Fraud Analyst

We are currently seeking a Fraud Analyst to join our team. This is a hybrid role with an option to work from our Collaboration Centers in Langley, Vancouver, Kelowna, Penticton, Duncan, Victoria, or Toronto.

Under direction from the Team Lead, Fraud Detection & Analytics, supports the organization’s fraud prevention and detection capabilities through fraud monitoring, data analysis and reporting, risk and control improvement, and cross-functional collaboration. The role uses fraud detection systems, analytical tools, and data from multiple sources to identify unusual activity, emerging fraud patterns, control weaknesses, and opportunities to enhance detection effectiveness. The Fraud Analyst reviews and escalates fraud alerts, supports the testing and refinement of detection rules and thresholds, and develops reporting and actionable insights to inform fraud prevention activities. Working within established procedures, risk tolerances, and delegated authority, the role maintains accurate documentation, supports data quality and continuous improvement, and recommends practical solutions that balance fraud mitigation, operational effectiveness, and member impact. 

Here’s what would be included as a part of your typical day

1. Fraud Monitoring & Detection Support: Uses fraud monitoring and detection systems to review, prioritize, investigate, resolve, and escalate alerts involving transactional, behavioural, digital, and account activity. Supports the development, testing, implementation, and ongoing refinement of fraud rules, thresholds, and alert strategies. Documents decisions and completes activities within established procedures, service standards, risk tolerances, and delegated authority.
2. Fraud Analytics & Performance Insights: Aggregates, validates, and analyzes data from multiple sources to identify fraud patterns, emerging risks, control weaknesses, and opportunities to improve detection effectiveness. Develops recurring and ad hoc reports, dashboards, metrics, and analytical insights related to fraud trends, losses, alert activity, false-positive rates, detection outcomes, and member impact. Provides evidence-based recommendations to strengthen fraud prevention and operational controls.
3. Fraud Risk: Supports fraud risk assessments, quality assurance, data validation, control reviews, and continuous-improvement initiatives. Maintains documentation relating to fraud rules, testing, reporting definitions, analytical methods, procedures, and change decisions. Identifies and escalates significant fraud risks, data-quality concerns, process gaps, and control weaknesses, and recommends practical improvements within the scope of the role.
4. Cross-Functional Collaboration: Collaborates with Fraud Investigations, AML, Technology, Operations, Product, Compliance, Risk Management, vendors, and other stakeholders to provide fraud analysis, technical support, and subject-matter guidance. Contributes to projects and system enhancements, maintains awareness of emerging fraud trends and typologies, shares relevant knowledge, and escalates material issues requiring senior or management attention. 

Required Skills, Experience & Qualifications

• Diploma in Business, Finance, Risk Management, Criminology, Information Security, Data Analytics, or related discipline required; CFCI, CFE are considered an asset
• 3 years relevant experience in fraud prevention, fraud detection, transaction monitoring, or financial crime analytics including knowledge of financial crimes typologies.
• Strong analytical, critical-thinking, and problem-solving skills, with the ability to interpret data and identify fraud patterns. 
• Sound judgment and attention to detail when managing alerts, priorities, and time-sensitive issues. 
• Clear written and verbal communication skills, with the ability to collaborate with diverse stakeholders. 
• Strong organization and adaptability, with the ability to respond effectively to change, uncertainty, and evolving fraud risks while maintaining confidentiality and accountability.
• Advanced proficiency in MS Office programs particularly Excel
• Experience using fraud detection, transaction-monitoring, or analytical systems, with the ability to learn new technologies quickly.
• Working Knowledge of SQL Server, Power BI, PowerPivot, Dashboards and Data Visualization, 
• Familiarity with Python and basic machine-learning concepts is considered an asset. 
• Ability to use approved generative-AI tools responsibly, securely, and with appropriate validation and human oversight.
• Overnight travel may be occasionally required, up to 6 times per year
• Displays an understanding of risk and risk ownership by being able to demonstrate adherence to policies and procedures.