Money20/20: Hummingbird on the Path to AI Enablement
In an exclusive interview with FinTech Magazine at Money20/20, Matthew Van Buskirk, Co-founder and CEO of Hummingbird Regtech, discusses how the company is enabling data to be labelled at ease through the use of artificial intelligence.
The Data Challenge
Hummingbird positions itself as an AI enablement company, addressing a critical challenge in the financial sector: the lack of well-labelled, clean training data.
“From the day we launched, we saw that deploying effective machine learning or AI capabilities in this industry is incredibly difficult because we don't have clean training data. Instead, we have thousands of ad hoc spreadsheets -- a data scientist's nightmare,” says Matthew.
The company's solution involves extracting and transforming this disparate data into usable, clean formats, creating a feedback loop where decisions made within the platform organically label data, which can then be used by customers to train their in-house models.
This year marks a significant milestone for Hummingbird as it begins deploying its own AI capabilities, leveraging developments in raw processing power from major technology providers.
“Our customer base has historically been very large fintechs running in cloud environments, but we're now expanding to support global tier-one banks"
Transforming Investigator Efficiency
“Historically, investigators spend about 90% of their time data gathering, cleaning, and doing paperwork, with only 10% dedicated to actual investigative work,” Matthew explains.
“We're really trying to invert that ratio by having data models and AI capabilities prepare all the information for them.”
“We're trying to be the human-in-the-loop platform,” Matthew explains. “The goal is to let humans do what they do best -- figure out what's going on, apply their intuitive know-how, make decisions -- and then let the computers run with it after that point.”
The platform's demonstration at Money20/20 showcased these capabilities, highlighting how seemingly simple automated validations and data processing can have profound implications for financial crime investigation efficiency.
What might appear as basic text field operations and automated validations represents a significant advancement in investigation methodology.
Market Evolution
The company's growth trajectory has seen it expand beyond its original customer base.
“Our customer base has historically been very large fintechs running in cloud environments, but we're now expanding to support global tier-one banks and other financial institutions,” Matthew notes.
This expansion requires the company to operate across diverse technical environments to meet varying customer requirements.
Understanding the impact of these technological advancements requires deep domain expertise, yet the implications for the financial services industry are significant.
“It's exciting to see this whole ecosystem of AI-enabled capabilities tackling these esoteric, behind-the-scenes, but incredibly important aspects of financial services,” says Matthew.
“The positive response to our demo shows that people understand what this technology means for the future of our industry.”
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