Council Post: Financial Institutions: Considering Which Type Of AI To Use (2024)

CEO and Co-Founder of Posh AI.

In October, the White House released an executive order outlining steps toward safe, secure and trustworthy development and use of artificial intelligence. The executive order outlines specific AI risks and regulations that different agencies and institutions must implement within the next 90 to 365 days.

But it’s not only government agencies and institutions that need to care about the executive order. Financial institutions have been rushing to adopt AI products in response to the rapidly changing market. New banking trends have been pushing companies to adapt to newer generations through personalized experiences while also reacting to new cybersecurity threats. At the same time, consumers expect more flexibility, personalization and convenience in their banking experiences.

However, a lot of AI products currently on the market are created based on hype, and they’ve become catch-all pursuits that lack attention to detail. Upcoming AI guidelines, soon-to-follow regulations and critical market changes require financial institutions to scrutinize both partners and solutions to ensure their AI implementation succeeds.

Most AI solutions fall into one of two categories: horizontally focused or vertically focused. Financial institutions need to understand the key differences between these types of solutions to partner with the right providers.

Horizontally Focused AI Solutions

Horizontally focused AI providers offer AI services or products with a broad range of applications. Often, they quickly solve common problems. As such, they’re usually easy to implement and can be applied to a wide range of businesses across industries.

For companies that are looking for simple, turnkey solutions and need them to be deployed on a wider scale in a shorter amount of time, horizontally focused AI providers may be the right choice. These solutions can also be a great place to start for organizations who are trying to learn more about AI and better familiarize their company with it. However, these types of solutions may not have as much accuracy or efficiency, which could be detrimental in certain workflows.

Vertically Focused AI Solutions

A vertically focused AI provider operates within a niche market. It holds targeted insights, expertise and specialized services within a particular domain. Where horizontally focused providers look to cover a wide range of workflows, a vertically focused provider has a focused target audience and drives its solution based on specific use cases.

For industries with more regulations and specific nuances, vertical AI providers tailor technology to a company’s specific needs. Take the financial services industry for example. There are multiple regulations and industry specificities that must be met with a higher degree of scrutiny. Therefore, any technology that a financial institution integrates must have the right security, practices and priorities in place.

Especially in combination with some of the upcoming best practices and regulations that will come from the new executive order, financial institutions are responsible for ensuring their AI solutions follow these guidelines.

Four Considerations When Shopping For AI Solutions

When looking for an AI solution, companies need to look for more than just a vertical or horizontal focus. Here are four recommendations when exploring AI partners:

Beware Of Bolted-On Generative AI

Many vendors right now are jumping on the AI bandwagon. As such, they are bolting AI onto their existing products to solve problems. This can be compared to a rocket car.

A rocket is great for going fast, and a car is great for transportation. But if you want your car to go faster, attaching a rocket to it isn’t the right strategy because of its impracticality and lack of safety. Similarly, attaching AI to an existing value proposition or product doesn’t necessarily provide value-generating applications of AI that are secure, scalable or practical.

Scrutinize Providers Around Data Security

AI brings a variety of new security and public domain risks that financial institutions need to consider in their technology choices. Look very closely at the data and cybersecurity practices that your AI providers follow. For example, any AI solution used by a financial institution should keep controls such as RBAC, encryption standards and security standards at the forefront.

That’s one of the reasons why it’s so important for certain industries to find AI solutions that are purpose-built for the industry. They can help implement strong risk and threat mitigation controls to protect, secure and encrypt customer information specific to that industry.

Create A Tailored Risk Framework For AI Solutions

Risk frameworks aren’t new to the industry, serving as a method to understand the risks and opportunities of implementing new technology. AI solutions should have a tailored framework that evaluates a provider’s transparency, AI talent on staff and changing value propositions in relation to the latest technology. Companies should also scrutinize demos, references and case studies to determine if their AI promises are truthful.

Get Ready For Upcoming Regulations

While agencies and creators of AI models will be directly impacted by upcoming guidelines and regulations, financial institutions themselves need also to prepare. At the bare minimum, financial institutions should familiarize themselves with NIST’s current guidelines, seen in the AI Risk Management Framework, and be prepared for the companion piece coming this summer.

Not only will that keep companies thinking about best practices and guidance from the premier thought leaders in the industry, but also it will enable them to have more impactful conversations with vendor partners and understand their adherence to these best practices.

As innovation continues to accelerate, more updated iterations and use cases of AI will continue to arise. The institutions that are likely to get ahead will understand that it isn’t just about what AI can do, but also what kind of AI is right for them.

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