While many hurdles still stand in the path to an AI-enabled banking future—data privacy concerns, the potential for bias and the proliferation of disinformation—the promises are much greater. The adoption of the technology will hinge on the industry’s ability to ensure the accuracy of outputs, integrate safeguards and ethical standards, and comply with global regulations.
It’s critical to be forward-thinking in developing AI-based solutions and Mastercard Signals has been working to apply generative AI to banking and payment processes. In its recent report, it looked at how generative AI could roll out in the coming decades.
Three Stages of AI
According to the report, there are three distinct phases of AI development. They include:
Immediate focus: Experimentation
Banks are currently focusing on internal gen AI applications—software development co-pilots, knowledge bots, operational efficiency drivers. These can serve as test beds, laying the groundwork for what’s to come.
Short-term focus: Building foundations
The next phase will likely involve constructing the architecture for more ambitious gen-AI initiatives, such as customer onboarding solutions—while remaining within a proof-of-concept context.
Mid- to long-term focus: Scaling up
At some point AI will produce applications that redefine customer interactions, like client-facing AI financial advisors. This could be contingent on better regulation: Developers will want to know the rules of the game, given gen AI’s risks.
Related to this last stage, some leading AI developers have explicitly called for more government regulation of their industry. This may have an element of protecting first-mover advantage, as generative AI’s current winners attempt to sideline the competition. But legal, regulatory, and even ethical clarity from regulators could reduce liability and potential missteps that may otherwise have consequences for their clients and themselves.
Fears of a Talent Shortage
One of the challenges for companies looking to build out generative AI is that the field has not yet developed a well of talent. Alongside infrastructure development, progress will be contingent upon a growing reservoir of AI expertise within the banking sector. The AI talent crunch, in particular, has been well-documented. Some 75% of companies for whom hiring AI specialists is a priority reported being unable to fill their AI talent requirements, according to a recent study from Amazon.
The development of that talent will help elevate the entire AI industry. “We’ve just scratched the surface of potential transformations enabled by generative AI,” said Ken Moore, Mastercard’s Chief Innovation Officer. “We expect that within the next year, it will gradually integrate into the operations and products of financial institutions and merchants globally.”