HSBC’s PayMe for Business app | How we built it on Azure

In this video, Alessio Basso, the Chief Architect of PayMe from HSBC, provides an executive briefing on how the intelligent and digital payment platform for the app was built on Azure.

HSBC’s PayMe for Business App has gained popularity in a very rapid fashion.

At 0:55, it is clearly stated that HSBC has been the first international bank to move their technology to the cloud. At 1:22, Alessio states that HSBC focuses on ensuring information security and risk management with the latest cloud technology strategies. Later at 2:35, he explains that at first it all started with the cashless methodology in a P2P fashion.

Intelligent and secure analytic app

At 2:50, Alessio explains that the HSBC PayMe app was launched for customers in 2017. He adds that it is a social payment application which allows the users to send money to their friends and family without asking for their phone number or the bank account, all for free.

At 3:05 he states that the application is widely used in HongKong to transfer money in social situations. He further adds that the users can avail themselves of all the bank-grade securities that HSBC provides. In addition he describes that the best part of the application is it’s speed, explaining at 4:00 the statistic that 98% of the transactions terminate within 500ms.

Alessio further adds that there is built-in intelligence in order for the business to use the data to completely analyze the sales trend.

At 5:10, he begins to explain the security authentication microservice which conveys the user, the level of authentication which is required to perform different functions within the app. At 6:03, he demonstrates the payment process.

He briefs that when the merchant needs to collect a payment, the amount is typed. The app would then call the QR code payment service. He further adds on that the consumer then takes his or her PayMe for a consumer app, scans the QR code and confirms the payment confirmation. The confirmation can be made by either fingerprint or face id.

Achieving scalability

At 8:18, Alessio explains how scalability is reached during the seasons where there is more traffic. During those times, the payment transaction services are scaled. In the same time, the database layer also gets scaled by obtaining direct replicas of the MySQL databases. At 10:20, he emphasizes that the secure model of the cloud is still followed to connect every transaction.

All the services can communicate with each other as if they are in the same perimeter. At 12:35 he points out a scenario where a security alert mail is obtained when the user signs in the app from the place which is different from their usual place. These get flagged for further investigation.

Alessio, at 14:07 explains the use of Databricks as the data platform which would stitch together all the data interaction. It also does data engineering and the data science workload. At 16:08, he puts forward the example of transaction classification which is not real-time. Here the data engineering and data science is being performed.

Through this video Alessio provided tips and ways to build intelligent and secure analytics app on the Azure cloud.

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