Case Study

Multinational Investment Bank – Data Analytics

James Alexander at Appsbroker wearing purple branded polo

Written by James Alexander
Sales Director, Financial Services

How a Multinational Investment Bank Delivers Streaming Transaction Data in Real-Time

 

THE CUSTOMER

The customer is a British multinational investment bank and financial services holding company. The bank was among the largest in the world and in Europe by 2020, with total assets worth over US $2 trillion as of late August.

APPSBROKER’S ROLE

Having previously worked together and developed a strong relationship, the bank chose Appsbroker due to its extensive experience delivering data analytics projects in the financial services sector.

THE CHALLENGE

The bank’s retail transactions were being processed and data enriched using a periodic batch process. This resulted in delays before downstream systems and business users were able to analyse the data and take appropriate action. An example would be to send out alerts or postal address changes.

The bank needed to move the processing and data enrichment to an instant process enabling its business users to react and take decisions in real-time. The extreme peaks of incoming ordered transactions of up to 10,000 a second made the real-time processing a real engineering challenge.

THE SOLUTION

Appsbroker worked with the bank’s teams to process incoming retail transactions events into the managed Google Pub/Sub messaging service. From there, events were identified and enriched with an automatic scalable Dataflow job.

The identified and enriched transactions were then able to be pushed into a new custom built events rules engine. Non-technical business users use the events engine to build complex rules, in business language, to determine where identified transactions can be consumed by target downstream systems within the bank.

THE RESULTS
As a result of our engagement, business units now have the ability to monitor and analyse the bank’s incoming transactions in real-time and take appropriate decisions.

In addition to improving the way the business can use its data to make decisions, the bank has unlocked substantial cost savings by moving the process to a streaming and automatically scalable solution on Google Cloud.

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