In the world of financial technology, AI poses questions, heightens efficiency, and encourages ingenuity

This article was written based on discussions from the latest Bloomberg Women in Fintech event. To learn more about the series, please email [email protected].

While AI has been a buzzword for some time, the uncertainty and rapid changes stemming from the global pandemic have brought the technology’s benefits and challenges to the forefront. Within the multitude of applications, several focus areas are helpful for the fintechs in particular, keeping in mind how humans and AI can work together to empower the other.

The opportunities for AI to both assist in a tumultuous working environment and heighten human efficiency were under discussion at the latest panel hosted by Bloomberg’s Women in Fintech. There are many details to consider with a constantly evolving technology, particularly surrounding bias and security, but according to panelists, it is essential that companies look to integrate AI holistically, ensuring automation bolsters their business and empowers employees to do their best work.

Adapting to change

When implemented with a company’s processes and business needs in mind, AI can facilitate different digital transformations, allowing for everything from anticipating and adhering to new regulations to using predictive technology to save for and past retirement.

Given the current turbulent and unprecedented environment, it’s especially worthwhile to consider how AI can assist: accommodating and adapting to remote work and addressing other changes that have come with this new reality. And many of these adjustments, especially when assisted by automation, can be helpful in the long term. As systems are examined and reconsidered, prior ways of working are being streamlined. Processes that weren’t gaining interest or moved slowly are now popular and expedited as a result.

Sana Khan, Analytics & AI Solutions Lead for Azure Data & AI at Microsoft, explained that, in past months, the use cases for AI that already existed within financial services have been expedited. “Some of the processes that we’ve been trying to get in front of customers for the past year and a half have now become priorities,” she said. “What used to take months is now being accomplished and accommodated in two or three weeks.”

As COO and Co-founder of Artis Technologies, Lena McDearmid has experience advising clients on legacy systems and architecture, and the need to update to make way for new technology. “There’s a need for a single source of truth at these companies, particularly when considering alternative data sets and the volume of information that’s being analyzed,” she said. “The platform is critical, to be able to benefit from automation and machine learning. Companies need to shift to support AI, allow for scalability, and adapt to make the most of their data.”

Hear more about the shift in the digital environment:

Humanity of work

Any discussion of AI must include the human element: what human tasks can the technology replace and what requires human ingenuity and thought? The current climate provides an opportunity to add humanity to workflows and interactions with clients, which AI can help facilitate and customize.

“AI has always had a seat at our table at Artis,” said McDearmid. The company’s approach to personalized customer experience is built into their models and strategy, all made possible through AI. “The benefit of that is that we’re not forced to play catch up with our infrastructure and platform, so we’re able to focus on product development but take it in a whole new direction. We want to leverage the information we’re getting from all our end users, and make sure all their needs are being met. By optimizing the way we develop products, complemented by AI, we can ensure the experience is improved for all our users, not just most of them.”

For Khan, in order to measure success in adoption of the technology and the efficacy of its capabilities, it’s key to integrate AI, instead of seeing it as separate. “The way I look at this with customers is to see it as an analytics journey. The way we measure success is often by adoption of the solution, not just in how it’s being used internally, but also externally by customers. It’s also important to consider the cycle of data: whatever information is coming through our AI capabilities – how has that data been used to further improve the application? It’s a lot like how profits are reinvested to support and grow value.” Success is also dependent on outside factors, like market slowdown or the internal culture of an organization, but it’s important to consider how automation can fit within a company’s existing goals, not as a standalone element.

Hear more about increasing usability of AI:

Considering risk

There are a number of risks and potential drawbacks to consider when looking at the rise of AI and how large a role it can and does play. Aside from the often-discussed existential risk to human jobs, there is the possibility for bias and programming errors, as well as the unforeseen errors that come with any quickly and constantly evolving technology. For those trying to drive adoption of AI in their businesses, unclear ROI can also present a challenge, particularly in early stages when determining how automation can best complement existing processes and strategies.

At Bloomberg, as Naz Quadri, Global Head of Data Science and Alternative Data Practice, explained, it’s important to always be planning for technology, instead of fearing or reacting to it.

Using a recent study on facial recognition software as an example, and its tendency to favor white male faces, he explained “it wasn’t a function of the modeling, but of the data it was fed. Because there were more examples of white male faces in the data, the machine got much better at recognizing them. This is one of many reasons why the human element and diversity in the teams that build and manage AI is so important, and should be part of planning moving forward.” Keeping these extenuating factors in mind is crucial for the development of AI, and ensuring it’s used in an effective, constantly improving way.

Hear more about AI’s role in the analytics journey:

Broader applications

There are multiple trends and developing use cases for AI within the fintech landscape moving forward, like forecasting, explainable AI, and fraud detection, just to name a few. As the technology and its applications continue to evolve, business strategies can grow and be tailored in tandem.

It’s also important to note this is widely considered a transition moment for AI, with the technology moving from a specialized sphere into more broad, widely understood applications, which allows for more opportunity. As Quadri predicted, “as you see the barriers to entry and understanding come down, we’ll be able to unleash more human capital and make bigger strides in how we customize and use automation.”

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