“Why should I automate financial operations” is almost a question that answers itself, especially in the AI age.
Manual accounting procedures are known for their inefficiency and time-consuming nature. When utilizing spreadsheets for essential financial tasks such as accounts payable and accounts receivables, activities that should take seconds or minutes can consume several hours or even days. Moreover, each stage in the manual process is prone to human error, resulting in additional expenses, delays, and frustration.
With talent harder to come by and hold on to than at any time in the last 30 years, increasing regulatory pressure on your finance function, and persistent fiscal uncertainty coupled with our recent return to higher interest rates, it’s never been more important to achieve visibility over your processes to optimize your working capital, lower DSO (days sales outstanding), extend DPO (days payable outstanding) and improve financial control.
This is where finance automation and financial automation solutions come in.
What is finance automation?
As the name suggests, finance automation uses technology to automatically complete financial tasks that your teams are currently performing manually.
This includes tasks like:
- Account reconciliation
- General ledger entries
- Financial statement preparation
And even more complex tasks like budgeting, forecasting, and creating reports.
Finance automation is increasingly handled by AI-powered solutions that incorporate smart workflows that are ushering in a new era of autonomous finance—a base-state for operations where most day-to-day work is handled autonomously with human oversight and approval.
Finance automation tools and solutions make it possible to handle growing pressure on your department, and do it in a way that is easier and significantly more comprehensive than in any other business function.
Accenture, for instance, estimates that up to 80% of financial operations could be automated.
And since as much as 60-75% of employee time in the finance department is spent performing routine jobs that can be performed more quickly, with fewer errors, and with significantly less risk of staff burnout, you should see doing so as a no-brainer.
But in spite of this, 49% of companies still don’t automate their financial processes, meaning they’re missing out on a huge world of innovation and opportunity.
Why are companies slow to adopt finance automation tools?
Finance leaders and their teams tend to be naturally much more cautious than other lines of business. Automation within finance processes remains relatively low compared to other operational functions in enterprise.
That said, major changes over the last several years, including the shift to remote and hybrid working structures, the rise of cloud-based ERP platforms, and the widespread availability of AI-powered automation software, have seen different teams within finance begin to adopt automation and associated automation tools with different rates of both speed and success.
In particular, Accounts Payable (AP) teams have been the most enthusiastic adopters of automation technology for the last several years because of their reliance on highly manual processes. Cash application teams have likewise made huge strides in Accounts Receivable (AR), although credit and risk management and collections teams have been slower to automate, even with the rapid adoption of AI-powered automation solutions.
5 top benefits of finance automation solutions
Here’s 5 of our favourite ways that finance automation tools can have a huge positive impact on your business and its ability to maintain strategic agility in the face of a rapidly changing marketplace.
1. Save everyone time and enhance the user experience for both customers and employees
The non-automated finance ecosystem, whether it’s procure-to-pay or order-to-cash processes, is beset with challenges created by siloed systems, manual processes, and fragmented data.
Finance automation software helps to resolve these strains by creating an integrated ecosystem for every part of the finance workflow. As well as creating numerous “quality of life” improvements for your teams by making data retrieval and reporting easier and eliminating large parts of the tedious rote work that often comes with financial operations tasks.
With the use of robotic process automation in finance you can improve the user experience for your teams, your customers, and your suppliers. Enhancing relationships, making receiving and making payments easier, and improving staff retention through improved engagement.
This translates to obvious tangible benefits any CFO can appreciate. The most important of these is faster and more accurate closing cycles. Many Serrala customers reduce their month-end closing process from a weeks-long exercise to one that’s done the week after the end of the month in question.
2. Reduce the errors inevitable in manual processes
Repetitive transactional work of the kind common throughout financial operations inevitably leads to errors, as even your most competent people aren’t perfect. The potential for errors is only compounded when you take into account the potential for duplicate or erroneous data entry created by working with multiple siloed systems.
Automated systems powered by AI and machine learning principles have a huge advantage in that like people, they can learn the correct steps and approaches for simple processing tasks, but unlike people, they don’t get tired and they don’t make mistakes “at random”. Allowing you to have a greater degree of confidence in the fundamentals, and giving your teams to pursue higher-value strategically focused work of the kind that helps the finance department and CFO become trusted advisors to the organization.
3. Improve data visibility and quality
Most finance departments are sitting on mountains of data that they can barely access, let alone efficiently leverage. With many processes still relying on multiple spreadsheets maintained by different teams, manually maintained databases, and a disjointed ecosystem of software solutions, data is often difficult to access, unreliable, and outdated by the time it’s retrieved. This makes reporting processes both more drawn out, and the conclusions they produce less reliable.
Automated solutions make it possible to create a “single source of truth” for all the data that exists in your finance department. Allowing you to look up any information required instantly and to a high level of granularity, and vastly accelerating the reporting cycle, making it possible to generate strategic forecasts, month-end close reports, and handle regulatory reporting commitments in minutes or hours rather than days or weeks. Analytics capabilities transform how finance teams access and use their data.
4. Simplify regulatory compliance
Compliance regimes are becoming more strict and more complex as governments worldwide pass new regulations to close taxation gaps and enhance audits. Without automated solutions, the workload of managing financial compliance will continue to skyrocket, and according to LexisNexis, it’s already costing over $200bn globally every year.
Not only does finance automation software streamline processes, but it also ensures they are more accurate and compliant. As most automation products are now being delivered via cloud, these can be used on an automatically updating basis to ensure you always remain compliant without having to invest hundreds of hours of work a year in doing so. E-invoicing compliance across multiple jurisdictions is a prime example.
5. Boost decision-making and decision velocity and approach finance more strategically
Access to near real-time data from an integrated single source of truth gives your teams the power to work more strategically, with more confidence about the data they’re analyzing. It also makes a greater level of sophistication in analytics possible, providing business leaders with an up-to-date picture of your company’s financial position and health and allowing them to make strategic decisions faster and with a higher degree of certainty. All of which can contribute to finance becoming a more valued and trusted business partner to the board and the rest of the organization.
Which parts of your financial operations can be automated?
Simply put, any finance task that doesn’t require a human mind to handle an exception or a novel situation should be automated. But here are just a few examples of parts of the process we’ve helped to successfully automate at rates of 90% or higher with amazing results for our clients:
Order-to-Cash processes
Automation can transform how your business requests, accepts, and applies payments. For Serrala customers, this means liberating businesses from manual and time-consuming processes, automating the entire accounts receivable cycle from the conclusion of credit management to the application of cash to an invoice through the power of AI.
By harnessing Electronic Invoice Presentment and Payment (EIPP), you can eradicate paper-based procedures and significantly boost the speed and efficiency of your AR cycle. This includes validating remittance advices, ensuring precise collection scheduling, and promptly identifying issues for dispute resolution.
Procure-to-Pay processes
For most organizations, AI-powered solutions can make straight-through invoice processing automatic for a significant proportion of outbound payment requests, including managing automatic approval and routing any problematic invoices for exception handling if they require additional input or appear to be fraudulent. The result is a greater ability to intelligently and strategically make use of payment terms to capture discounts, fewer late payments, and strengthened supplier relationships. Supplier portals enhance this transparency.
Treasury processes and cash visibility
Automated solutions can unify your entire banking estate, making it possible to manage every account your business holds from a single platform. Improving your ability to optimize fees, ensure all mandates and instructions are up to date, and radically simplify regulatory reporting and compliance.
Achieving cash visibility is of particular significance to treasurers and cash managers because it delivers the fundamentals for strategic decision-making concerning financing, FX hedging and investments. It is also essential for accurate cash flow forecasting, managing cash and risk exposures efficiently to ensure the financial solvency of the organization on a daily basis.
AI-powered solutions for finance automation
The most mature approach to AI implementation integrates different capabilities into processes where they’re capable of driving the most value so that complex finance challenges can be tackled by the appropriate tools. This means no single points of failure, and it ensures we only deploy more complex and expensive technologies when they’re necessary to do a better job.
In finance automation, five major AI types form the cornerstone of automated workflows. The pinnacle of finance automation—”autonomous” finance operations, in which most of the run-rate tasks of a finance team are handled entirely by automated systems—depends on combining these capabilities across your working capital cycle to eliminate chokepoints created by manual processes and poor data visibility and quality.
They are:
RPA
Robotic process automation is by far the most established subtype of “AI” in business today. It creates a ruleset that allows tasks and data to be routed in ways based on their characteristics. Most of us will be familiar with it from call center interactions.
Within O2C its most important role is in automating workflows like the generation and sending of invoices and reminders, the routing of customer queries, and the tagging and escalation of tasks for exception handling and human review. In P2P, it’s a powerful ally in invoice data capture, matching workflows (particularly with non-PO sources), and compliance.
Machine learning
At the most basic level, machine learning provides an algorithmic method for processing data that updates itself as it’s exposed to new data.
ML allows your systems to “learn” from process failures or breakdowns and spot them before they happen, allowing for early intervention in cases that need special attention across cash application, credit risk management, and collections.
In AP and payments, it’s a growing ally in 3-way matching workflows, data capture from invoices across multiple formats, and fraud and risk management, helping teams spot fraudulent or erroneous approval requests before they can damage the business.
Predictive analytics
This is the application of machine learning to extrapolating future events based on current and historical data. Our customers already use this in O2C to predict likely customer payment dates and even defaults to proactively manage workflows from cash application to dunning. In AP and payments workflows, predictive analytics is most useful for reporting and dashboarding but it also very useful in matching invoices against purchase orders and non-PO authorization documents, as well as compliance and payment automation tasks.
Prescriptive analytics
If you’re already able to make predictions, suggesting potential courses of action based on them is the next logical step. In O2C, we’ve seen many customers successfully use prescriptive analytics to create more flexible workflows for their teams, empowering them to make more nuanced exceptions and modifications to company policies that improve customer and bank relationships and optimize working capital and cash flow.
As of now, P2P applications for prescriptive analytics are more limited, but it does help to improve reporting and analytics workflows by suggesting actions for continuous improvement.
Generative AI
The current “star of the show” in AI applications. Generative AI uses complex statistical models to complete data transformation tasks according to natural language prompts.
More than any other AI technology, generative AI is most likely to be sold as a kind of “everything app” that can complete any task you ask of it. This often leads to disappointment when a lack of specific training on your unique datasets yields poor results.
But despite this, it also has what’s potentially the largest scope for scale and expansion. With connection to the right datasets, O2C teams can use generative AI to instantly look up and cross reference data, creating complex bespoke reports in a matter of minutes and tracking down key information that would otherwise have kept the most skilled forensic accountants busy for weeks.
In P2P, it can combine with text analytics and computer vision solutions to make auto-capture of invoice details an entirely automated process.
This is what’s meant by “agentic AI”. An AI “agent” is simply a specially-deployed instance of generative AI that conducts specific analysis tasks on behalf of a team to present them with action-ready insight. Serrala’s AI approach incorporates these agentic capabilities throughout the platform.
What should you look for in a finance automation platform provider?
Selecting the right finance automation platform isn’t a simple task, and will require you to evaluate potential vendors on metrics like:
1. Process coverage
Many automation vendors are “pure play” providers for a specific workflow. They’re AR specialists, AP specialists, expense processing specialists, month-end close mavens, or the like. Depending on your organization’s size and setup that might be fine for your current needs, but you should also consider future requirements.
2. Scalability
Scalability remains the single biggest need and obstacle for finance teams looking to drive business outcomes and create a strong foundation for growth and investment. Your finance automation platform will need to be scalable to meet your changing needs as your business grows, your data expands, and your processes become more complex and interdependent.
3. Integration capacity
Your finance automation solutions will only be as good as the data they’re working with. And without the ability to integrate with your ERP platform or other finance systems of record, they won’t be much use to you at all. This will be of particular importance to organizations in the process of sunsetting their legacy systems as part of overall transformation strategies. You’ll need to pick systems and data structures that can speak to each other.
4. Implementation expertise
Finance automation isn’t something you can really undertake as a DIY project. A lack of in-house expertise can open the door to security-related vulnerabilities as cybercriminals become more sophisticated in identifying operational and security gaps within organizations. With organizations losing around 5% of their annual revenue to fraud, taking a do it yourself approach here can create risk exposure that simply isn’t acceptable. What’s more, for those of you working in regions with strong data protection regulations, breaches carry their own risk in terms of fines and audits. Outsourcing your implementation process to your vendor or to other experts will help you to effectively mitigate these risks and secure your systems.
5. What your O2C, P2P, and treasury/liquidity management teams actually need to perform better
Before you start, you’ll need to spend time with your finance teams to build a picture of where and how they do their jobs, the information they use, and the systems it lives in. This is also key to establishing success metrics.
6. Success metrics
Success metrics for finance automation are highly bespoke to each organization. Yes, there are some star figures like DSO, DPO, automation rate and the like that we can fall back on to see the big picture. But how you measure success for your own teams depends on their specific current situation and capacity gaps.
The Serrala Finance Platform
The Serrala Finance Platform is designed to make AI-powered finance automation a simple, scalable, unified concept within your teams regardless of your current challenges.
Serrala’s AI-powered automation solutions are trusted by over 2,800 world-leading brands to achieve the highest possible automation rates across their financial operations process. Eliminating manual effort from many of their most important accounting functions and saving weeks’ worth of time across not just their finance teams, but their wider business processes, and experiencing the improved working capital that allows them to make key strategic investments and decisions more quickly and more confidently.
Our solutions are SAP-embedded, cloud extensible, and S/4HANA and RISE ready.
They’re designed to deliver financial operational excellence, empowering finance leaders to:
- Accelerate processes for order-to-cash, procure-to-pay, cash management and treasury.
- Better optimize working capital with near real-time insights, AI-driven modelling, and continuous learning for smarter decision-making.
- Improve financial control for business and regulatory needs.
- Enjoy greater financial predictability to support the organization’s strategic objectives.
- Free proficient people to generate financially focused value.
We’ve developed the new Serrala Finance Platform to create the perfect architecture for CFOs looking to complete their organization’s journey to autonomous finance.
A single working capital intelligence hub that provides the foundation to bring AR, AP, payments, and treasury workflows together in a flexible system that adapts to individual organizations’ digital transformation roadmaps while enabling AI integration in every single process. It’s based on our experiences of both the ongoing project of digital transformation in finance and the areas in which our customers are already seeing genuine use cases for AI that bridge the gap to fully autonomous operations.
Most importantly, the Platform is designed to make the kind of data clarity and quality necessary to leverage AI for autonomous processes simpler for organizations to achieve. We leave storage to your ERP—after all, that’s what it’s designed for—and allow every part of the finance department to access it to automate workflows, accelerate decisions, and deliver measurable ROI.
If you’re interested in learning more about what we can do for you, get in touch with us today to book a demo.
Frequently asked questions
What’s the typical ROI timeline for finance automation?
Most organizations see measurable benefits within 3-6 months of implementation. Early wins typically include reduced invoice processing time and improved cash application accuracy. Full ROI, including working capital optimization and strategic benefits, usually materializes within 12-18 months depending on implementation scope and adoption rates.
How long does it take to implement finance automation?
Implementation timelines vary by scope and complexity. A focused pilot for AP automation might take 8-12 weeks. Comprehensive deployments covering AR, AP, and treasury typically run 4-6 months. SAP-embedded solutions often deploy faster due to tighter integration.
Will finance automation eliminate jobs in my department?
Finance automation typically transforms roles rather than eliminating them. Staff shift from manual data entry and invoice chasing to higher-value work like analysis, strategic planning, exception management, and business partnering. Most organizations redeploy people to roles that better utilize their skills and judgment rather than reducing headcount.
How secure is finance automation software?
Modern finance automation platforms provide enterprise-grade security including role-based access controls, encryption in transit and at rest, comprehensive audit logging, and compliance with standards like SOC 2, GDPR, and regional data protection regulations. Security should be a primary evaluation criterion when selecting vendors.
Which finance processes should we automate first?
Start with high-volume, rules-based processes where automation delivers immediate value. Invoice processing and cash application are common starting points because they consume significant manual effort and deliver quick wins. Organizations with strong SAP foundations often start with SAP-embedded AP automation to leverage existing infrastructure.
Can finance automation work with our existing ERP system?
Yes. Modern automation platforms integrate with major ERP systems including SAP, Oracle, NetSuite, and Microsoft Dynamics. Integration depth varies by vendor and ERP. SAP-embedded solutions offer the tightest integration for SAP environments, while cloud-native platforms connect to multiple ERPs through APIs and certified connectors.
How do we measure success after implementing finance automation?
Track operational metrics like invoice processing time, error rates, automation percentages, and staff time allocation. Also measure strategic outcomes: DSO and DPO improvements, working capital optimization, forecast accuracy, and how quickly finance can respond to business questions. The right metrics depend on your specific goals established during implementation planning.
What’s the difference between RPA and AI-powered automation?
RPA follows fixed rules (if-then logic) to automate repetitive tasks. AI-powered automation uses machine learning to adapt to patterns, make decisions based on context, and improve over time. Agentic AI takes this further by autonomously evaluating scenarios and taking appropriate action with minimal human intervention. Most comprehensive finance automation combines multiple AI types for optimal results.
