29 May 2024

Power up your finance with AI

a man sat with a laptop smiling.

What is AI financing, and how can your team use it?

What is AI in finance?

Finance functions have a lot of power when shaping a business' future.  

Unfortunately, that means that a lot of a finance department’s time will be spent combing through data, processing that data and trying to get it into a fit state to be properly analyzed. Only then can the team take action. 

From credit and collections to risk and compliance, all these critical parts of the finance function use a lot of manual processes. Some of them cannot be taken out of the hands of people (especially compliance) but many of them can. That’s where AI can be a gamechanger. 

These tasks are important, but they’re also a lot of work, taking up a huge amount of time. You can’t ignore them, but they’re not the most fulfilling work, or the best use of the many talents a good finance team will have. 

AI is being utilized by more and more finance teams to take some of that load off. An AI can look at huge volumes of data, beyond what a human can, and ensure that when your team comes in, they’re focusing on the big picture. 

To be clear, this isn’t a substitute for the human touch. You’ll still need a qualified finance professional to take a look at your data and draw the right conclusions. You’ll also need to translate those findings into reports that can be used to communicate with the rest of the organization. 

But finance with AI is a fantastic way to keep your team’s focus on strategy, not just the day to day. 

Benefits of AI in finance

There are many key benefits of using AI in finance. 

The most common and obvious is the speeding up of certain key processes. For example, an AI can process lots of financial data, which is often in a format that’s hard for a human to properly understand and tidy it up.  Likewise, many mundane processes that operate on clearly data and defined rules, like applications for credit, can also be processed much faster. 

Cybersecurity is another area where AI can really help. AI in finance can offer enhanced risk management and fraud detection, spotting unusual activity, comparing it to older data. 

These flags can then be communicated to the relevant team member, helping stop fraudulent activity much faster. 

All of the above can help reduce costs, overcome key skill gaps and improve employee engagement. By enabling more accurate forecasting and reporting, AIs can create more investor confidence, and build up the strength of your company’s finances. 

Challenges of implementing AI in finance

Equally, there are some key challenges to consider before implementing any kind of AI solution. 

The biggest is data protection. Finance departments often deal in diverse countries, often with different data protection requirements. Any AI tool the team uses needs to factor this in. Some AIs are not as secure as they seem, and there have already been some cases of AI tools facing data losses. Use the same care as you would with choosing any other kind of solution and ensure they have the credentials and the credibility you need. 

Likewise, data hygiene is a concern. While finance AI’s can comb through a lot of data, they’ll make mistakes if that data isn’t kept in an orderly way with minimal data siloing.  

There are also some key ethical considerations, particularly if you’re going to engage in AI-driven decision making. AIs aren’t infallible. They can misunderstand data, like a human, and are also prone to bias. A human being should always be involved with any decisions, as they’ll be able to spot these issues and prevent them. 

How AI is shaping the future of finance

Many finance teams have gone digital and moved away from the old-fashioned spreadsheet only approach. However, now the challenge is in scalability. There’s only so much a single human being can do. With AI in finance, this can be overcome. 

AI is also driving several innovations in procurement and supply chain management, as their algorithms can minimize the need for human intervention. For example, purchasing data can be used to predict future demand, so inventory can be accounted for more easily.  

There are also career opportunities where AI and finance meet, and new skills to be learned. As the technology develops, we’ll likely see the skill requirements of a finance professional shift and change. They won’t need to have as strong an understanding of the data, but they will need to be able to work with AI effectively to stay relevant. 

Governance and regulation of AI in finance

As functions go, finance is one of the most strictly regulated. As a result, any solutions you bring in will need to match that.  

As a developing technology, AI doesn’t quite have the same level of regulation as other technologies, but the law is catching up. 

For example, Connecticut state privacy laws already grant residents the right to opt out of the use of automated decision-making if those decisions would be solely handled by AI. The California Consumer Privacy Act covers that even when it’s only used as part of human decision making. 

More broadly, the US Department of the Treasury released a report on how to manage cybersecurity risks that come from AI, and why financial institutions that are on the cloud already have an advantage when it comes to using AI systems effectively. This provides a solid benchmark to build out some best practice policies. 

Whatever AI usage looks like in your organization, it’s looking to be an important conversation for the future. You and your team should aim to stay on top of any developments and start seeing how AI factors into your digital transformation. 

AI-powered solutions in finance

Finance from MHR comes equipped with best of breed features, and that includes developing AI software. Leveraging Microsoft Dynamics alongside its new Copilot feature, we’ll help keep you on the cutting edge of finance technology. This can help you pull data together with a single prompt, simplify collections and payment plans, and even detect variants that can slow down your financial reporting. Much of this can be done through natural language processing, which means you don’t need to compete for the same skills in the talent pool that your competitors are fighting over. Your team will complete tasks quickly and with much less stress. 

Blog tags
Emma Reid headshot

Emma Reid

Content writer at MHR

Back to previous