For finance teams still handling cash application processes manually, it’s a daily uphill battle. Entire teams spend their days chasing payments, verifying remittance details, and cleaning up exceptions while match rates (often called hit rates) barely improve. A top rated accounts receivable (AR) platform can completely transform this process, improving cash application hit rates while turning hours of manual grind into minutes of automated work.
Improving Cash Application Hit Rates: Capabilities to Look for
The following capabilities define what separates a top-rated AR automation platform from the rest, each playing a key role in driving higher hit rates and faster remittance posting.
- Data capture and process automation that reduce the number of reconciliation exceptions – regardless of how the invoice was paid or how the payment was received (via email, phone, mail, etc.)
- AI and machine learning (ML) that can adapt to evolving invoice formats and payment structures, matching invoices with unstructured, missing, or minimal remittance information
- A digital lockbox that extends automation by managing all of the data handling and reconciliation required to achieve straight-through processing – particularly for credit cards and virtual cards received via email
- Extensive system integration for smooth AR data flow and a unified view of all payment and remittance data.
Why is cash application so hard today?
In short, because a seemingly simple process hasn’t evolved to meet the complexities of a modern digital economy.
So much change has happened in a short span of time: Twenty years ago, most customers paid by check or ACH. Today, only a quarter of Gen Z (who is starting to shape the modern workforce) have ever written a check. The world of B2B payments is evolving with more payments coming through cards, portals, virtual cards and digital wallets. This means information is even more distributed than ever, leaving AR teams to track down payment information across a slew of systems all with different logins and user experiences.
Finance leaders need to understand these key forces shaping cash application to improve their organization’s hit rates and their team’s efficiency too.
My team spends way too much time manually matching payments to invoices. How can I automate this?
You’re not alone. One Billtrust customer, a leading storage solutions company, had two full-time analysts and one part-timer working 8-hour shifts just to process virtual card payments manually.
Automation lightens the load, made possible through integration as well as automated data capture, reconciliation, and closing. A top-rated platform should connect directly to banks and customer accounts payable portals to ensure data moves seamlessly between buyer systems and your cash application software and ERP system – supporting straight-through processing. In the end, all payment and remittance data should be available in one place offering a unified view of receivables – paid and unpaid.
Within this holistic view, teams can see:
- All incoming payments in real-time, regardless of source.
- Linked remittance details automatically associated with each payment.
- Match rate or hit rate statuses indicating which payments were automatically linked to invoices and which require manual review.
Automated data capture and integration eliminate manual lookups and redundant verification activities. With all payment and remittance data consolidated in one platform, matches happen faster, accuracy improves, and cash app hit rates climb.
Extend Cash Application Automation with a Digital Lockbox
A digital lockbox acts as the intake layer for many payment types, capturing and normalizing data from checks, ACH, wires, credit cards, and virtual cards into a single digital stream. It’s especially valuable for payments that arrive via email, like virtual cards, which are troublesome to manage manually.
After adding Billtrust Digital Lockbox to their Payments solution, our storage solutions customer began managing 96% of their virtual card payments automatically – turning 20+ hours of work into just 10 minutes a day.
“When payments clear faster and more securely, our customers are more motivated to use virtual credit cards,” said the Sr. Manager of Cash Applications. “It creates this positive feedback loop. They’re happy, we’re happy, and our finance team isn’t constantly playing catch-up.”
What are the top-rated platforms for automating the resolution of payment exceptions?
First, top-rated platforms for cash application automation should be able to do two basic things:
- Automatically identify and categorize exceptions into groups
- Allow you to customize exception handling procedures
This way, manual resolutions are faster and less laborious.
Standard automation uses configurable business rules to manage predictable scenarios. For instance, if a payment is short of the total invoice amount (a short pay), it’s automatically labeled as a partial payment or deduction. You define the rules: which exceptions to flag, who they should be routed to, and what alerts or tasks should be triggered to happen next.
This rules-based logic is helpful, but it can only go so far.
Advanced capabilities: What the best cash application automation software does
As payments become more complex and exception volumes grow, AI and ML step in to deliver intelligence and adaptability at scale. They don’t just flag what went wrong – they identify why it happened, recognize recurring patterns, and suggest or even apply the best resolution automatically. The system continuously learns and improves to reduce manual review and improve cash app hit rates.
A top-rated AR platform should offer rules-based logic as well as AI and machine learning to move beyond simple exception flagging – progressing toward more proactive, self-improving resolution. This kind of autonomous AI (called Agentic AI) is extremely powerful, which is why 57% of finance teams are already implementing it or planning to.
Billtrust’s Agentic AI is already showing what’s possible when this level of intelligence is applied across the order-to-cash (O2C) cycle, boosting productivity by up to 80%. Imagine this level of intelligence applied to cash application to drive higher hit rates.
What are the advantages of using AI in cash application?
We’ve already reviewed AI advantages and its ability to reduce exception handling. What are the other advantages it offers for improving cash application hit rates?
We’ve established that traditional automation can only handle what it recognizes: structured data, consistent formats, and clear invoice references. The chances of this happening every time? Zero. Remittance details are buried in PDFs, spreadsheets, and emails, and every customer seems to send payments differently. It’s messy and unpredictable, which is why rules-based logic cannot be the end-all solution for modern cash application.
Matching powered by machine learning and confidence-based approaches
With optical character recognition (OCR) built-in, ML-driven matching can go the extra mile, converting unstructured remittance info into match-ready data. When paired with a confidence-based matching approach, these powerful AI solutions can improve cash application hit rates even more by giving AR professionals greater control over how many reconciliation exceptions are generated.
Here’s how it works.
Instead of treating every match treated as an “all-or-nothing scenario,” the engine evaluates each incoming payment based on a range of factors and then assigns a confidence score based on how accurately the payment data aligns with the invoice data. You set the confidence threshold or score, which determines automated processing. Anything that doesn’t hit the score gets flagged for review. This granular control delivers the best of both worlds: automation for the situations where it’s deemed safe, and oversight where it’s needed most.
At the same time, AI learns from your historical reconciliations – recognizing when invoices are reformatted and when payment information is now split across multiple emails for example. It applies that knowledge to future matches. Let’s say Sally from Company ABC typically pays multiple invoices in one combined payment but forgets to include every invoice number; the system will recognize this and fill in the gaps by matching those missing invoices automatically. Ultimately, AI turns cash application into a self-learning system that continually improves hit rates over time.
Who offers the best technology for matching payments with minimal remittance information?
We’ve established that a top-rated platform should use AI and ML to match payments even when remittance information is unstructured, minimal, or even missing. But which provider delivers it best?
The answer lies beyond surface-level claims. You need to look at real-world outcomes, customer success stories as proof, and peer recommendations that validate performance.
At Billtrust, we can’t speak to other providers’ results, but we can share what finance leaders have to say and experience with Billtrust and our ML-driven, confidence-based matching engine.
- While the target for any organization should be an 85-95%+ match rate, Billtrust clients on average achieve up to 95%+ cash application match rates.
- A study from IDC study found Billtrust clients achieve 384% ROI.
- A study of 500 finance leaders ranked Billtrust as the most-recommended AR software provider, best known for its strength in cash application.
- One industrial supply leader designed an incentive program linking match rate improvements directly to team performance metrics. This reframed automation as a collaborative win rather than a threat to employee value. Match rates climbed by 42%, and productivity gains equaled 9 full-time employees. Read their story.
- Cintas, a professional services provider, used our matching engine to double its processing speed, increase productivity by 150%+ and gain more than $1M in annual savings. Read their story.
Break free from the endless cycle of exception handling and start truly controlling your cash flow. See how with a demo of Billtrust’s AR platform.
