Senior Analyst, Fraud Prevention & Detection
# Senior Analyst, Fraud Prevention & Detection **NAB - National Australia Bank** · Sydney NSW · `On-site` 🕒 **Статус:** *Опубликовано: сегодня* · *Источник: Indeed* --- ### About the Role Senior Analyst, Fraud Prevention & Detection 809157 NSW- Sydney CBD QLD- Brisbane South & Gold Coast VIC- Melbourne CBD Compliance, Regulatory Risk & Financial Crime Permanent Full time Opening at: Sep 15 2026 - 06:00 AEST Closing at: Sep 21 2026 - 23:55 AEST Turn complex data into actionable intelligence that stops fraud and scams. As a Senior Analyst, you’ll uncover emerging threats, connect patterns and influence smarter prevention, detection and disruption strategies—protecting customers and reducing fraud losses. Uncover emerging fraud and scam threats through sharp data analysis. Turn intelligence into smarter prevention, detection and disruption actions. Protect customers and reduce fraud losses through meaningful insights. Our people are customer obsessed. They prioritise the needs and satisfaction of the customer above all else. Our mindset fosters innovation and creates strong, lasting customer relationships as we strive to be the most customer centric company in Australia and New Zealand. In this Senior Analyst Fraud & Scam Intelligence , role you will join the Fraud Operations Team within Financial Crime and Fraud that’s doubling down on customer obsession. Each day, you’ll go above and beyond to support with: Analysing enterprise, industry and external data to identify customer, entity and network risk. Driving improvements in fraud detection and prevention, targeting better outcomes in loss reduction, customer experience, and detection accuracy. Producing strategic, operational and tactical intelligence aligned to agreed priorities and timelines. Working closely with operations, risk and technology to translate intelligence into prevention, detection and disruption actions. Ensuring compliance and ethical standards, aligning all work with internal policies, audit requirements, and health & safety legislation. We’re looking for the best and brightest to deliver the best for our customers. You’ll need: 3+ years’ experience in fraud, scams, financial crime, intelligence, investigations, risk or a related analytical role. Proven exposure and interest in database analysis, reporting and application programming (including, but not limited to PowerBI, SQL, Splunk, Python, SAS). Strong investigative and analytical judgement, including assessment of incomplete or conflicting information. Ability to identify patterns, link entities and develop clear, evidence-based intelligence assessments. Excellent written and verbal communication, with the ability to tailor complex insights for operational and senior audiences. Strong stakeholder engagement and collaboration across operational, risk and technology teams. Customer-focused approach, with sound judgement when balancing customer harm, fraud risk and operational impacts. A diverse and inclusive workplace works better for everyone We know that our people make us who we are. That's why we have built a culture of equity and respect – where everyone feels valued and appreciated for being their authentic selves. In partnership with our multiple Employee Resource Groups (ERGs) we continue to foster an inclusive environment, where all NAB colleagues’ unique backgrounds and identities are understood, respected and celebrated. We are committed to providing an environment where you can work your way. For details on the recruitment process, and accessibility, please visit https://www.nab.com.au/about-us/careers/apply-for-job. To discuss adjustment requirements, please contact the NAB Careers team, via nab.careers@nab.com.au (please reference job number) or visit our Careers page through the link above for other contact options. Join NAB If you think this role is the right fit for you, we would love to hear from you. Please note candidate screening and interviews may be conducted prior to the closing date of the job advert. Unsolicited CVs from agencies will not be accepted. #LI-DNI
Наблюдалась 2026-09-15, впервые 2026-09-15, источник — Indeed.