Build Versus Buy – How Will You Acquire Your AI for Financial Compliance?

Almost everyone reading this has used AI in one shape or another.

Some may be incidental users, browsing AI-generated search results or chatting with Siri and Alexa. Others are more invested, using ChatGPT to shortcut what used to be marathon Google sessions.

And then there are the heavy users: the ones with a supercomputer on their desk and agentic AI controlling everything from their morning routine to their retirement portfolio.

And I very much fall into the latter category.

It reminds me of when Google search first hit the mainstream. It changed our relationship with the internet and the data it contained. And we all looked to our work lives and wondered: why can’t we have the same capabilities there?

This time around, I think we’re more AI-enabled at work than we were search-enabled in the late ’90s. Many companies now offer limited access to tools such as Microsoft Copilot.

But the real question is: how can we use AI to unlock difficult, repetitive, manual processes in the workplace – especially in compliance? What’s happening under the corporate covers?

The Temptation to Build Your Own AI

I spend a lot of time talking to people about their use of AI and how they want to employ it. Very often, when I present them with a specialist product designed to alleviate back-office problems with AI baked in, they say: “We could do that with Copilot.”

But can they, really? A recent report from MIT helps explain why that argument rarely holds true. The State of AI in Business­­­­* paints a gloomy picture:

95% of enterprise GenAI pilots fail.

That’s a staggering number.

And the reasons are clear—it’s not the models that are at fault. It’s their integration into company workflows and the lack of understanding around how that should be achieved.

These systems don’t learn and don’t adapt over time. But when it comes to complying with strict, ever-changing financial regulations, the ability to adapt and further enhance should never be ignored.

Why Compliance Is a Special Case

Compliance software isn’t just about automation: it’s about trust, auditability, and resilience. You’re not just building a tool to make life easier. You’re building a system that must:

• Handle sensitive data securely
• Adapt to evolving regulations
• Provide clear audit trails
• Be defensible in front of regulators.

This is where “build your own AI” starts to look shaky. You might be able to prototype something with Copilot or a few Python scripts, but can you guarantee it will still be compliant in 18 months? Can you prove its logic to an auditor? Can you patch it quickly when a new regulation drops?

If the answer to any of those questions is anything less than a confident ‘yes,’ you may want to think again.

Is experimenting with AI really worth it when being non-compliant could set you back millions of dollars in fines and damage the reputation of your business?

Building vs. Buying AI – Things to Think About

But it’s not all black and white, of course. Building your own AI and grabbing it “off the shelf” both have their advantages and disadvantages. Here’s a breakdown of the key considerations:

Building In-House Pros & Cons:

Buying Off the Shelf Pros & Cons:

The Long View

The critical lesson is that solving a problem with AI means understanding the full end-to-end workflow, from how you acquire and store data, to how you process it, and how it flows into your target systems.

You need to learn from the outputs and improve the system over time.

Anyone who’s worked in a large company will remember a system built in-house that worked well for a few years, until the developers moved on. Then it slowly became a liability—less flexible, less useful. Eventually, a legacy.

Of course, any company can invest time and money in using off-the-shelf tools to automate workflows. But a specialist software vendor has spent thousands of hours testing, refining, and learning from real-world use cases.

The system you’re using in five years will be vastly improved over the one you initially bought. It will be maintained, patched, and upgraded with the latest tech.

When I think of old “build versus buy” projects, the vision in my head is of the Russian diesel-powered submarine Novorossiysk surfacing due to mechanical issues, because no one on board can fix them, limping slowly home to port. Is that how you envision your compliance efforts? Of course not.

To Be Continued

You’ve hopefully enjoyed this brief comparison of in-house and off-the-shelf AI systems, and now you have a better understanding of the benefits and risks of both. But wait, there’s more!

Stay tuned for part 2, as next time we’re planning to dig a bit deeper into Verint’s own finance-specific AI Insights and how they can help organizations stay clear of compliance and conduct risks.

In the meantime,  watch this webinar or read this executive perspective to learn how secure, explainable AI can supercharge compliance in any financial services firm.

Get in touch with us and see how Verint’s AI-powered financial compliance solution can help your business comply with strict, ever-changing financial regulations and avoid legal sanctions and reputational damage.

­*MIT NANDA – The GenAI Divide – State of AI in Business 2025 –https://mlq.ai/media/quarterly_decks/v0.1_State_of_AI_in_Business_2025_Report.pdf