Automation in Finance: Confronting Fears & Maximizing ROI

But historic fears, frustrations with bandwidth and learning challenges can often take over and stop you from taking advantage of these benefits.

Whether you’re worried that it’ll take too much time to learn how to automate certain processes (or teach team members) or you don’t feel like you have enough time to pile on more to your immediate/existing workload, finance teams have historically been slower to adopt AI and automation.

But the rewards you can reap through AI shouldn’t be ignored out of fear or an inability to adapt. That’s why we’re exploring some of the most common psychological triggers that hold finance teams back from maximizing results through AI and automation. Plus, we’ll outline the key benefits so you can maximize ROI.

One of the most common fears we repeatedly hear is that AI will replace key jobs in the finance sector. We can see why since recent reports have fanned those flames of anxiety. It’s claimed that up to 30% of jobs will be automated by the mid-2030s and that the number of US jobs lost to automation will reach 73 million by 2030. 

We ran a recent study to see how financial teams saw the role of AI in business risk and 63% told us that a lack of automation creates little to no risk. This is telling for a couple of reasons. One, it means the finance teams are confident in their ability to deliver the right data and make the right decisions. Two, it could also suggest a case of doubling down and refusing to even consider AI as an option because of the perceived threat to human roles. 

As the financial industry is built on trust, it’s not a stretch to think that people are worried about AI not having the kind of human understanding that it takes to maintain strong relationships between departments and customers. It’s natural for finance staff to worry about AI-driven credit risk models being prone to errors or producing biased outcomes. 

After all, dealing with swathes of credit risk data, budgets and numbers isn’t a straightforward process. Each customer’s financial circumstances are unique and there are lots of nuances to consider in a cost of living crisis, labor shortage and recession. 

This fear stems from the perceived complexity of AI systems. On a deeper level, it may stem from not wanting to give up control of existing processes that have been in place for years. In turn, this creates a hesitance to train new staff because of an attitude of ‘this is the way it’s always been done and we don’t need to change.’

Age is likely a contributing factor here too, as data reveals that the average age for a financial employee in the US is 44. Research from Gartner also shows that the largest demographic that’s growing in finance is 60 and over. So, it’s not hard to picture older generations being more set in their ways and being resistant to embracing new technology.

Sarah-Jayne Martin, Director of ICA Global AR Practice at Quadient, agreed with these points and provided further insight into why there’s so much hesitation around AI.

“There are a couple of reasons that finance departments fear automation. First, finance professionals tend to lean on the side of ‘trust but verify.’ Any finance professional reading this will likely be nodding their head. It’s obviously best practice to make sure accounting entries are accurate. But for some, the thought of a software platform or other solution automating a process that’s always been done manually can be slightly unnerving or even intimidating. 

Second, we’ve all been through implementations where things don’t go as planned and, in some cases, a solution has ended up causing more problems. So, there’s a healthy skepticism towards anything that removes control from the accounting personnel.

And then you’ve got the generational gap in finance. According to a study by Zippia, the average accountant in the US is 44 years old. So, while this doesn’t make us all dinosaurs, it does put us in the category of being slightly less technologically savvy. For most, we’ve been performing our job functions manually for many years. And any change to the status quo is frankly scary.”

In a heavily regulated industry like finance, people are naturally concerned about the ethical implications of AI. These concerns may involve the use of personal data, unauthorized access to credit risk information and potential unintended consequences. 

The fact is that fraud and data breaches are one of the top challenges that financial staff are dealing with. Cybercriminals are getting more brazen every year. Just look at these stats:

• In Q1 2022, the average ransomware payment was over $200,000. 
• Phishing attacks cost companies more than $1,500 per employee. 
• It’s estimated that the average cost of a data breach was $4.24 million in 2021. 

With warning signs like this, don’t be surprised if your employees call on you to establish ethical guidelines and frameworks about responsible AI deployment, transparency and fairness. 

Now that we’ve confronted these fears, let’s take a look at the benefits of financial automation. 

AI is a game-changer when it comes to enhancing all the financial processes associated with keeping your cash flowing. We’re talking about vetting customers for risks, assessing their financial health, reaching credit decisions and so much more. This is especially important given the rising cost of inflation, cost of living crisis, energy crisis and supply chain disruptions.

So, rather than have 5+ people from your finance team run around trying to collate various data sources about your customers’ financial health (which could inevitably lead to data errors and skewed analysis), automating the credit decision process can help you reach credit decisions more quickly and more reliably. Isn’t that what your team and business ultimately want? Less risk and better protected cash flow sounds pretty good to me.

The presence of advanced credit scoring systems that go beyond just looking at credit scores is sure to increase in the future. The algorithms will analyze multiple layers of data, such as legal filings, debt situations, the individual circumstances of directors and the overall performance of a company. This type of software has been recorded to improve financial loan applications and lower customer loss by as much as 45%. 

Danny Wheeler, AR Solutions Strategy Manager at Blackline, shared his thoughts on the efficiency and decision-making benefits that AI brings to the table.

“Automation can provide significant returns on investment in various areas related to credit risk, finance and profit. It can streamline manual processes, reducing the time and effort required to perform tasks. This increased efficiency can lead to cost savings and productivity gains.

It also means teams are working with the latest data which isn’t always the case when done manually. This means there are far fewer wasted activities where data isn’t up to date and people have had to do unnecessary work like when a customer makes a payment that the Accounts Receivable team can’t apply against an invoice for a few days because they’re working to process several other payments.

In that time, the collections team are likely to have chased the customer again for payment for the invoice or the account has been put on hold. Both cases result in wasted effort for the person chasing payment and a terrible experience for the customer who may decide to take their business elsewhere in the future because of the poor experience.

Automation also enables real-time data processing and analysis, allowing for faster credit risk assessments and decision-making. This speed can result in quicker responses to credit inquiries, customer issues (leading to an improved customer experience). As a result, the business will be able to identify patterns and trends in real-time, which means they can mitigate risk far better or make better decisions on where to focus based on the data provided.” 

Given the prevalence of cybercrime, you’ll want to make sure customer information and credit risk data are always protected. Crimes to watch out for include ransomware, phishing emails, hacking weak passwords and employee tampering, just to name a few.

Thankfully, AI and automation are great weapons to have in your arsenal in all these scenarios. For instance, you can use machine learning to screen customers and suppliers to make sure they aren’t in violation of financial crimes, fraud, corruption, child labor and forced labor. Predictive analytics allows you to double-check information and adapt to blind spots, while machine learning algorithms can help you detect and prevent human errors that could lead to serious financial losses for your business.

When we interviewed Sarah-Jayne Martin from Quadient, she went into more detail about the benefits of automation in processing sensitive financial data.

“Automation can teach financial teams that there’s an opportunity for efficiency improvements across all finance functions. By automating key processes, finance teams can free up time that can be used for more strategic and value-added tasks. So rather than spending time sifting through paperwork to assess creditworthiness, automation can provide instant decisioning. This, in turn, gives credit teams time to focus on the customers who are good opportunities for upselling and can work with sales teams to ensure that the right customers are being targeted for increased sales, which ultimately increases revenue and working capital.

In addition, automated monitoring of accounts allows credit teams to stay on top of accounts that may be declining in financial worthiness. So, they can make quicker decisions around limiting credit lines or sales to avoid unexpected write-offs.

Automation can also provide valuable insights into your business processes and identify areas for improvement and forecasting. As an example, an automated report or dashboard on invoice disputes can recognize if there’s a spike in disputes that need to be investigated to see if there’s a problem upstream causing the increase. By providing insight into historical data as well as predictive analysis, automation can improve the overarching view of the finance function and help achieve a more streamlined process.

Typical historical data might be past payment history, which allows teams to understand if a customer is improving (paying faster) or declining (paying slower). AI can be leveraged to spot these trends and automatically alert a team member to address the situation. Credit data from an external source like Creditsafe can also be monitored to help teams understand how a customer is paying other vendors and determine whether any action is needed, such as increasing a credit line if a customer is paying well or decreasing it if the customer is paying slower.”

You’ll have heard the expression: ‘High risk, high reward.’ With finance automation, it’s the opposite - low risk, high reward. This is because technology looks at financial trends and streamlines processes to bring more money into the business. We asked Sarah-Jayne Martin from Quadient what she thought of how AI helps to increase profits. This what she had to say.

“The benefits of automation outweigh any concerns. Technology can reduce manual tasks and repetitive chores, which allows professionals to focus on more value-added or strategic initiatives. This leads to overall better employee satisfaction and reduces churn. In addition, technology can provide greater transparency into the finance function, which allows teams to assess areas of their processes that can be improved, ultimately benefitting the bottom line and working capital. 

By automating the credit application and assessment function, companies can gain better insight into the different types of risks they could be exposed to and mitigate those risks effectively. This results in fewer delinquent accounts and better credit line management, which reduces exposure to risks. By leveraging automation in the credit risk and customer onboarding process, finance teams can streamline the process which improves the experience for both internal stakeholders and prospective customers.”

The future is certainly bright for financial automation. And while it may feel scary to use for the first time, it shouldn’t be kept at arm’s length. AI needs to be embraced by every financial manager.

Here’s what Sarah-Jayne Martin from Quadient predicts for the future.

“We have seen massive improvement in the finance function with the emergence of automated solutions. There is better accuracy, better visibility, and better experiences for internal and external customers. There are now automated solutions for most finance functions, which have reduced paper-driven or excel based processes. Looking into the future, I think we will see more use of AI and machine learning to further improve the function. I don’t believe the finance back office will ever be completely automated but in the future, ideally human interaction and decision-making will only occur when needed, versus at every touchpoint.”

Danny Wheeler from Blackline also weighed in on the topic. “We’re also seeing a lot more interest in AI as a function because of the data and insights available on customers that can be shared across the business. Essentially, AI turns it from a back-office function to a strategic business partner and I think this is where AI will develop in the future.”