Fraud Scam Prevention Analyst

vor 4 Wochen

Melbourne, Österreich Tideri Jobbörse Vollzeit

Division: Australia Retail
Location: Melbourne
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 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.

Role Type: Permanent
Role Location: 833 Collins Street, Docklands VIC 3008
Work Hours: Full-time
What will your day look like?
As a Fraud Scam Prevention Analyst, you will:
Fraud Detection Strategy : Work on refining fraud detection rules and strategies to proactively 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 will you bring?
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 You're not expected to have 100% of these skills.
At ANZ a growth mindset is at the heart of our culture, so if you have most of these things in your toolbox, we'd love to hear from you.

So why join us?
From the moment you join ANZ, you'll be doing meaningful work that will shape a world where people and communities thrive.

But it's not just our customers who'll feel your impact.
You'll feel it too.
Because at ANZ, you'll have the resources, opportunities, and support you need to take the next big step in your career.

We're a diverse bunch at ANZ in different roles, different locations, doing different things.
That's why we have a range of flexible working arrangements, so our people can 'make work, work for them'.
We also provide a range of benefits including access to health and wellbeing services and discounts on selected products and services from ANZ and more.

At ANZ, you'll be part of an organisation where the different backgrounds, perspectives, and life experiences of our people are celebrated.
That's because we're committed to building a workplace that reflects the diversity of the communities we serve.
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.

To find out more about working at ANZ, visit .
You can apply for this role by visiting ANZ Careers and searching for reference number 78719.

Job Posting End Date #J-18808-Ljbffr

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