case study banking fraud prevention

Case Study:

Leading Financial Institution Takes Fraud Prevention to the Cloud

Company Profile

  • One of Australia’s longest established and largest financial institutions
  • Diversified global financial services player
  • Website gets 80,000+ visits per month

Goals

  • Transform simplistic, rules-based risk reviews to more nuanced, AI-powered fraud detection
  • Reduce fraud rate and severity of fraud losses
  • Save money by streamlining and digitizing once-manual fraud risk reviews

Results

  • 400% increase in identified fraud cases
  • 33% reduction in flagged transactions
  • 76% reduction in manual review budget

The Problemcase study banking fraud prevention

Digitizing Overnight Fraud Operations

The FI’s risk prevention and analysis team relied on an archaic, rules-based system that was relatively simple and difficult to modify. Amidst growing sophistication on the part of fraudsters, the firm was facing not just a high rate of fraud, but also fraudsters that were making it too far through the transaction lifecycle before they were identified.

To solve these challenges, they were taking a brute-force response, employing a parallel fraud analysis group that would work the overnight shift, just to work through all the questionable transactions that came in daily. But to truly transform its fraud operations, the FI would need to digitize and streamline its fraud risk reviews.

The Solution

Providing Comprehensive and Flexible Fraud Management Infrastructure

Fraud.net provided the client with a comprehensive platform for risk analysis and prevention, allowing them to digitize part of its overnight review operations. This included a flexible, intuitive, and secure rules engine, which made it easy for the client to refine and update rules based on experience and machine learning and save money by deploying its analysts more efficiently. Fraud.net also provided a host of data delivered via collective intelligence—billions of anonymized data points shared across partners and clients. This helped risk-prevention officers spot fraudsters long before they ever tried to transact.

Our Solution:

  • Comprehensive Platform – A comprehensive platform for risk analysis and prevention.
  • Secure Rules Engine – Flexible, intuitive, and secure rules engine powered by AI.
  • Collective Intelligence – Provided a host of data delivered via billions of anonymized data points shared across partners and clients.

    “The great usability of Fraud.net is night and day when comparing it to our prior risk prevention platform. Reporting is also faster, more straightforward, and more impactful. With Fraud.net, we can easily visualize and share findings, providing our leadership with a clear understanding of the return-on-investment for our activities in real-time.”

    Fraud Manager, Global Financial Institution


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    AWS Infrastructure + Fraud.net’s Intelligence Layer =
    A Complete, Cloud-born Fraud Management Platform

    The more you move mission-critical processes into the cloud, the greater your agility as an organization, and the faster you will pull ahead of your competition.  But in doing so, you need new frameworks that offload non-core functions to partner specialists offering highly scalable, highly resilient systems-of-record on which you can rely.  Only then can you focus on thrilling your customers by doing what your organization is known for.

    Let Fraud.net on AWS help you to:

    • Isolate fraud to deliver immediate bottom-line improvements,
    • Gain real-time risk intelligence across your applications and services,
    • Remove friction from your new customers’ applications and transactions,
    • Grow revenues by confidently expanding into new products and geographies.
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