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Company: Macquarie Bank
Industry: Financial
Functional Use Case: Personalization, Data Store

Macquarie Bank is a subsidiary of Macquarie Group Limited, a global financial services company based in Sydney. It is one of the largest financial institutions in Australia and a major player in the global financial services industry. Macquarie Bank operates in a range of financial services areas, including asset management, corporate finance, banking, commodities trading, leasing, and advisory services. The bank has a significant presence in the Americas, Europe, Asia, and the Middle East, and has a diverse range of clients, including corporations, governments, and individuals.

Choosing the right platform to support Macquarie’s digital journey

Macquarie Bank’s customer’s technological needs and expectations are constantly changing, so the Bank needed to change with them to help deliver a truly world-class and innovative digital experience. They believe a digital bank needs to be more human and intuitive than a traditional brick-and-mortar bank, with an intimate understanding of what the customer wants and needs. Macquarie has a branchless network and a sound financial services business with solid partnerships with some of Australia’s leading brands, putting them in a favorable position to deliver an experience customers are not able to get elsewhere. They needed to look at the architectural foundations to support their aspirations to ensure they become even more relevant in today’s digital world.

What was needed to drive their digital capability?

When selecting a database that would help Macquarie embark on their digital journey, they needed to understand the necessities involved. Firstly, the digital architecture must operate in a continuous real-time environment and capture fast-occurring events and data streams. As consumers have become accustomed to highly personalized digital experiences 24 hours a day, seven days a week, the Bank’s systems also needed to be personal and in the moment. Macquarie wanted users to have the same experience they currently have with digital companies like Facebook or Apple. Macquarie Bank must replicate such a dynamic through an engaging online and mobile banking experience that gives customers the power to take control of their finances online to reach their goals.
Personalization had to be at the forefront of Macquarie’s solution to enable customers to understand how they spend their money, how their finances are performing, and where they need to improve. To do so meant utilizing both real-time and batched analytical solutions. Analytics needs to be in real-time alongside historical data providing quick feedback loops for customers. Data pushed on the edge, recommendations and personalization must-have analysis done in near real-time at the point of interaction or each transactional action or event. An important digital feature was giving users the power to search their accounts and transactions in natural language, so they can engage with their finances and gain genuine insights. This means augmenting the data collected from the customer with information sourced at the enterprise level to provide meaningful and searchable analysis, so not only can they search spending on categories like coffee or fashion, but by store and the location of expenditure.

Additionally, to support a great customer experience, the volume of transactional data, events, and actions have to be considerably large, stored for long periods, and importantly be accessible at high speeds. The architecture has to respond to the ever-changing needs and demands of future customers and technologies, given the rapid and flexible platform changes necessary to be and remain relevant in today’s digital market.

The solution

To support Macquarie Bank’s digital banking transformation, they selected Apache Cassandra® for its elastic linear scale, tunable consistency, and peer-to-peer architecture. The implementation of Spark provided for near real-time stream processing and in-memory distributed computing capability with support for machine learning and Solr for its search and indexing. All of these from an enterprise platform powered by Cassandra.

The key benefit of using these technologies is the co-location of the data and technology with Cassandra and Solr for search, and Cassandra with Spark for analytics. This results in the real-time nodes having access to data instantly and not requiring time-consuming or costly ETL processes to move data between systems, because all the data is transparently replicated in the cluster. The vision of having HTAP (Hybrid Transactional/Analytical Processing) architecture enacted as an achievement through workload segregation allowing data centers dedicated to analytics and search.

The advantage of using these technologies is that it is founded on the principles of ease of use, low latency, distribution and fault tolerance. These technologies allow Macquarie Bank to focus on delivering an exceptional experience and value, to focus on execution of sophisticated personalized recommendations, advice and experience quickly and efficiently.

Stack Includes: Apache Cassandra

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