Open Banking
The Open Banking dream is to democratize banking as we know it. An “Open Bank,” or neobank, or digital bank, operates entirely online. COVID has accelerated the urgency of digital business in every industry, especially banking. Banks, startups, and social media firms must all become more digital and agile.
Neobanks hope to provide more choices, better service, and frictionless commerce. Fintech startups like Stripe, TransferWise, and Zopa aim to disrupt old-school banking styles. Facebook, Amazon, and Alibaba have the pole position on your social banking experience. Traditional banks are reimagining themselves as tech-driven innovators. Open Banking regulations throughout the world empower neobanks to operate.
In March of 2020, I wrote a paper called "Open Banking 2020: The Complete Guide to Tech Innovation." I get asked a lot about a section called "The Elements of an Agile Open Banking Culture.” Here it is, expanded and explained.
Element One: Anything as a Service
The North Star for Ally Bank CIO Sathish Muthukrishnan is what he calls "Anything as a Service." He has it right. Neobanks have the DNA of a software company. Their software services are their product. For traditional banks, this is a new way of thinking. Indeed, JP Morgan’s Jamie Dimon said he wouldn’t be surprised to see a bank fully backed by a tech company in the near future. API Management tools help manage APIs as products. They are the first essential element of a software service culture, because every product is a service. If you’re not familiar with API management, here’s a good tutorial:
Element Two: A Culture of Data Curation
Neobanks must derive insights from data quickly. But many traditional banks have a sprawling, unorganized, unstable data fabric. Neobank startups get to start with a clean sheet of paper with their data. Wherever you start from, a culture of data curation is essential.
My favorite example of a culture of curation comes from the fast-casual dining, not fintech. Faced with uncertainty during COVID, Panera turned their business model upside down in 10 days. Instead of only serving prepared food in 2,000 Cafes, they introduced Panera Pantry. With Panera Pantry, customers can buy Panera ingredients and cook at home.
Panera’s culture of data curation began in 2013, when they introduced a new global metadata management system. Menu adjustments made by chefs are shared in real-time with every part of the Panera team, from supply chain managers to the store. This enabled Panera to act as one team, and quickly adjust their business model.
Element Three: Maniacal About Metadata
For many, metadata management is an abstract and arcane technology area. Metadata means “data about data.” But its business implications aren’t conceptual: metadata is the engine of Panera’s success. By abstracting the business meaning of data away from its implementation, metadata helped Panera focus on transforming its business, not how to get at the information it needed. For Panera, the metadata they needed was about their menu, suppliers, ingredients, stores, hours, delivery vehicles and the weather. For agility neobank, metadata governs access to customer data, business rules, reports, predictive models, risk models, counterparties and more.
Element Four: Automation Awareness
An algorithmic trader friend of mine used to say this about his algorithms. "Being algorithmic is like having 100,000 employees. Algorithms don't complain. They don't take vacations. I can promote the ones that work well. I can fire the ones that fail."
That’s a scary view of algorithms: the power of 100,000 employees. Fire algorithms that fail. But in the very next breath, he spoke of balancing that algorithmic power with human creativity and intuition:
“Human decision making, however, is the key to profitability. When the markets are stable, automation works well. But when things get volatile, human decision-making wins. Every time.”
Successful digital banks strike a balance between human intelligence and automation. Successful digital banks strike a balance between human intelligence and automation. The design automated systems with streaming data science and visual analytics for moving data so human knowledge workers can collaborate and learn from the patterns and trends that emerge from automated systems.
Element Five: Augment Human Intelligence with AI
Artificial intelligence is an essential element of digital business success. Algorithms yield smarter banking services, situational awareness for customer engagement, and intelligent pricing. But data science teams are often disconnected from the business. For open banking innovation, this barrier must be lowered.
Jeff McMillian at Morgan Stanley has it right. He embeds data science professionals with the investment professionals. Morgan Stanley augments human decision making with AI; AI is not the decision-maker.
Element Six: Virtualize Data
At the heart of every open banking service is data, so agile access to information is the first port of call for innovative neobanks. But although every fintech business wants an agile, efficient, scalable data lake, most have a data swamp: balkanized data sources, a mix of old and new, real-time and streaming data, and a maze of organizational barriers.
Data virtualization is a technology that helps firms tame their data swamp. It allows teams to turn dozens of independent data sources into one virtual data warehouse with nearly the same performance as a single system. So, instead of over-using ETL to create a bigger data swamp for APIs, data virtualization leaves data where it is. This provides a unified interface to customer information as if it was, indeed, a single system.
KBTG Bank in Thailand illustrates data virtualization at work. It services 16 million retail banking customers. Through technology, it competes with non-banking companies for digital banking to fit customer lifestyles.
“A lot of things you needed a bank for you can now do through 7-Eleven or with wallets. We’re competing against non-banks now,” said Fred Roteseree, deputy managing director, “so we need to handle a lot more transactions, a lot more activities.
Data virtualization brings the business and IT together because we can deliver services in a much more timely manner.”
For example, KBTG’s “My Portfolio” mobile phone app shows users every banking product and account they have. The data that powers these services is stored in multiple systems— deposit account, credit card, mutual fund. Each API call can require data stored in 12 to 15 databases. By virtualizing its data access, KBTG quickly combines it all.
“Now that we use [data virtualization] technology, people start to think about data differently,” says Roteseree. “We can create a sandbox environment, add another source of data into the report within days as opposed to six months. We can publish data services in a variety of formats within weeks as opposed to months and deliver them in a standardized format within a single layer. Web services can be built in a few hours.”
A Neo Way of Thinking
Neo banking culture is a new kind of digital business culture. The technology is the business. Knowledge workers, data, metadata, virtualized data and algorithms act as one team to deliver anything as a service. The neobanks that apply these cultural elements best will have a leg up on winning the open banking race.
