Artificial intelligence has emerged as the great disruptor of the twenty-first century, and has begun taking significant ground in the financial sector. Many institutions are now leveraging AI-driven tools to make better lending decisions, automate trades, streamline customer services, and improve security.
“We’re already integrating tools that leverage AI to automate most of our data processes,” shares Jay Avigdor, President and CEO of Velocity Capital Group. “It helps us to better understand deal trends and to identify similar deal performance based on relevant data points. AI also gives us the ability to pre-approve deals and determine anticipated pricing so our underwriting team can prioritize a full-scope review. Overall, it’s allowed us to be one of the fastest in our space and increased our capacity to fund like never before.”
Velocity Capital Group is a direct funding platform located in Greater New York that funds small businesses nationwide, servicing over 15,000 clients since its founding in 2018. Under Avigdor’s leadership, Velocity Capital Group is setting new trends in the industry by merging finance with technology through automation, thus allowing a quicker and smoother process for merchants and brokers serviced.
“AI promises to increase both speed and accuracy in the financial sector,” Avigdor says. “We’re very excited about AI’s ability to automate almost all of our processing and, with proper programming, to anticipate various events in our funding process.”
Improving the relationship between advisors and investors
When it comes to financial advising, AI is taking the concept of the “robo-advisor” to new heights. In addition to empowering more intelligent chatbots that can provide service directly to clients, AI tools are also being called upon to assist human advisors.
“AI can serve as a powerful tool for financial advisors, analyzing a wide range of data points to provide the types of insights that allow advisors to provide better service to their clients,” says Mitchell Morrison, CEO and Founder of Eyeballs Financial. “We refer to those valuable insights as ‘night vision.’ Advisors with night vision know what their clients are thinking without the need for a live conversation.”
Eyeballs Financial’s innovative Eyeballs app is the first to deliver convenient, automatic, and secure insight on financial investments by providing up-to-date information drawn from both trusted advisor intelligence and artificial intelligence. The technology behind the Eyeballs app is the only US patent with Remote Inquiry Questions (RIQs), allowing it to provide up-to-date information on users’ financial portfolios and instant communication with advisors regarding questions or concerns.
“AI-driven tools can also cut down on the amount of phone tag that happens between advisors and their clients,” Morrison says. “If an AI-powered chatbot can answer the question, it does away with the need for a meeting. In addition, advisors can get intel on the types of questions that clients are posing to chatbots. If they repeatedly ask about money market rates, for example, it can signal the advisor to touch base with the client on that issue. If the advisor sees a client inquiring about Apple stock, he gains information that can be used to provide better advice.”
By allowing advisors to be more engaged with their clients without requiring more work, AI can also assist with regulatory compliance, especially related to Securities and Exchange Commission Regulation Best Interest (BI). In order to ensure that financial recommendations are in the best interest of the customer, SEC Regulation BI requires advisors to have an ongoing relationship with their clients that enables them to understand the clients’ evolving needs. As explained in a recent SEC Staff Bulletin on Regulation BI, developing an investment profile for clients should not be considered a “once-and-done exercise.”
Guarding against AI-driven biases
AI bias, which refers to unfair recommendations or incorrect outputs caused by training AI models with poor or incomplete data, has emerged as one of the main concerns associated with leveraging AI in the decision-making process. As financial institutions seek to deploy AI-driven tools to guide financial decisions, guarding against the discrimination that can result from AI bias is a key concern.
Making sure that AI-driven decisions are always reviewed by human representatives is one way to detect and guard against biases.
“There should always be a human element when it comes to AI, especially when it comes to making decisions about lending or funding,” says Avigdor. “Institutions must develop standards regarding the way AI functions and review performance regularly to ensure those standards are being met. Ideally, AI is used to remove 99.9 percent of the repetitive, copy-paste work and to pull in all the data needed to make an informed decision. At the end of this process, however, we have a human representative take over to review the end result and make a final decision. Adding key parameters to AI functions provides safeguards against AI biases and unreliability.”
AI is clearly reshaping the financial landscape, introducing opportunities for greater efficiency and productivity. Harnessing its power, however, requires financial institutions to carefully consider where and how it can best be deployed. Understanding its strengths and weaknesses will be key to developing effective AI integration strategies.
