
We’re truly global in who we are, how we work, and how we build. Everything we do is centred around creating a world of money that’s fast, easy, fair. And open to all. Everyone who works here owns a piece of Wise, from the work they do, to the stock they hold.
Gallery
Wise Offices
Hybrid Workspace
Employees engage in a combination of remote and on-site work.
We expect new joiners in the office most days to build connections and learn from colleagues for their first six months. After that, most Wisers split their working week between the office and home, typically coming in at least 12 times a month.
