Big Data and Cloud Computing Changed Banking Forever
Book: Bank 3.0: Why Banking Is No Longer Somewhere You Go But Something You Do Author: Brett King ISBN: 978-1-118-58963-2 Publisher: Wiley (2013)
Chapter 10 is about three things that were buzzy in 2012 and completely normal by now: cloud computing, big data, and augmented reality. King ties all three together to make a case for how banking infrastructure needs to change at its core.
The Cloud Was Never Optional
King opens with the Chromebook. Google launched it in 2011 as a laptop that barely had local storage. Everything lived in the cloud. Need a document? Open a browser. Need a spreadsheet? Browser. The whole point was that your data shouldn’t be tied to one device.
This seems obvious now, but back then it was a real debate. Many IT teams in banking were still running everything on local servers. The idea of putting customer data somewhere in “the cloud” made compliance teams nervous.
King’s argument was straightforward. As people started using more devices (phone, tablet, laptop, work computer), their data needed to follow them. Syncing contacts across devices was already painful. Now imagine syncing your entire financial life. The cloud was the only answer that scaled.
He walks through how Google, Apple, Microsoft, IBM, and Amazon were all building massive data centers and cloud platforms. Apple had iCloud. Microsoft was pushing Office365 and SkyDrive. Google had its apps suite. The major players were betting billions on the idea that the future was in the cloud. Banks needed to catch up or get left behind.
Banks Were Stuck on 1960s Infrastructure
This is one of the more important points in the chapter. Most banks were running on legacy mainframe systems built in the 1960s and 70s. They’d spent billions on these systems over decades. Ripping them out felt impossible.
But King points out the problem: these systems were built for a world where the transaction was the center of banking. Put money in, take money out, record it. That’s what mainframes were good at.
In a world where the customer is the center, those systems fall apart. You need flexible, real-time connections. You need to integrate with third-party apps. You need to scale up during peak usage and scale down when it’s quiet. Legacy mainframes can’t do any of that well.
Some banks were starting to get it. BBVA moved desktop applications to Google Apps. Commonwealth Bank of Australia set up cloud operations with Amazon Web Services. Deutsche Bank launched a cloud-based development platform. But most banks were still dragging their feet.
King also makes an interesting argument about APIs. Citi had started building APIs that let partners access banking functions directly. Google Wallet was one of the first implementations. It could onboard a customer and provision a credit card in real time, no paperwork, no branch visit needed. That was forward thinking for 2012.
The lesson is clear: banks that locked themselves inside proprietary systems were building their own cages. The future belonged to banks that could connect with the outside world through open, flexible interfaces.
PayPal Was Already in the Cloud
King drops this line almost casually, but it hits hard. PayPal was already a cloud-based payment system. If banks didn’t move their payment infrastructure to the cloud, someone else would just do it for them. And they’d keep the customers.
The cloud also opened up possibilities for small and medium businesses. Better accounting tools, cash-flow analysis, easier merchant payments, e-invoicing. Banks could either provide these services or watch fintech startups take that relationship away.
P2P payments were starting to take off too. Bank of America, ING Direct, and PNC had all rolled out person-to-person transfer technology. Within a few years, your phone would be the main way to pay small businesses for services. No more “the cheque is in the mail” excuses.
Big Data: Your Data Is Sexy, Don’t Throw It Out
The Big Data section is where King gets most excited. Banks were sitting on mountains of data about their customers. Transaction histories, spending patterns, location data, behavioral information. And most of them were throwing it away or ignoring it.
His example is credit card data. Banks wanted customers to keep using their cards. So they’d blast out random offers hoping something would stick. But they already had the data to know which specific merchants each customer preferred. A targeted offer for a store you actually shop at is way more effective than a random coupon for somewhere you’ve never been.
King quotes Sean Park from Anthemis Group: “Your data is sexy. Don’t throw it out.” That’s blunt, but accurate.
The bigger picture is about real-time decisions. Instead of having a human risk officer manually review each loan application, algorithms could pre-approve customers based on their data profile. Instead of generic marketing, banks could serve offers based on where you are and what you’re doing right now.
King acknowledges the privacy concerns but argues that customers were already trading privacy for convenience. Social media users were sharing attitudes, opinions, and behavioral data by the petabyte. Banks that refused to use data because of vague privacy worries would lose to competitors who used it responsibly.
The challenge in 2012 was speed. Data analysis took months. By the time you had results, they might already be stale. The solution was better infrastructure (hello, cloud) and better collaboration with outside partners. No bank could build all the data capabilities it needed internally.
Augmented Reality: The Wild Card
The last section covers augmented reality, and this is where the chapter gets a bit speculative. King talks about Google Goggles (image-based search), heads-up displays, and the concept of overlaying digital information on the real world.
Google was about to launch Google Glass. King was excited about the possibilities. Smart glasses that could remind you of a business contact’s name using facial recognition. AR apps that could show you the nearest subway station by pointing your phone at the street. Banking apps that could overlay financial data on your physical environment.
He also acknowledges the problems. Distracted walking. Privacy creep. The weirdness of having data constantly floating in front of your eyes. Fort Lee, New Jersey, had just started fining people for texting while walking. AR glasses would make that problem worse.
Looking back, Google Glass was a famous flop in its consumer version. But the underlying tech didn’t go away. AR is now in phones, in retail, in manufacturing. Apple eventually released their own spatial computing device. The concept King described was directionally right, even if the timeline and form factor were off.
What King Got Right and What He Missed
The cloud prediction was spot on. Banking infrastructure has moved heavily toward cloud services. AWS, Azure, and Google Cloud are now standard parts of bank technology stacks. The idea of running everything on your own mainframes feels ancient.
Big data was also a clean hit. Every major bank now uses data analytics for risk decisions, customer targeting, fraud detection, and product development. The “exaflood” of data King warned about is here, and banks that learned to use it have a real edge.
The augmented reality prediction was the miss. Not because AR didn’t develop, but because it didn’t become the primary way people interact with banking. We got better banking apps instead. The interface that won wasn’t AR glasses. It was the phone screen you’re probably reading this on right now.
My Take
This chapter is really about infrastructure. Not the exciting kind of infrastructure with flashy demos, but the boring kind that determines whether a bank can actually serve its customers in real time. Cloud, data, APIs, real-time processing. None of this sounds exciting. But it’s the foundation that separates banks that work from banks that frustrate.
King’s point about legacy systems is the most important one. Banks that built their identity around physical branches and 50-year-old mainframes weren’t just behind on technology. They were structurally unable to compete. Moving to the cloud wasn’t just a tech upgrade. It was a survival decision.
The data argument is equally important. Banks have more information about our financial lives than almost any other institution. The ones that use it well (with proper controls and consent) build better products and stronger relationships. The ones that ignore it lose customers to competitors who actually pay attention.
Solid chapter. Less flashy than the previous one about Moore’s Law and 3D printing, but probably more important for understanding where banking actually went.