Legacy systems are banks’ Achilles' heel

All over the modern economy, legacy businesses have been upended by the digital revolution: The old travel agencies have been destroyed, print news verges on extinction and Main Street stores are on their knees. In banking, too, there are fears. Bank CEOs have expressed public concern. A 2019 report by MIT Sloan Management Review showed that over 40% of bank revenue is at risk of digital disruption.

Incumbent banks are at crossroads. On the one hand, they are heavily regulated and need to have extensive internal control systems. On the other, they're being disrupted by fintechs that are agile, innovative, less regulated, and are eating into their revenue streams and client base.

But banks have a chance to thrive, if they remain vigilant and smart — and if they embrace fintech, along with the products, services and ideas it brings to the table.

That’s because legacy banks have an advantage other industries do not: People have trusted them for centuries with their worldly financial assets. When the stakes are that high, many naturally prefer to talk to a person, not an app. That trust is what is keeping banks on Main Street and, crucially, buying them time to catch up to their new rivals.

Banks must use their time wisely by leveraging their internal governance and controls to accelerate their AI transformation in a manner that will satisfy their regulators. And the need for action is urgent.

Fintech startups and their artificial intelligence are already disrupting key areas like retail banking, capital markets and wealth management, and in specific use cases like fraud detection, compliance risk, and conduct and credit risk. Efforts by legacy banks to build their own AI require time, energy and innovation that their complex bureaucracies cannot easily adapt to. Their Achilles' heel is their fragmented and inflexible legacy systems, and their data sits in silos — all of which considerably slows the pace of their digital transformation.

In this balancing act between legacy banks and fintech, regulators must play a constructive role.

Regulators need not be a force that hinders innovation. In this transition period, their challenge is to ensure customers feel the same confidence in AI-operated banking services as they do in a brick-and-mortar bank. Allowing innovation while providing protective guardrails is a balancing act in which explainability and fairness are key.

Much of today’s concern about AI implementation in the banking industry is heavily associated with accountability, governance and the risk management side of the operation. Regulators must ensure AI models are transparent and accountable. They want to know that the AI predictions are explainable and operate at reasonable confidence levels. That means there must be a human in the loop, overseeing and understanding AI decisions. Additionally, regulators over time should aim to foster a level playing field between fintechs and incumbents.

An imminent test of this three-way collaboration is the need for fintech regulations that address longstanding digital pain points, such as gender and racial disparities in loan approvals. Are the models producing decisions that show no hidden human-based bias for race, ethnicity, age or gender?

While all this is playing out, the savvy banks can still accelerate their digital transformation, in pockets, by placing strategic bets on fintech partnerships and acquisitions across areas like data security, wealth management and payments. This does not undermine, but rather potently enhances “relationship first” businesses.

While banks cannot match the fintechs in development and implementation speed, they must make up for that with agility in execution within their regulatory framework. According to McKinsey’s Global AI Survey report, banks are already displaying their ability to meet this challenge, with nearly 60% of financial services sector respondents reporting that their companies have embedded at least one AI capability in their systems.

More still needs to be done, and that agility in execution can be enabled by investment in cloud computing, data management and APIs for greater scalability and speed to production. The opportunity for success is unlimited.

Are the banks being disrupted? Yes. But can they also rise in this seminal moment to use AI to transform their organizations to enhance revenues, improve efficiencies and augment customer experience and outcomes? Absolutely.

Call it a constructive disruption.