A version of this article first appeared in the November BAI Executive Report: Harnessing the power of AI in banking. Find more insight within on careful adoption of artificial intelligence, automation and machine learning, from SMB examples to creating core efficiencies, expanding lending use cases and more.
The rise of artificial intelligence (AI), and more recently generative AI, at banks and credit unions has already captured the industry’s attention, and its use within personal finance creates unique possibilities and potential pitfalls.
Even as healthy skepticism persists, advocates stress that AI creates cost-saving operational efficiencies and eases the burden of data overload on a staff that might instead expand human-centric talents. Importantly, AI’s supercharged boost allows banks and credit unions to readily present well-suited account features and products for each of their customers based on real intelligence instead of guesswork, including drawing from other shopping behaviors and interests.
Personal finance is, after all, ‘personal’
Cautious optimism peppered with a reality check is shared among financial service professionals and the public they serve. According to J.D. Power, 54% of surveyed banking customers say they have used some version of a generative AI tool, and 32% say they have a complete understanding of AI. Gen AI digests large- or small-language models to recreate “new” text or graphics, for instance.
This growing level of comprehension and adoption has fueled a largely positive view of the technology, as 50% of customers are optimistic that AI will at least somewhat enhance their lives, says J.D. Power. But the survey also reveals that customers can’t quite shake concerns about security, an increased risk of fraud and loss of human support.
That’s where banks and credit unions can continue to deliver. Today’s customers, especially young Millennials and Generation Z, increasingly want to feel empowered in their own financial wellness and as they navigate digital banking and financial planning, yet they strongly desire a partnership with their bank or credit union for value-added guidance when appropriate, as BAI findings show.
We already know that banks and credit unions are logging more engagement with AI, and more recently, gen AI. Fraud-detection tools and investment analysis platforms are a couple of examples of this technology’s growth within banking institutions. But those operations are largely behind the scenes.
Personal finance poses a distinct challenge as individual goals and risk tolerance vary greatly. This uniqueness makes a “one-size-fits-all” solution, often a hallmark of fast-acting AI, not only impractical but potentially detrimental to a bank or credit union’s reputation for understanding their customer, detecting nuance within customer engagement and being able to pivot quickly.
A proponent talks about the human and AI balance
BAI grabbed some time with Brian Gunn, chief revenue officer of EarnUp, creator of an AI-powered customer platform that banks and credit unions layer within their own offerings. The platform’s focus is on debt management and other personal finance goal setting and measurement. Gunn embraces what AI can offer in financial services but not without advising institutions to value human capital and consider potential risks before forging ahead.
BAI: You consider AI as a co-pilot that very much keeps the human banking professional, especially one offering financial advice, engaged. Talk about this relationship.
Gunn: AI excels at processing massive amounts of data at lightning speed, identifying patterns and trends within financial data that might escape even the most seasoned human advisor. These AI-powered insights can translate into actionable tips tailored to an individual’s unique financial situation, including recommendations for investment strategies, debt management, budgeting and savings, and fraud detection.
However, while AI offers valuable insights, it’s important to remember that it is still a tool. Financial decisions often involve complex considerations and emotional factors best navigated with the guidance of a human advisor. The ideal scenario is one where AI augments the expertise of a human advisor, providing data-driven insights to offer more-informed recommendations. But the human remains the gatekeeper.
BAI: What are some common uses of AI for financial wellness or advice?
Gunn: Consumers are leveraging AI for various financial needs, including personalized budgeting assistance, simplified mortgage processes, improved credit score management and easier investment decisions. These technological advancements allow even novice investors access to sophisticated financial planning resources traditionally reserved for wealthier clients who work with human advisors.
BAI: Are there potential drawbacks when relying solely on AI for financial advice?
Gunn: While AI can analyze data and identify trends, it lacks the human touch and emotional intelligence that a skilled financial advisor can provide. AI may not fully understand the nuances of an individual’s personal values, risk tolerance and long-term aspirations. For example, AI might struggle to grasp the emotional implications of a particular financial decision or the subtleties of an individual’s personal goals.
A human advisor can offer a more comprehensive approach to financial planning, considering an individual’s entire financial situation and personal circumstances. Context matters.
BAI: You’re perhaps putting even greater value on what humans can bring to the table during this period of fast AI growth, which maybe helps soothe some of the trepidation around this technology?
Gunn: One of the significant advantages of working with a human financial advisor is the personal touch they bring. They take the time to understand specific financial situations, goals, and risk tolerance, ensuring their advice fits the client’s needs.
In contrast, AI-powered financial advice often feels more automated and uniform. While these algorithms can analyze data and provide recommendations, they may miss the finer details that make a situation unique.
Human advisors excel because they possess emotional intelligence, allowing them to relate deeply to what an individual is going through financially. They can provide reassurance during challenging times and maintain focus on long-term goals. Having an experienced advisor listen and offer guidance makes tackling significant financial matters less overwhelming.
BAI: What do you predict for the future of AI in financial advice?
Gunn: The future of AI in financial advice is bright. As AI technology continues to evolve, we can expect even more sophisticated tools that not only analyze data but also understand and respond to financial goals and risk tolerance in a more nuanced way.
Some of the advantages of AI-driven financial guidance include accessibility and affordability compared to human advisors. AI can quickly sift through vast amounts of data, offering personalized suggestions that fit individual needs and aspirations. This is particularly beneficial for individuals who may not have had access to financial guidance before or those just starting to plan for their futures. Additionally, AI can provide 24/7 support, allowing individuals to receive guidance at any time and from any location, a convenience factor that is particularly appealing.
BAI: There’s a particular growth area you’ve targeted, generative AI, yes, but also Retrieval Augmented Generation, or RAG. What is this and how can it impact financial advice and financial management?
Gunn: Unlike traditional AI, which primarily classifies or predicts based on existing data, generative AI can produce entirely new data, ranging from text and images to music and beyond. This capability enables it to craft personalized experiences, generate realistic simulations and even assist in creative processes.
Building on that idea, RAG is an advanced technique in natural language processing. It combines the strengths of retrieval-based and generative models to provide accurate, contextual and up-to-date answers from vast databases with generative models that create coherent, contextually appropriate responses, resulting in highly accurate and relevant answers to financial inquiries.
As these technologies continue to evolve, generative AI and RAG hold the potential to revolutionize financial services by offering innovative and highly adaptive solutions tailored to individual needs.
One example is enhancing homebuyer readiness by crafting bespoke guides for first-time homebuyers, detailing each step toward homeownership. These guides can encompass budgeting for a down payment, managing credit scores and exploring mortgage options. Additionally, interactive simulations can illustrate the impact of various saving strategies, helping potential buyers understand how their financial choices affect their homebuying readiness.
BAI: You also see scope for generative AI and RAG helping to democratize who has access to financial services, which also helps banks and credit unions add to their rosters of customer prospects. Talk about these use cases.
Gunn: Generative AI and RAG can also offer “second chance” support. For individuals previously denied a mortgage, financial institutions can offer tailored advice to bolster their financial profiles. AI tools can scrutinize credit reports, identify areas for improvement and propose personalized action plans designed to enhance their loan approval prospects.
Another example is strategic debt management with dynamic debt repayment plans. Generative AI and RAG can devise flexible debt repayment strategies that consider factors such as interest rates, minimum payments and income levels. These plans prioritize debt reduction effectively and track progress.
Banks and credit unions can also offer debt consolidation insights. AI can evaluate the viability and benefits of debt consolidation based on an individual’s specific financial situation. Customers receive detailed analyses and visual representations of how consolidation could impact their overall debt burden, aiding them in making informed decisions.
BAI: Sum up what is clearly your optimism for AI growth, alongside continued human significance, and the risk to financial institutions for lagging in AI adoption.
Gunn: While AI is not yet a complete replacement for human financial advisors, it is undoubtedly reshaping the financial landscape. The combination of AI’s data-driven insights and human advisors’ expertise offers a powerful approach to financial planning.
As technology continues to advance, the future of AI in financial advice looks promising, making it an area worth keeping an eye on.
Rachel Koning Beals is Senior Editor with BAI.