Aug 25, 2026
Most B2B sellers still run trade credit on a spreadsheet, a credit application PDF, and one person's judgment. A buyer asks for Net 30, someone pulls a credit report, someone else decides on a limit, and the invoice goes out with a due date nobody actively tracks until it is 45 days late. It works until volume grows, and then it becomes the reason DSO climbs and good orders get turned away.
B2B credit automation replaces that with software. This guide covers what it actually includes, where manual credit-to-cash breaks, the five components of a working stack, how the vendor categories differ, what changes as you scale, and how to tell whether your business is ready.
Key Takeaways
- B2B credit automation is the use of software to run the credit-to-cash cycle: buyer credit decisioning, terms and limit assignment, invoicing, payment reconciliation, and collections.
- The five components of a full stack are credit decisioning, terms assignment, AR automation, collections, and financing or risk transfer. Most sellers automate two or three and leave the rest manual.
- Manual credit review is the usual bottleneck. Decisions that take days cost orders at checkout and in live sales conversations, where buyers expect an answer in seconds.
- Point solutions create handoffs. A separate credit bureau, AR tool, collections agency, and factoring line means data re-entry at four boundaries.
- Vendor categories are not interchangeable: payment networks, lenders and factors, credit insurers, ERP AR modules, and integrated credit-to-cash platforms solve different problems.
- Resolve combines credit decisioning, net terms financing, AR automation, and collections in one workflow, with advances of up to 100% on eligible approved invoices and non-recourse protection on eligible approved advances.
- Requirements change with scale, but the readiness signals do not: terms requests you currently decline, aged receivables nobody has contacted, and credit limits that have not been reviewed since onboarding.
What Is B2B Credit Automation?
B2B credit automation is the use of software to run the credit-to-cash cycle without manual review at each step. It covers assessing buyer creditworthiness, assigning credit limits and payment terms, issuing and tracking invoices, reconciling payments, and following up on overdue balances. The goal is to make extending trade credit a repeatable, rule-driven process instead of a case-by-case judgment call.
It is distinct from consumer credit automation in three ways. Buyers are businesses, so the underlying data is commercial (trade references, business credit files, payment history with other suppliers) rather than personal credit. Order values are larger and less frequent. And the credit decision usually has to happen inside a sales conversation or a checkout flow, where a two-day turnaround loses the order.
Where the Manual Credit-to-Cash Workflow Breaks
Five stages, and each one has a predictable failure mode.
| Stage | Manual process | Where it breaks |
|---|---|---|
| Credit application | PDF or web form, emailed to AR | Incomplete data, no validation, sits in an inbox |
| Credit decision | Pull a bureau report, call trade references, apply judgment | Takes 1 to 5 days, inconsistent between reviewers, no audit trail |
| Terms and limit assignment | Set in the ERP or on the invoice by hand | Limits go stale, no re-review as buyers grow or deteriorate |
| Invoicing and reconciliation | Invoice from the ERP, match payments by hand | Partial payments and short pays create write-off backlog |
| Collections | Someone emails at 30, 60, 90 days past due | First to slip when the team is busy, which is exactly when AR is worst |
The compounding cost is not any single stage. It is that a slow decision at stage two produces a lost order, and a neglected stage five produces a receivable you eventually write off. Both show up as cash flow problems long after the process failure that caused them.
The Five Components of a B2B Credit Automation Stack
1. Credit decisioning
Automated assessment of buyer creditworthiness using commercial data. A decisioning engine pulls business credit files, trade payment history, and firmographic signals, then returns an approve, decline, or limit recommendation. The value is speed and consistency: the same buyer profile gets the same answer regardless of who is looking at it.
What to evaluate: how many data sources feed the decision, whether decisions return in seconds or hours, whether limits are re-reviewed automatically, and whether you can override.
2. Terms and credit limit assignment
Once a buyer is approved, the system assigns a limit and a terms option (Net 15, 30, 60, or 90) and enforces it. This matters most at ecommerce checkout, where the terms option has to appear as a payment method with an approved limit already attached, not as a request form.
3. Accounts receivable automation
Invoice generation, delivery, payment acceptance, and reconciliation. Automated AR means invoices issue on a trigger rather than a person, payments post against the correct invoice without manual matching, and the ledger syncs to accounting. This is where the labor savings concentrate.
What to evaluate: which accounting and ERP systems sync natively, whether reconciliation is automatic or assisted, and which payment methods buyers can use (ACH, wire, card, check).
4. Collections
Scheduled reminders before and after the due date, escalation paths, and follow-up that runs without someone remembering to send it. Newer approaches use AI agents to handle the outreach and the follow-up sequence directly. Resolve's position on this: our agents collect your overdue invoices, or we advance the cash today and collect them ourselves.
5. Financing or risk transfer
The optional fifth component, and the one that changes the economics. Automating the first four makes the process faster but you still carry the receivable and the credit risk. Financing converts the approved receivable to cash now. Risk transfer moves the default exposure off your balance sheet. They can be separate or bundled.
Most sellers automate components 1 and 3, leave 4 to a person, and never address 5. That combination still leaves cash tied up in terms and default risk on your books.
Manual vs Automated: What Actually Changes
| Dimension | Manual | Automated |
|---|---|---|
| Credit decision turnaround | Days | Seconds to minutes |
| Decision consistency | Varies by reviewer | Rule-driven and auditable |
| Terms at ecommerce checkout | Not possible | Terms as a payment method |
| Invoice reconciliation | Manual matching | Automatic posting and sync |
| Collections follow-up | Depends on capacity | Runs on schedule |
| Cash timing | Buyer's due date | At advance, where financing is included |
| Credit risk | On your balance sheet | Transferable, where non-recourse coverage applies |
How Requirements Change as You Scale
The five components stay the same at every size. What changes is what you need from each one.
| Stage | What credit automation has to solve | Where it usually lives today |
|---|---|---|
| Early terms program | Any decision faster than a manual bureau pull, one terms tier, invoices out of QuickBooks or Xero | Spreadsheet plus a credit report subscription |
| Established terms program | Multiple terms tiers, automatic limit re-review, reconciliation that keeps up with volume, collections that runs without a dedicated person | A part-time credit function plus an AR clerk |
| Multi-channel and multi-entity | Terms at ecommerce checkout and in the sales motion, consistent decisioning across channels, sync to a real ERP, reporting by entity or division | A dedicated credit team, ERP AR module, separate collections process |
| High volume and complex structures | Approval hierarchies, buyer parent and child account structures, API-level control, exposure reporting across the portfolio | Credit team, ERP, financing line, sometimes credit insurance |
Two things worth noting. First, the amount of work does not scale linearly with revenue: it scales with buyer count and channel count, which is why a seller with many small repeat buyers often feels the pain earlier than one with a handful of large accounts. Second, larger operations rarely have a cleaner process, they have a bigger team running the same manual process, which is why the labor savings from AR automation tend to be largest at the top end.
Is Your Business Ready to Automate?
Work through these. Three or more and the manual process is already costing you more than the software would.
- You have declined or slow-walked a terms request in the last quarter because credit review would take too long.
- Your AR aging has balances past 60 days that nobody has contacted this month.
- More than one person makes credit decisions, and they would not reach the same answer on the same buyer.
- You sell online and buyers ask for terms that your checkout cannot offer.
- Someone spends more than a few hours a week matching payments to invoices.
- Your credit limits were set at onboarding and have not been reviewed since.
- Cash is tight specifically because revenue is sitting in receivables, not because of margin.
- A competitor won an account you had because they offered longer terms.
The common thread across sellers who automate is not revenue, it is that trade credit has become a constraint on growth rather than a tool for it. That happens to manufacturers, distributors, and wholesalers at every scale, including HVAC and plumbing suppliers, electrical distributors, industrial equipment manufacturers, medical device and pharmaceutical distributors, and construction materials suppliers.
The Vendor Landscape: Five Categories, Different Problems
The most common evaluation mistake is comparing vendors from different categories as if they were substitutes. They are not. Sort by what the product actually does, not by which segment its marketing names.
| Category | What it does | Choose it when | Limitation |
|---|---|---|---|
| B2B payment networks | Global payment and invoicing infrastructure, trade credit programs, managed AR. Example: TreviPay, operating in 30+ countries with multi-currency support. | Cross-border, multi-currency, and managed-service coverage is the requirement | Implementation is scoped as a multi-phase project with custom integration |
| Lenders and factors | Working capital term loans, invoice factoring, asset-based lending, PO financing. Example: Breakout Finance. | You need operating capital for payroll or inventory | Term loans create repayment obligations regardless of buyer behavior. Does not decide credit or automate AR |
| Trade credit insurers | Insure against buyer default | You want to keep your existing process and only cover the loss | Claims process, no speed improvement, no cash acceleration |
| ERP and accounting AR modules | Invoicing and reconciliation inside your system of record | You want AR automation only | No credit decisioning, no financing, no risk transfer |
| Integrated credit-to-cash platforms | Credit decisioning, terms, AR, collections, and financing in one workflow. Example: Resolve. | You want terms to be sellable without carrying the risk or the labor | Scoped to B2B seller workflows rather than general-purpose lending |
Three questions cut through most vendor conversations:
- Does this product make the credit decision, or do I still make it?
- Does it move the default risk off my books, or only insure or finance against it?
- How many separate vendors does the full credit-to-cash cycle require if I buy this one?
A factoring line answers no to the first. An AR module answers no to the first two. An integrated platform is the only category where the answer to the third is one.
How Resolve Approaches B2B Credit Automation
Resolve was spun out of the B2B side of Affirm and is supported by a team with experience at companies including Amazon and PayPal. More than 15,000 businesses use the platform. It covers all five components in one workflow:
- Business credit check: real-time buyer creditworthiness decisions using thousands of data points.
- Net terms financing: offer Net 15, 30, 60, or 90 while receiving advances on eligible approved invoices. Advance rates are determined by the transaction and buyer profile, up to 100% on eligible approved invoices.
- Accounts receivable automation: automated invoice generation, payment reconciliation, and accounting sync.
- Agentic collections: AI-powered workflows that automate payment reminders and follow-up activity.
- White-labeled payment portal: branded buyer dashboard accepting ACH, wire, credit card, and check.
The component that distinguishes the model is non-recourse protection. Where a buyer is approved through Resolve's credit engine and subsequently fails to pay, Resolve absorbs the covered loss and the seller keeps the advance. That transfers the covered credit risk on eligible approved advances away from the supplier, which is a different outcome from insuring the loss or financing against it. Pricing is tied to sales volume with no setup fees or monthly minimums, so cost scales with activity rather than sitting as fixed overhead.
On the integration side, the platform connects to accounting and ERP systems including QuickBooks Online, Xero, Oracle NetSuite, and Sage Intacct, with native ecommerce integrations for Shopify, BigCommerce, Magento 2, and WooCommerce, plus a REST API with webhooks and a sandbox environment for custom builds. That range covers both a seller running on QuickBooks and one running a NetSuite instance with a custom commerce front end.
What results look like
Each of these maps to one of the five components above.
| Customer | Industry | Component | Outcome |
|---|---|---|---|
| SS&SI Dealer Network | Security and fire distribution | Terms as a growth lever | 5x revenue growth |
| ConEquip | Construction equipment | Terms as a growth lever | 30% year over year growth |
| Archipelago Lighting | Lighting manufacturing | Credit decisioning speed | Tripled revenue, 90% increase in approval speed |
| Nandansons | Consumer goods distribution | Vendor consolidation | 75% growth after replacing two vendors with one workflow |
| Elston Materials | Concrete and masonry | Financing into supplier terms | Margins from 25% to 30%, credit checks from four days to a few hours |
| SDi Fire | Fire and life safety | Working capital release | Unlocked working capital, profit margins up 25% |
| Rebag | Luxury resale | AR automation | Order processing time reduced 50% |
| Trenchless Supply | Underground infrastructure supply | AR automation and collections | Eliminated manual AR chasing and inbound invoice requests, with advances on invoiced orders funding growth |
| Marshall Wolf Automation | Industrial automation distribution | Full credit-to-cash | Streamlined B2B payments while scaling |
| Shields Childcare Supplies | Childcare supply | Terms as a competitive offer | Won new business by offering Net 90 |
| Lift Foils | Watersports manufacturing | Risk transfer | Scaled pre-season orders without taking on more risk |
| Tern Bicycles | Bicycle manufacturing | Payment workflow | Increased sales orders with better B2B payment workflows |
Two patterns across these. Terms became a way to win orders rather than a cash flow cost, and the operational relief showed up in the same place every time: nobody was chasing invoices by hand anymore.
More stories across manufacturing, distribution, and marketplaces: Resolve customer case studies.
What Implementation Looks Like
Connect your accounting or ERP system, then connect your sales channels. Buyer credit assessments can be delivered quickly once the connection is live, and invoice, payment, reconciliation, and transaction data syncs back to your books.
Practical sequencing that works regardless of size:
- Connect accounting or ERP and get reconciliation clean.
- Turn on credit decisioning for new buyers only.
- Migrate existing buyers in cohorts, largest exposure last.
- Enable terms at checkout once decisioning is proven.
- Turn on automated collections across the full book.
Migrating existing buyers before reconciliation is clean is the most common cause of a stalled rollout. The second most common is enabling checkout terms before anyone has validated decisioning against buyers you already know, which removes your ability to sanity check the engine against your own credit history.
Frequently Asked Questions
What is B2B credit automation?
B2B credit automation is the use of software to run the credit-to-cash cycle without manual review at each step: assessing buyer creditworthiness, assigning credit limits and payment terms, issuing and tracking invoices, reconciling payments, and following up on overdue balances. It replaces case-by-case credit judgment with a repeatable, rule-driven process.
How long does an automated credit decision take?
Automated decisioning returns a result in seconds to minutes, compared with one to five days for a manual review involving a bureau report and trade reference calls. Speed is the main reason automation wins orders: at ecommerce checkout or in a live sales conversation, a multi-day turnaround loses the sale regardless of whether the buyer would have been approved.
Does automating credit remove my credit risk?
Not by itself. Automating decisioning, invoicing, and collections makes the process faster and more consistent, but you still hold the receivable and the default exposure. Removing risk requires a financing or risk transfer component. Resolve provides non-recourse protection on eligible approved invoices: if a buyer approved through Resolve's credit engine fails to pay, Resolve absorbs the covered loss and the seller keeps the advance.
How is this different from invoice factoring or a working capital loan?
Working capital term loans require repayment according to the financing agreement regardless of whether your buyers pay. Factoring advances funds against eligible receivables but does not decide credit, automate AR, or run collections for you. An integrated credit-to-cash platform handles the decision, the terms, the invoicing, the collections, and the advance in one workflow, so there is no handoff between four vendors.
Can B2B credit automation work with my existing accounting and ecommerce systems?
Yes. Resolve integrates with accounting and ERP systems including QuickBooks Online, Xero, Sage Intacct, and Oracle NetSuite, with automated syncing and payment reconciliation. Ecommerce integrations cover Shopify, BigCommerce, Magento 2, and WooCommerce, enabling net terms at checkout. A REST API with webhooks and a sandbox environment supports custom integrations.
What size company should automate trade credit?
There is no revenue threshold that decides this. Workload scales with buyer count and channel count rather than revenue, so a seller with many small repeat buyers often feels the pain before one with a handful of large accounts. The reliable signal is behavioral: if you have declined a terms request because credit review would take too long, or you have aged receivables nobody has contacted this month, the manual process is already costing more than the software.
Do we still control credit decisions if we automate?
Yes, and this is worth confirming with any vendor. Automation sets the default: the engine returns an approve, decline, or limit recommendation in seconds so that the routine cases clear without human review. Your credit policy still defines the rules, and manual override remains available for the accounts where relationship context matters more than the file.
What happens if a buyer does not pay their invoice?
With a working capital term loan, buyer payment behavior does not affect the loan obligation. Resolve provides non-recourse protection on eligible approved invoices: if a buyer is approved through Resolve's credit engine and subsequently fails to pay, Resolve absorbs the covered loss and the seller keeps the advance they received. This lets suppliers extend terms to grow sales while knowing eligible approved advances include non-recourse protection against the covered buyer credit risk.
This post is to be used for informational purposes only and does not constitute formal legal, business, or tax advice. Each person should consult his or her own attorney, business advisor, or tax advisor with respect to matters referenced in this post. Resolve assumes no liability for actions taken in reliance upon the information contained herein.
