Will AI Revolutionize Regtech? Part 1: Faster, Easier, Richer

Check out the ways artificial intelligence and machine learning are playing increasingly important roles in fintech and regtech.

Later this year at the NSCP National Conference, I’ll be speaking on a panel with Jane Stabile and Andrew Siegel on the topic “Will AI Revolutionize the Financial Services Industry?” To help promote the event, I’m publishing a series of blog posts on AI and its impact on the industry. To begin, let’s talk generally about the current state of AI development in fintech.

The Rate of AI Use Is Increasing, and You’re Already Contributing to It

Deloitte (in partnership with PitchBook) publishes a series called Private Financial Markets: The Road to Next that tracks market trends affecting investor-backed private companies. Recently, it focused on the fintech space, which is trending among wealthy, private investors. As the Deloitte report notes, “[k]ey innovations exerted competitive pressure across the financial services spectrum, often accelerating existing trends.” But often we don’t even know when we’re using AI. For example, many of us use LinkedIn on a regular basis (if you’re in business development, it’s daily). An employee searching for a job and an HR manager looking for a new hire on LinkedIn are both using LinkedIn’s AI engine.

In a white paper published by SambaNova Systems, an AI developer, the firm quotes an IDC report from 2020, saying: “Businesses will need to adopt AI technologies not just because they can, but because they must—AI is the technology that will help businesses to be agile, innovate, and scale.” At Joot, we find this to be true in the fintech and regtech space. We’re collaborating with other firms on projects such as digitizing interactions between general partners and limited partners to private funds, developing compliance technology, and launching new investment products based on technology that leverages large data sets and AI. We’re also exploring our own AI solutions in the ad tech space. All these efforts are driven by demand from financial services firms that are looking for ways to scale their business with limited resources, including people and capital.

AI Is Becoming More Accessible

In May 2021, the Artificial Intelligence Report announced that Microsoft’s Power App Ideas partnered with OpenAI to create a no-code/low-code service to translate spoken text into code. According to the article, the new feature, which is powered by GPT-3, could allow a nontechnical employee to describe a programming goal using conversational language. As noted in the article, “There’s massive demand for digital solutions but not enough coders out there,” and this type of technology could make it easier for companies “to do more with less developers.”

As a nontechnical startup founder, I really appreciate these types of developments. When I first launched CCO Technology LLC (now known as Joot), I was searching for a technical cofounder but couldn’t find one. Instead, I had to leverage external developers until I could hire Joot’s internal team. I toyed for a while with learning to code myself, but I realized that was an uncertain and time-intensive path. With a tool like this, the path would have been more accessible. As AI implementation becomes easier and faster, we expect the pace of AI development to continue its exponential curve.

Investors Are Pouring Money into Fintech

Perhaps the greatest indicator of future disruption is the amount of capital pouring into fintech, including AI-based companies. The Deloitte report notes that 2020 saw the largest sum ever—$18.2 billion—invested in fintech expansion-stage companies, and the industry is on pace to break that record in 2021. As of March 31, 2021, the industry has seen over $9 billion in deal value, 14% of all financing rounds for the quarter! Valuations are up, the number of deals is up, and more unique investors are pouring into the space. As any entrepreneur knows, innovation requires four key inputs: ideas, effort, time, and money. One can even argue that innovation requires only ideas and money because both can convince others to put their time and effort into development.

In Part 2, I’ll discuss how financial services firms are currently leveraging AI in their daily operations. Part 3 will provide some practical advice on how your firm can start an AI project. And in Part 4, I’ll wrap up the series by discussing ethical implications of AI development and implementation.

Originally published on joot.io.

The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.

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