6 Ways AI and ML are Transforming SaaS Finance (and How You Can Take Advantage) 

AI and machine learning (ML) are helping many SaaS finance teams operate more effectively. By automating repetitive financial processes, teams are able to focus on more strategic contributions during their workday. At the same time, the automated tasks are completed more quickly and accurately. 

In this post, we’ll explore six reasons for SaaS CFOs to incorporate AI and ML into their accounting departments. We’ll also look at the accounting technology you can adopt to accomplish that. 

Reason 1: Tightened Security and Automated Regulatory Assistance

Security and compliance are always top-of-mind for SaaS accounting leaders. You need to manage risk and uncertainty.  AI and ML for SaaS finance can help create a secure environment for your valuable internal and customer data. 

Peace of Mind Through Secure Data 

AI and ML for SaaS finance can enhance your operational security by eliminating manual processes. 

With a single source of truth (SSOT), your data that’s currently spread out across departments gets centralized in the cloud–accessible at any time to anyone on your team who needs it.

This eliminates risky manual processes like exporting customer data to spreadsheets and sending those spreadsheets as email attachments. 

Whenever someone on your team sends data that way instead of leveraging AI and ML for SaaS finance, it creates a whole chain of security liabilities. 

Real-Time Regulatory Updates 

The compliance landscape for SaaS finance professionals grows more complex every year. This makes keeping up with regulatory updates a constant challenge. The cloud helps finance leaders stay attuned to any changes that take place.

When you opt for AI-fueled SaaS accounting in the cloud, you’ll be automatically updated every time a regulatory change impacts your company. 

Reason 2: Dismantled Data Silos 

Why is it important to dismantle data silos if you find them in your company?

The Ideal Organization is Collaborative (Silos Aren’t)

Today’s SaaS CFOs should do everything possible to encourage teams and individuals to work together. Data silos, by their very nature, do the exact opposite. 

When you switch to the cloud, data silos are automatically knocked down in favor of a centralized data lake–a single pool of constantly updated info that all teams can consult as needed. 

This approach helps teams cover all their bases. The AI handles the data-intensive heavy lifting, and your team uses its human intuition to spot patterns, ask the right questions, and craft profitable strategies. 

Data Quality Through Integration

In addition to facilitating seamless access to data, integration with an SSOT ensures data quality and accuracy. That’s because your data is continuously updating in the background at all times, as opposed to each department executing its own updates. 

This eliminates human error and facilitates much faster decision-making, reporting, and forecasting. 

Reason 3: Streamlined Revenue Recognition 

Revenue recognition is another area where AI and ML for SaaS finance really shine. With manual processes, some degree of revenue leakage is almost guaranteed due to the unreliability of legacy methods. 

In a manual rev rec scenario, various departments update their data independently. This leads to reporting inconsistencies, problems with deferred revenue waterfalls, and revenue leakage. 

Stop Revenue Leakage Permanently 

In combination with a revenue recognition strategy, AI and ML for SaaS finance allow accounting teams to effectively plug up revenue leaks.

When you use AI and ML for Saas finance to remove the requirement of syncing up data sets, rev rec almost takes care of itself. 

Reason 4: Smoother Customer Experiences 

One of the great things about AI and ML for SaaS finance is that its benefits also extend to your customers. 

By allowing you to collect more detailed customer data, AI-based SaaS accounting puts you in a position to deliver a tailored and optimized user experience. 

Better Data Collection and Analysis 

With manual processes, SaaS accounting departments are often left in the dark concerning a staggering amount of customer data. 

AI and ML for SaaS finance can help teams access valuable data, including: 

• The full range of SaaS metrics that help companies understand their customers’ needs and pain points.

• Feature preferences, adoption patterns, and other user data that your team can use to make better decisions.

How else can AI and ML in SaaS finance help you rethink your organization’s relationship with its customers?

AI Chatbots 

AI chatbots offer an opportunity to collect profitable user data and even pitch customers on subscription upgrades. They can even help multiple customers at once, for free.

Among various other applications, AI chatbots can be used to: 

• Learn more about a user’s preferences or opinions related to your brand. (It’s less official and time-consuming than a customer review, but it serves the same function for internal feedback purposes.) 

• Offer suggestions about other products from your company that users might enjoy, or ask them in a non-pushy manner if they feel like upgrading their subscription for an even better experience. 

What else do you stand to gain by adopting AI and ML for SaaS accounting and finance? 

Reason 5: Forecasts Stakeholders Can Trust 

One of the best things about AI in the context of SaaS accounting is what it can do for your forecasting accuracy and effectiveness. 

CFOs are using AI and ML in SaaS finance to overcome the traditional 

challenges of forecasting and the forecast variance they produce.

The Hidden Costs of Forecast Variance 

Using an automated SSOT to assemble your forecasts will help you produce more accurate and reliable results. 

The high variance associated with legacy forecasting methods leads to: 

• Poor FP&A decisions that often fail to achieve their desired results. 

• Short forecasting ranges that limit your operational impact. 

• Lost potential connections and insights due to limited SaaS metrics and other dataset restrictions.  

Reducing forecast variance isn’t all that AI and ML for SaaS finance can accomplish. It can also help you cut your churn rates. 

Reason 6: Automated Churn Management 

High churn rates don’t please anyone in a SaaS accounting department. And as CFO, they should please you least of all. 

If you adopt a cloud-based financial management system, you’ll have the power of AI to help you deal with churn. 

AI and Dunning 

One of the largest sources of churn for SaaS companies is what’s known as involuntary churn. When a user churns involuntarily, their subscription is deactivated because their payment cannot be processed. 

The majority of the time, this is simply due to the customer needing to update their payment method. Dunning is the practice of sending these customers notification emails asking them to update their card info, and letting them know you’ll try rerunning the charge in 3-5 days. 

AI and ML in SaaS finance can help you send out dunning emails automatically, recapturing a large percentage of subscriptions you otherwise would have lost to involuntary churn. 

Enhance Your Results in the Cloud 

AI and ML present SaaS CFOs with a range of opportunities to enhance their effectiveness and profitability. 

Even though many finance leaders realize this, they often hang back because they mistakenly believe that upgrading to cloud-based accounting is a complex process. 

We dispel this myth entirely in our recent white paper: 7 Reasons Implementing Cloud-based Finance Software is Easy.