Databricks exec explains why open banking will disrupt finance the same way open source upended software

• Junta Nakai is the global industry leader for financial services and sustainability at Databricks, a big data and AI company valued at $28 billion.
• In this op-ed, Nakai explains open banking and why it is critical to the future of finance.
• Nakai also explains how firms can be best prepared for the shift.

The way individuals borrow, save, and move money hasn't changed much in decades. However, things are changing. Open technologies and the adoption of data and artificial intelligence are fundamentally transforming the way we interact with money.

Open banking - rules that force banks to share customer data with competitors - will be the catalyst that upends this decades-long innovation stasis.

The concepts of open application programming interfaces (APIs), open data, and open source that underpin open banking will quickly spread beyond Europe and become a fixture in the world's major markets - spurring innovation, bringing transparency, and creating new services that will bring millions of individuals out of the shadows of banking.

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Specifically, open banking will do to banking what open source did to software.

Which is:

1) Accelerate innovation

2) Launch new business models

3) Create massive value for disrupters and adapters

Open banking is about faster, more flexible banking services

Open banking represents a paradigm shift for banks. It transfixes the open mindset and open-software principle to the rigid world of finance. Open banking is about leveraging technology to create platforms for transactions and banking services that are more flexible and faster than what is available today.

It is about enabling fintechs and other financial startups to drive innovation and offer consumers more choice at lower prices.

But mostly, open banking is about data. Specifically, it systematizes the reality that the most important asset for a financial service institution (FSI) today is no longer capital or scale, but rather data. It opens up access to customer data to third-party developers, leveling the playing field in a sector that consistently ranks among the lowest in its ability to innovate.

Open banking provides opportunity for new business models and products to emerge. It is designed to spur innovation underpinned with data.

See more: Execs from Plaid and Yodlee explain how new data-sharing rules will dictate the future of how banks and fintechs work together

Incumbent banks will be forced to move from a historically "closed" model to an "open" model, where customer data now belongs to the customer and thus data can be shared between institutions. In order to better compete with fintechs, established FSIs must better utilize data to evolve away from product-centricity towards customer-centricity.

Consumers will unequivocally benefit from new services and gain more transparency, e.g., in credit scores and pricing. On the other hand, for incumbents that do not adapt, open banking exacerbates the risk that they become utilities, characterized by low pricing power, low brand awareness and low customer loyalty.

We have historical precedent for this kind of shift towards "openness." In the 2010s, when open source took hold of the software industry, the new paradigm significantly accelerated innovation. Agile companies and startups that embraced an open mindset were able to capture an outsized share of the value creation.

The companies that did not are no longer around. Today, the largest companies on Earth are the ones that have embraced open source and its open mindset. On the index level, software vastly outperformed diversified financials in the 2010s.

Similarly, in open banking, companies that survive and thrive must become more innovative, data-driven, and cost-effective. They must institutionalize an open mind-set. To this end, the use of data-driven analytics plays a major role. Machine-learning techniques are already common in banking and will become even more important in the future.

Leveraging data and AI is key to open banking

The decisive factor for adaptation and survival will be the speed at which they can analyze customer information through the use of algorithms and automation. Various use cases can be rapidly prototyped from the data, such as banking-as-a-service and real-time personalization of financial products.

To fully realize the potential of data and AI, FSIs must modernize their approaches to risk management, personalization, and fraud detection by leveraging the power of the cloud, best-in-class open-source tools, and big data/AI platforms to enable collaboration and innovation.

Simply put, data and AI are at the heart of unlocking business value. Moving to a modern cloud and AI-based bank is easier said than done, but CEOs are firmly focused on it because they understand the existential threat of inaction.

Jamie Dimon, CEO of JPMorgan Chase, recently addressed the topics of cloud and AI in an earnings call by saying "10 years from now, [Cloud+AI] will be probably 50 times more than we are doing today. And I would spend anything to get it done faster."

See more: The next hot fintech trends top VCs are betting on: Embedded finance, finfluencers, and a 'great rebundling'

Tomorrow's winners will be the FSIs that equip their employees with the right technology tools to leverage the most important asset they have: their data.

The conclusion from all of this is that a modern and simplified technology stack is becoming a prerequisite for competing in an open-banking paradigm. While open banking is currently mainly focused on Europe, Canada, and Australia, the impact will quickly be felt all over the world and become the modus operandi for the banks that win.

Junta Nakai is the global industry leader of financial services and sustainability at Databricks. In his capacity, he is responsible for driving the world wide adoption of the Databricks platform across capital markets, banking/payments, insurers, and data providers as well as the advancement of ESG use cases across all verticals. Prior to joining Databricks, Junta spent 14 years at Goldman Sachs, where he most recently served as the head of Asia Pacific sales for the Americas in the equities division.