In the complex and rapidly evolving landscape of financial advisory, Artificial Intelligence (AI) tools are increasingly becoming integral. Large language models (LLMs) and AI-driven marketing techniques are offering profound benefits, yet they are also presenting new risks that have garnered the attention of regulatory bodies like the Financial Industry Regulatory Authority (FINRA) and the U.S. Securities and Exchange Commission (SEC).
Recent discussions highlight emerging threats such as "AI washing," where firms exaggerate their AI capabilities; hallucinations, where models like ChatGPT produce false information; and ethical concerns related to using personal data for targeted marketing. Brad Ahrens, Senior Vice President of Advanced Analytics at FINRA, stressed the dual nature of AI's potential at a FINRA advertising regulation conference held on September 27. “We have to understand not only how these models are working, but also what are the opportunities and what are the risks within each of the models that are out there, especially in generative AI,” Ahrens stated.
A week prior, SEC Chair Gary Gensler issued a cautionary note during his video "office hours" on September 19. In a somewhat humorous comparison to the film "Her," he warned against over-reliance on AI, stating, "Regulators, market participants, I believe, need to think about what it means to have the dependencies of potentially 8,316 brokenhearted financial institutions on an AI model or data aggregator." Gensler underscored the importance of keeping the emotional and functional integrity of capital markets intact.
Specific concerns have arisen over AI's capacity to mislead. In March, the SEC charged two advisory firms for overstating their use of AI. Issues such as hallucinations in large language models and AI "deepfakes" also pose substantial risks. Authorities are now scrutinising how firms use AI for dictation services during meetings, particularly regarding potential data leaks into public learning models like OpenAI’s ChatGPT or Anthropic’s Claude. Ahrens pointed out, “If you’re using openai.com or anthropic.com, you should be concerned if your employees are using that, because there is a possibility that you could leak data back into the models. It does happen.”
Another area under the microscope involves the use of chatbot-like AI for customer service and internal queries. Many firms are employing large language models to answer questions ranging from investment disputes to regulatory clarifications. Ahrens described a typical use case where a firm might input, “What do I do when tenants are in a dispute?” and receive precise guidance from the AI. Although FINRA has not explicitly condemned this practice, it has emphasized the importance of human oversight and stringent compliance measures.
Philip Shaikun, Vice President and Associate General Counsel in FINRA’s Office of General Counsel, stressed the need for supervision. “How are you going to ensure that this gen AI is functioning as it's supposed to? In other words, how are you going to supervise its use? You’re going to want to be sure that you’ve got certain types of procedures, a human in the loop, spot checking.”
Both regulatory entities insist on close monitoring of technology vendors who may integrate AI technologies post-contract signing. Amy Sochard, Vice President of FINRA’s Advertising Regulation Department, alerted firms to routinely review vendor contracts, especially if there have been technological updates introducing AI.
In May, FINRA updated its Rule 2210 guidelines to include AI and chatbots in communication with investors, pointing out that while client-facing AI usage remains limited due to risks, hyper-personalisation in advertising is on the rise. This trend uses machine learning tools to analyse clients' digital footprints, potentially leading to exploitative advertising. Rachael Chudoba of McCann Worldgroup addressed this during the FINRA conference, emphasising that teams should be well-versed in the ethical implications of AI. “It’s opening up the door to exploitative advertising tactics where advertisers may know more about a digital user than the person knows what they're giving up,” Chudoba noted.
Concurrently, FINRA is leveraging AI for sentiment analysis of public responses to proposed regulations, employing sophisticated AI tools to categorise and interpret the sentiment behind the thousands of comments it receives. “It’s not just a simple sentiment that you’re used to — like happy, sad or myth — it’s more figuring out: who wrote it, where is it coming from? Then, we cluster those together. And then we actually go deeper into the sentiment,” Ahrens explained, adding that numerous use cases are currently underway.
As financial institutions navigate the integration of AI, regulators continue to adapt and respond to both the innovations and implications, striving to strike a balance between technological advancement and ethical responsibility.
Source: Noah Wire Services