Safeguarding Compliance and Ensuring Responsible Banking with Data at ANZ Bank
Technology Category
- Analytics & Modeling - Machine Learning
- Infrastructure as a Service (IaaS) - Private Cloud
Applicable Industries
- Finance & Insurance
- Retail
Applicable Functions
- Product Research & Development
- Quality Assurance
Use Cases
- Leasing Finance Automation
- Machine to Machine Payments
Services
- Cloud Planning, Design & Implementation Services
- Data Science Services
About The Customer
ANZ Bank is a publicly listed company that provides banking and financial products and services to over 8.5 million retail and business customers across 32 markets. The bank is committed to sustainability and corporate responsibility. In recent years, ANZ Bank has focused on digital innovation and improving the customer experience through the development of new technologies and services. The bank has also been involved in several community initiatives and partnerships, including programs to support small businesses and improve financial literacy.
The Challenge
ANZ Bank, a leading financial institution in Australia, was faced with the challenge of identifying and rectifying compliance gaps in its processes and products. The bank needed to analyze every single transaction over the past 20 years to uncover lapses, such as incorrect interest rates and fees charged. This was a daunting task as it involved sifting through approximately 10 PB of data. The challenge was compounded by the evolving regulatory landscape in Australia's banking sector, which had become more stringent since 2017. Banks were now required by law to design their products with their customers’ needs in mind and were held accountable for instances of non-compliance. ANZ Bank was committed to acting responsibly and wanted to rectify any mistakes made in the past to build customer trust.
The Solution
To address this challenge, ANZ Bank deployed the Cloudera Data Platform Private Cloud Base (CDP Private Cloud Base) to build data forensics capabilities. The platform provided the flexibility to implement various product pipelines for data forensics analysis in the Australia retail and business lending divisions. It enabled capabilities such as data ingestion, customer segmentation, and reporting. With Cloudera’s open data lakehouse, ANZ Bank was able to identify past compliance gaps in its processes and products and take action to fix these issues. The bank also plans to use Cloudera's machine learning capabilities to build data analytic models to screen its current and new products, ensuring that adequate safeguards and best practices are put in place to prevent future lapses in compliance.
Operational Impact
Quantitative Benefit
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