Fraud Scam Prevention Specialist

3 weeks ago


Melbourne, Victoria, Australia ANZ Full time

About Us

At ANZ, we're shaping a world where people and communities thrive, driven by a common goal: to improve the financial wellbeing and sustainability of our millions of customers.

About the Role

As a Fraud Scam Prevention Analyst in our Fraud Analytics team, you'll play a key role in helping to protect our customers against fraud and minimise ANZ's fraud losses. You are expected to use analytical techniques to utilise internal and external data/indicators to identify compromises and fraud trends and come up with prevention and detection strategies to mitigate the risk and exposure. The role involves liaising with internal teams and the broader fraud community comprising of representatives from other banks, schemes, external vendors and government bodies. The role also involves ensuring timely and accurate reporting of fraud losses and metrics to business stakeholders and providing insights on the same. Knowledge of Fraud, strong analytical skills and a background in data mining/working with multiple sources of data are key attributes to succeed in this role.

Key Responsibilities

  • Fraud Detection Strategy: Work on refining fraud detection rules and strategies to pro-actively identify potential Application Fraud events, whilst minimizing the impact to our genuine customers.
  • Data Analysis: Dive into large datasets using SAS and SQL to mine for trends and anomalies. Generate reports that highlight suspicious activities and patterns related to Application fraud.
  • Collaboration: Participate in regular meetings with investigation teams & industry peers, product, risk & technology to discuss ongoing cases, share insights, and coordinate efforts to enhance fraud detection capabilities.

What We're Looking For

To grow and be successful in this role, you will ideally bring the following:

  • Understanding of retail & commercial bank products, payment channels / types & associated fraud risk
  • Experience with Data mining and Analysis of large datasets & reporting
  • Experience working in Fraud or demonstrated close coordination with Fraud teams
  • Experience with using SAS/SQL in prior / current role
  • Demonstrated ability to work collaboratively with internal & external stakeholders and peers
  • Ability to manage multiple priorities and support quick decision making

Why Join Us?

At ANZ, you'll be part of an organisation where the different backgrounds, perspectives and life experiences of our people are celebrated. We welcome applications from everyone and encourage you to talk to us about any adjustments you may require to our recruitment process or the role itself. If you are a candidate with a disability or access requirement, let us know how we can provide you with additional support.



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