Money Matters

Risk and opportunity in generative AI: Tips for SaaS CFOs

Discover how generative AI presents both risk and opportunity for SaaS CFOs. We offer tips to navigate this dynamic landscape.

As a CFO, one tiny mistake in your department can create a cascade of problems. SaaS finance is a tightrope walk of delicately balanced processes and workflows. 

That’s made some finance leaders hesitant to adopt cloud software with generative AI.

This hesitation comes at a real cost since generative AI is one of the most powerful accounting tools currently available for finance teams.  

In this article, we’ll help you gain an understanding of generative AI for SaaS finance, identify potential risks associated with this new technology, and explain how cloud AI tools can transform your department’s productivity and boost your organisation’s cash flow.

Here’s what we cover:

Understanding generative AI for SaaS finance

At this point, it’s probably safe to say you’ve heard of AI.

In a nutshell, it focuses on training software to be able to perform tasks that would ordinarily require a human. 

Examples of automated processes in finance include screening for transactional anomalies to detect fraud, or automatically routing an invoice through the proper approval chain.

Generative AI takes that one step further.

Cloud accounting software equipped with generative AI uses machine learning (ML) algorithms to not only work with and analyse data but also produce original content from data inputs, including:

  • Reports and financial statements
  • Customisable role-based dashboards
  • Revenue recognition readouts
  • Detailed ‘if-then’ SaaS forecasts, and much more

Embracing generative AI allows SaaS CFOs to drastically cut the cost and hassle involved in all kinds of accounting processes. 

But most importantly, it acts as a valuable partner that can offload tedious repetitive tasks so you and your team can focus on strategic initiatives rather than busy work.

The significance of generative AI for SaaS accounting

The generative AI revolution has permeated various industries, including SaaS finance.

This ground-breaking technology opens up new opportunities for SaaS CFOs to rapidly analyse and interpret vast amounts of data. 

This is important because your role has slowly merged with that of the data scientist–you’re responsible not just for crucial financial processes but for working with massive amounts of customer and financial data as well.

By harnessing generative AI, CFOs can gain valuable insights into customer behaviour and preferences, enabling them to keep churn to the bare minimum.

For recurring revenue SaaS companies, there’s almost nothing more crucial than managing churn and maximising your annual and monthly committed revenue.

Generative AI’s emergence marks a pivotal moment for SaaS CFOs seeking to optimise their financial operations.

We’ll dive deeper into its robust functionality in a moment. 

But first, let’s examine a few potential risks involved with these tools.

Identifying the potential risks associated with generative AI

To ensure a smooth transition into the generative AI era, SaaS CFOs need to proactively identify and mitigate potential risks. Your financial processes are at the heart of your company’s success–you can’t take the risk of an accounting mishap lightly.

Below are some of the main risks SaaS CFOs should be aware of when contemplating automation, along with some tips for solving them.

A lack of sufficient training data volume might result in biased outputs

Cloud accounting tools with AI and generative AI require very large datasets for initial training. This helps the software get acquainted with your data in order to work with it accurately and effectively.

However, if you only have a small pool of existing historical data, you run a high risk of skewing or biasing your outputs. For instance, say you’re a newer company making a hard marketing push for one specific target audience.

If you trained your software on your data and then asked it to produce a forecast, you would have a hard time obtaining usable results. Instead of reflecting objective reality, your forecast will reflect the highly biased data you used to create it. Usable forecasts require objective and well-rounded data. 

To make the most of these technologies, you need to have relatively large pools of data to work with.

Interruptions in subscription or billing workflows could trigger churn waves

One of the most common sticking points around automation for SaaS CFOs is a fear that it will result in customer churn increases.

Since many SaaS users are on a revolving monthly payment schedule, any interruption in that billing flow could cause large volumes of churn.

Maybe you switch to AI and it causes a problem with your company’s ability to process payments, causing involuntary churn. Maybe it sends customers bills for the wrong amount, and they get fed up and leave.

These risks are real.

Before purchasing a cloud accounting solution, check that the vendor has served many clients with your precise needs and that they experienced no service interruptions as a result of the product.

Faulty AI products can produce hallucinations

AI hallucinations occur when a generative AI tool produces data or a statement that is incorrect or misleading. In a perfect world, this would never happen. Unfortunately, it does.

If someone casually playing with ChatGPT encounters a hallucination, it’s no big deal.

But if you let an AI hallucination slip into an important revenue forecast, the results could be disastrous and hard to repair.

The stakes are high and real.

The way to protect yourself from AI hallucinations is to vet your vendor up, down, and sideways:

  • How long have they been in business?
  • What’s their reputation like?
  • What specific product development standards and practices do they have in place to produce trustworthy and compliant products?

Now we’ve covered the major risks of this technology for SaaS finance, let’s return to its benefits.

Unveiling the opportunities in generative AI for SaaS CFOs

The risks of generative AI shouldn’t scare you away from these tools.

Yes, you should definitely proceed with caution. But that’s not the same thing as being afraid–and you shouldn’t be.

Let’s look at the other side of the equation. If you embrace this powerful new tech, what rewards can you expect?

Dynamic scenario forecasting

Forecasting is one of the most important workflows in all of finance.

SaaS CFOs need to simulate various scenarios to assess their financial impact and gain insights into different outcomes and courses of action.

This helps you make better strategic decisions and identify potential risks so you can steer clear and stay profitable.

Accounting software with generative AI uses ML algorithms to produce dynamic forecast models. This means that your forecast models will shift to reflect the changing financial realities in your environment.

It’s essentially real-time financial forecasting, and it’s as simple as putting in your starting data and clicking a button.

Automated board packs and capitalisation tables

Creating and distributing board packs before meetings requires a lot of time and hassle when doing it manually. 

Generative AI can seamlessly create and distribute board packs for meeting attendees.

Board packs created with generative AI feature financial storytelling techniques and helpful visual aids to quickly get everyone on the same page.

Generative AI can also create detailed capitalisation rundowns. This saves you considerable time, prevents capitalisation errors, and helps you effectively track your performance obligations.

Generative AI is helping SaaS CFOs effectively manage investor relations, an important responsibility that has an outsized impact on your profitability.

Robust SaaS metrics analytics

Adopting generative AI allows for effective analysis and tracking of all your key SaaS metrics. This integration provides deeper insights into customer retention, monthly recurring revenue (MRR), and other vital metrics.

Leveraging AI capabilities enables the identification of trends and patterns in SaaS performance, empowering CFOs to make real-time and accurate decisions based on SaaS metrics analysis.

When you align your strategies with the insights you gain from your metrics, positive business outcomes are much more likely.

SaaS metrics integration offers a comprehensive approach to key performance indicator (KPI) management. With accounting automation, you’ll have access to dozens of SaaS metrics continuously updated in real time.

Final thoughts

Automation tools for SaaS CFOs are not without risk.

But when it comes to maximising the effectiveness of your business operations, the positive impacts are simply too large to ignore.