Want to make more cash come in faster? To fix Enterprise Resource Planning (ERP) problems in accounts receivable, you’ll need more than your ERP system. It may sound harsh, but it’s true.
In a new study from Vanson Bourne, 68% of finance leaders admit their ERP isn’t enough to hit the gas pedal on cash velocity. One big reason why is clunky accounts receivable procedures. CFOs want to get way more strategic with cash flow optimization, but over 80% say their ERP is holding them back. That’s often because ERPs can’t apply remittances automatically or lack the behavioral analytics to reveal financial threats proactively. When that changes, so does cash flow: an average 25% reduction in Days to Pay (DTP) and 23% reduction in Days Sales Outstanding (DSO), the study found.
ERPs are essential, but we need to be very clear about what they’re good at, what they don’t do, and how their gaps in AR limit cash flow. That’s why I want go through this together: where ERPs struggle, the limitations they create, and the approach that’s helping 95% of finance leaders unlock cash faster without ripping or replacing critical legacy infrastructure.
Automation Needs to Move Cash, not Just Keep the Books
AR automation is at the top of CFOs’ list of strategic priorities – 93% using it confirm it accelerates cash flow and improves liquidity. Those with the highest levels of automation across the O2C cycle report crazy high reductions in DTP and major efficiency gains. For this to happen though, the ERP needs to be pulled into a transformation initiative. The system wasn’t designed to automate the end-to-end AR process or think about the big picture of cash flow – and that’s okay. Addressing these ERP problems in accounts receivable is the first step toward liquidity.
ERP Invoicing Gaps
Take invoicing, for example. ERP automation is built for speed (getting invoices out fast) not cash flow optimization (getting customers to pay fast). Delivery is typically batch-based and template-driven. There’s not a whole lot of flexibility per customer other than swapping a template or maybe changing how the invoice is sent. Error handling is also basic. The system might automatically block an invoice from being sent or flag someone for manual review. The team is still grinding through it, and cash flow stalls as a result.
How AR automation for ERP Fixes Invoicing Gaps
Purpose-built B2B payments software automatically sends invoices the right way, every time. The goal isn’t to push out the most amount of invoices, but to make sure they don’t bounce back. Teams with this kind of automation are 18% more likely to get invoicing right the first time every time compared to those relying on ERP systems alone. It’s a huge difference in the quality of the buyer experience, and a much better day-to-day for the AR team too.
The goal isn’t to push out the most amount of invoices, but to make sure they don’t bounce back.
In a world where agentic AI for finance can dynamically redesign invoice formats to accelerate payments, this level of automation is now the norm. But remember that AR software solutions vary in AI automation maturity. The right platform covers all the bases – the fundamentals you expect plus more advanced capabilities that drive efficiency (and thus, cash flow). You also need to think about capabilities for cash flow visibility, forecasting, and the buyer experience. Our 2026 Buyer’s Guide to AR Automation Software lays it all out.
AI is More than Efficiency – It’s Behavioral Intelligence
By “behavioral intelligence,” we mean using machine learning (ML), predictive analytics, and preventative analysis to understand buyer behavior today, past payment patterns, predict what’s coming, and take the next best actions to move cash faster or buffer the risk. It’s a huge priority for finance organizations – 47% are actively exploring how AI and behavioral science can influence liquidity and cash flow certainty. Again, this is one of the major ERP problems in AR that standard systems cannot bridge — nor should they be expected to.
ERP Collections and Payment Gaps
Let’s look at collections. Most ERPs tell collectors to focus on aging buckets. Older = riskier, right? But that’s not always the case.
If a customer always pays at 40 days, then 40 days shouldn’t be the moment a red flag is raised. For that customer, it’s actually normal behavior. But if another customer always pays at 28 days and suddenly they’re at 35? That’s the one you should be looking at. ERPs don’t know what’s normal for a customer. They don’t see the previous patterns and the moment behavior shifts.
ERPs simply record and keep moving, and that’s how collectors can end up working on the wrong accounts.
Another example is how payments come in. Short pays. Deductions. Missing remittance data. When things don’t line up perfectly, ERPs will wait for a human to figure it out. It doesn’t think, “This customer always deducts freight” or “They usually bundle invoices by region.” They’re not designed to understand, predict, or respond in real-time. Until that cash is applied, DSO looks worse than it is, delinquency looks inflated, and your team is chasing problems that may not even be of real concern.
This is why we’re now seeing ERP vendors working to retrofit AR-specific features into their systems. This might seem like a compelling solution due to its built-in convenience, but it’s not always ideal. Much like security features can be an afterthought, most would prefer a solution built for dynamic collections operations, including capabilities like real-time insight, ongoing monitoring and optimization.
Improving Collections with Agentic AI for Finance
An ERP with an AI add-on is not the same as having behavioral intelligence infused at all levels. You need an ecosystem of AI agents using data science and collaborating across the end-to-end AR process. Purpose-built AR software has a multi-agent architecture built into its core. The right solution (again, not every system is the same) can look at payment behavior and say, “This is normal” or “This is risky. Let’s try this at the collections level and do that at the credit management level and see how those changes influence AR performance.”
It’s a whole new level of intelligence for moving cash faster. When AI models and AR leaders can see credit allocation risk, customer payment risk, and real-time collections activities all at once, they’re far more capable of optimizing working capital than they would be if they had just one of those data points alone.
Buyer Beware: This is important
Before you keep reading, I encourage you to investigate what the AR platform’s AI is built on. Is AI intelligence built on big data? Meaning real AR data across a massive volume of buyers, industries, and payment behaviors? If it’s not real, neither is the promise of faster cash flow. Don’t implement an AI solution that has to start from scratch using nothing but your own customer data. Learn more on that here.
You also need to ask yourself what a trustworthy AI model means to you. Here are some things to consider:
- Transparent AI logic — audit trails and explainable rationale so you can see how decisions and recommendations are made
- Responsible AI practices like bias testing and customer data privacy
- The ability to move at your own pace — you should never feel like you’re giving up control for the sake of innovation
Explainability is now a key decision-making factor in AI adoption.
More ERPs = More Confusion
ERPs can show you a lot, but they don’t give you a clean, connected view of the entire O2C cycle – especially when you’re working across multiple systems. Vanson Bourne’s research found that the average company uses three ERPs. Eek! That’s a lot of data wrangling.
The fragmented data creates massive ERP problems in accounts receivable. Way too much time spent reconciling systems and pulling data together manually just to answer basic questions. And if we’re honest, you’ll still only be able to see part of the full picture.
Solving Data Fragmentation with AR Automation for ERP
When you only look at the ERP, you miss the bottlenecks, the friction…everything happening in the trenches of cash flow. Looking across multiple ERPs makes this even more confusing, and it takes way too much time trying to manually pull everything together.
Purpose-built AR software uses AI to look at everything – what’s sitting inside ERPs and all the other behavior, performance, and payment data you need – and packages it neatly in one single view. This is a big reason 98% of finance leaders say AR software saves their teams significant time on AR processes every week compared to relying on native ERP tools alone.
98% of finance leaders say AR software saves their teams significant time on AR processes every week.
The thing to consider here is integration. If it’s not an ERP-agnostic solution, you don’t want it. Just as important is integration with client AP portals, banks, and other financial systems that enable faster processing and reconciliation. Also make sure the platform can evolve with any ERP upgrades. It’s a fast-paced world, today. No company should have to wait until they have the latest and greatest version of one software for it to be compatible with another.
Workflows Don’t Follow the Same Rules Anymore
The problem here is two-fold. ERPs don’t orchestrate across systems, nor can their workflows adjust and adapt. ERPs do what they do, and teams do what they can to light up all the relevant next steps. But it’s not always a coordinated effort. At the same time, AR workflows are no longer rules-based operations, “if this, then that.” Modern operations are behavior-driven, based on real-time changes.
Finance leaders are now using agentic AI for finance to adjust, adapt, and optimize workflows. Some are looking at agentic procedures, which is just a fancy way of saying they’re having AI agents continuously monitor, optimize, and even carry out workflows under human supervision. It’s pretty incredible – you can see how it works with this quick demo on our site.
What Needs to Change
A modern AR platform is built to stitch all the right moves together and then flex. It can route tasks dynamically, flag changes in real-time, and prioritize actions based on risk and value. It’s a constant evolution, not a static ruleset someone configured three years ago that has never been revisited.
But measuring the success of AR workflows can be challenging too. When four primary activities are the biggest levers for key metrics like DSO, which one is slowing your cash flow? AR leaders should understand which activities are tied to which performance metrics and know how to pair KPIs together to improve operation. You can explore all of that in this periodic table of AR elements.
You’re Not Stuck. You Have Options, but One is Easiest.
Let’s look at three options and the data behind them.
- Your first option is to tinker with your ERP. Create a data warehouse, call on IT to sweat out some customizations, layer analytics on top, and see how far it gets you. Research shows you have a 30% chance of this working. In 2025, Deloitte polled CFOs leading these kinds of DIY projects to modernize their ERP and found that 70% of end up less impactful or slower moving than expected.
- Your second option is to upgrade your ERP system, trusting that the native tools will cover all your AR needs. If you’re kicking around the idea of a new ERP, you may want to know that 94% of CFOs in 2025 said they regret their most recent ERP purchase. They point to the same familiar headaches: clunky, hard to configure, disconnected…just not enough. Only 2% say they’re getting the full value out of the platform. Many were also hit with surprise expenses and ongoing maintenance.
- Your third option is to complement and extend your ERP with AR software. Take your existing ERP(s) and connect it to purpose-built AR software for faster B2B payments. This is the approach that addresses the most common ERP problems in accounts receivable and delivers the hard and fast ROI executives want to see – a 25% reduction in DTP, 23% reduction in DSO – and it’s just the beginning. Overall, 95% of finance leaders agree this is the best solution and delivers the greatest ROI. There are some gotchas, though. Remember the things we talked about: automation, system integration, and the transparency of AI decisioning. Do your due diligence and come back to us if you have any questions.
Billtrust vs. Your ERP
| AR Functionality | ERP Systems | Billtrust |
|---|---|---|
| Service, Support, and Partnership |  Sub-par or impersonal service quality marked by low-touch engagement |
 High-quality service, a menu of training, support, and professional services |
| Quick-Launch Solutions | Long implementation times, little support for in-house customizations |
Rapid time to value, minimal IT dependency, custom solutions and integrations |
| Real-Time AR Visibility | Lacks native real-time visibility across AR lifecycle |
Integration across AR functions enables full transparency |
| Payment Portal | Add-on feature, separate licensing, additional fees |
Branded portals are included, offering payment flexibility |
| Invoice Delivery | Limited options |
260+ integrated AP portals |
| Collections | Lacks AI maturity |
Automation and insight powered by Agentic and Generative AI |
| Integration Flexibility | Custom coding for AP portals, banks, and ERP systems |
15+ ERP connectors & seamless data exchange |
Start with Vanson Bourne’s latest report. It’s a must-read if you’re trying to successfully bring your ERP into the fold of modern AR and predictable cash flow.
