🗂 Link: Financial services and cloud: Delivering digital transformation in a highly regulated industry

“The most difficult part of what was a 10-month programme of work was that we were working to transform the current application, which was manually built, on-premise, and converting that into infrastructure as code,” says Niculescu.

“So we essentially took what would be manually-built environments that would usually take us weeks and months and numerous contract amendments to essentially grow and scale environments, and transformed it so that we could do them within the day – but now we can do all of this within 40 minutes, roughly.”

Source: Financial services and cloud: Delivering digital transformation in a highly regulated industry

Link: HSBC chief architect: Why machine learning is accelerating cloud adoption

If you build it, you own it, big data ed.:

“We got some value out of that but to be honest we found it hard to keep on top of, just hard to build skills at the pace required to integrate new technologies,” Knott says.

“No matter how hard we ran there is always something new coming in that we wanted to get access to, but we couldn’t get there quite fast enough to have really finished deploying what we were deploying previously.

“So it was hard to manage, hard to keep on top of, and also hard to scale. We had reasonable success but we were having these challenges.””

Original source: HSBC chief architect: Why machine learning is accelerating cloud adoption

Link: Cloud Next 18 – HSBC to run business banking on Kubernetes in Google Cloud

“HSBC plans to build its all-new business banking service to run on a Kubernetes-managed container infrastructure using Google’s toolset.”
Original source: Cloud Next 18 – HSBC to run business banking on Kubernetes in Google Cloud

HSBC’s Google Cloud use

A brief note, from William Fellows at 451, on HSBC’s use of Google Cloud’s big data/analytical services:

They have lot of data, that’s only growing:

6PB in 2014, 77PB in 2015 and 93PB in 2016

What they use it for:

In addition to anti-money-laundering workloads (identification and reducing false positives), it is also migrating other machine-learning workloads to GCP, including finance liquidity reporting (six hours to six minutes), risk analytics (raise compute utilization from 10% to actual units consumed), risk reporting and valuation services (rapid provisioning of compute power instead of on-premises grid).

As I highlighted over the weekend, it seems like incumbent banks are doing pretty well wtih all this digital disruption stuff.

Source: HSBC taps Google Compute Platform for Hadoop, is ‘cloud first’ for ML and big data