Financial services organizations, particularly larger ones, have long been adopters of AI and deep learning technologies to make their complex operations more efficient, improve risk management processes, reduce fraud and improve the customer experience.
Investments in emerging generative AI technologies are still relatively new, but it’s expected to grow rapidly, offering banks and other organizations new and powerful tools to do everything from summarizing content to answering questions via chatbots to create content.
“That means generative AI in banking could rapidly and cheaply (once the models are deployed at scale) generate hyper-personalized products and services, or accelerate software engineering, IT migration, and modernization of programs,” Miriam Fernandez, associate director of financial institutions for S&P Global Ratings, wrote in a report late last year. “It could also augment humans’ abilities, through AI chatbots or virtual assistants.”
It could also help level the playing field between the larger – and much more resource-rich – institutions and small ones that have similar challenges but fewer options.
Enter Hapax
A startup called Hapax, armed with $2.6 million in seed investment, launched Wednesday with a generative AI tool aimed at the financial services industry. The platform is designed to leverage generative AI to deliver industry-specific information, decision-making capabilities, and usable assets to banks and similar organizations.
It also is aimed at bridging the “information-access gaps” between big and smaller banks, according to Hapax officials. Small and midsize banks and credit unions, which can’t invest as readily in skilled employees and technology as their larger brethren, rely greatly on consultants and what Hapax calls a “best guess approach” to run their complex businesses and stay compliant.
Hapax’s tool will make it easier, cheaper and faster to access the accurate and validated information they need. Financial services institutions, in their highly regulated industry, can’t rely on off-the-shelf AI tools that are built using publicly available large language models (LLMs), according to Hapax CEO Tom Ferries.
“Hapax is built for bankers based on real, validated conversations with peer bankers,” Ferries said in a statement. “Each response also includes citations, allowing further confirmation that the information and recommendations are correct. This will change how banks work; particularly small and mid-sized banks that find themselves struggling with the resources and expertise to keep up with an ever-changing regulatory and competitive environment.”
Trained on Industry Data
Hapax is looking to differentiate itself in a highly competitive space with the data used to train its LLM. It’s using 13 years of proprietary data through a partnership with CBANC, a Texas-based network of more than 8,500 financial services institutions and 600 solution providers. The dataset includes more than 20,000 documents, 10,000 hours of videos and 230,000 conversations between bankers that include questions and validated answers.
All this creates a LLM that is trained for the financial services industry, according to the startup.
More than 20 banks, including Capra Bank and American Bank of Commerce, are beta testing the generative AI tool. Other banks interested in trying out Hapax’s offering can sign up for the waiting list.
Hapax’s $2.6 million in funding was led by RHS Investments. The startup also said that Hank Seale, founder and CEO of CBANC, joined the company as board chairman.
Generative AI and Banks
S&P Global’s Fernandez noted that numbers from IDC showed that last year, spending on AI was expected to reach $166 billion – with banking accounting for about 13% of that – and will grow to about $450 billion by 2027.
“The ways in which generative AI will be used by banks is likely to hold some surprises, but it seems certain that the new technology will result in both an evolution and an expansion of AI’s role within the banking sector,” she wrote.
The industry will be cautious, with banks testing generative AI models and investing heavily in them for the next two to five years before scaling deployments and taking on more transformative projects. That said, Fernandez wrote that the financial services sector will be among the sectors to be most effected by the technology, with it adding $200 billion to $340 billion in value every year.
The largest banks already are moving quickly to invest in AI, according to a report late last year by Evident, a platform that benchmarks and tracks AI investments in the financial services sector. Evident pointed to JPMorgan Chase, Capital One and the Royal Bank of Canada as the top firms in their investments and uses of AI.
Early Warnings
However, as banks grow their investments in generative AI, they’re also being cautioned about the dangers. The U.S. Treasury Department last month warned that the industry will be at a higher risk of fraud in these initial days of the technology due to an early advantage by threat groups using generative AI capabilities in their attacks.
“As access to advanced AI tools becomes more widespread, it is likely that, at least initially, cyberthreat actors utilizing emerging AI tools will have the advantage by outpacing and outnumbering their targets,” the Treasury report said.
