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Google Cloud
How The Cloud can help Financial Services, CIOs Create Business Value Through
Colin Timm
Having worked with many CIOs in the financial services industry, I’ve observed that managing regulatory and compliance risks come at the expense of technology advancements. I would argue though that there is often a bigger risk with sticking to the status quo.
For example, there’s a perception that on-premise systems are less risky than public cloud. However, legacy systems are hard to patch and modernize, and there’s a lack of data encryption at rest and in transit by default due to high financial and technical costs in implementation. It’s also common to hear of administrators and users bypassing security controls because the tools are inconvenient or impede workflow. So how should CIOs think about the transition to the cloud?
Questions to ask
For any company looking to develop their cloud strategy, I’d recommend asking their cloud service provider three questions:
On security: How does your cloud provider handle security across each layer - from physical security to server integrity, identity management, and data encryption at rest and in transit?
On interoperability: Does the cloud services provider support hybrid or multi-cloud approaches? Do they have open-source and interoperable tools that support a broader ecosystem and help you avoid vendor lock-in?
On data governance: Does the cloud service provider have tools to help you discover and classify the data that you have? And again, do they have easy to use tools that work with the user to secure your data?
Given the sensitivity of the information they touch, financial services organizations must have complete control over their data.
The introduction of hybrid and multi-cloud platforms, like google anthos, provides them with flexibility and choice
We a so see financial services organizations use machine learning to enhance security. For providers, security is always top-of-mind, and a growing number are moving to the cloud to take advantage of the automation and scale it offers. With its ability to handle computer and data analytics at any scale, cloud computing accelerates the capabilities of machine learning. HSBC is using BigQuery to identify potential anti-money laundering cases faster and more accurately. Utilizing data analytics and machine learning, HSBC can inspect the volumes of data from the banking behavior of more than 38 million customers. It can then cross-reference customer actions and flag unusual activity for review.
Productivity savings
The cloud has also proven to be a massive game changer to streamline daily tasks. Financial institutions are seeing how they can leverage tools like machine learning APIs to improve productivity across the business — from intuitive chatbots to intelligent case routing — without the need to build and train their models.
Case in point; ANZ, Australia’s third-largest bank by market capitalization, is leveraging Google Cloud’s big data analytics capabilities to drive productivity within the bank. It is using BigQuery as an automation tool, accelerating previously manual operations such as analyzing aggregated, de-identified credit card data - a process that used to take days, has been dramatically reduced to only seconds.
Improves your credit score with customers
In an age where the customer is king, banks are embracing the cloud to improve customer service. The insights derived from advanced data analytics are helping to fuel more personalized user experiences. ANZ is transforming the way it uses data to help its Institutional customers make strategic business decisions more quickly on issues like liquidity, risk and cash management, or strategic calls like store locations, inventory and market positioning.
Take the first step
When it comes to moving to the cloud, it’s still early days for many financial services organizations, but the urgency is there. For businesses to leapfrog the technology curve, now is the time to do an honest assessment of existing risks and see if the cloud can help mitigate them at scale.
