AI tools have flooded the market over the past year, with headlines and public sentiment ricocheting between acceptance, support, opposition, and downright hostility. While we are beginning to see early attempts at regulating generative AI, the technology is continuing down a path of exponential growth that promises both incredible opportunity and high risk for exploitation.
Like most fields, there is no question that AI will play an increasingly significant role in the financial services industry. So how can we harness developments to improve the financial lives in the U.S. and beyond? And how can we protect users from bad actors and the biases that seem inherent in today’s generative AI tools?
While the answer will be ever-evolving, there are several steps we can take today.
First the why: In today’s shaky economic climate, the smart and thoughtful application of generative AI can make much-needed personal finance tools more accessible for countless Americans. Individuals and families across the country report a lingering hangover from high inflation and growing concern around finances, despite high-level economic gains at the macro level. In fact, over 80% of Americans are in crisis or struggling financially, with unmanageable financial stress climbing 34% over the last year. If done right, integrating AI within financial services and planning can play a transformative role and reach more than ever before.
And yet, proper regulation and enforcement of AI are years away, putting the responsibility on the private sector to leverage these emerging technologies responsibly and implement user-first policies and procedures.
Eliminating bias within existing and new platforms is one of the greatest obstacles on the technical side. Since generative AI is trained on massive amounts of data available on the internet, its outputs are influenced by any biases present — ranging from inconsequential to downright dangerous. Another limitation is that AI may generate text based on untrustworthy or outdated information, making the information provided potentially inaccurate.
What’s more, the internet is rampant with bad actors who are already using generative AI for their own ends in the industry. Some seem innocuous, like the myriad of point solutions that promise to help users clear up specific financial challenges. Yet these are often pushed out as minimally viable products with little to no vetting ahead of time, and users are left essentially investing their money in a black box.
And finally, data privacy risks are an increasing threat – from bad actors stealing information to the longstanding issue of how data mining remains largely unregulated.
Despite these daunting challenges, there is a clear path forward to ensuring generative AI is both safe and effective for users, in the financial space and beyond.
At a micro level, companies must be mindful and transparent in their use of open vs. closed AI. Closed models can better contain bias and be fine-tuned to yield more accurate outputs than the open models currently available, which often hallucinate facts. Critical to these discrete models is a curated knowledge base from which the AI system can generate responses. This requires a distinctly human hand to oversee AI governance — from building and managing the source database to continuous testing of the system, to protecting user data.
On the macro scale, there are an increasing number of data alliances and self-regulation groups emerging with the goal of advancing research in AI safety or developing policy guidelines. While some of the biggest names in technology are involved, there needs to be greater coordination among these myriad associations. By working together toward clear, universal AI governance, AI companies can be held accountable and users’ best interests can be kept at the forefront.
With these types of measures in place, we can more effectively harness the potential of AI. Just look at rising generations, who have a strong preference for self-service options and would benefit most from a blended version of human and AI financial support.
While formal regulation and enforcement may never be achievable given the rapid progression of generative AI, it is up to private companies — both independently and as a collective — to ensure their products best serve their end users. Doing so presents an unprecedented opportunity to integrate AI into the financial services industry in a way that can truly transform lives at scale.
