The Formalization of Payment Economics: How Technology Has Created a New Financial Discipline
Issue 3 | The Payment Economics Journal | November 31st 2025
The Question No One Asked
Finance teams make thousands of decisions each day about how to pay suppliers. ACH or check. Wire or card. Immediate or batched.
For decades, finance teams treated these decisions as operational. The relevant questions focused on efficiency and control. Which method processes fastest? Which integrates with our systems? Which reduces exceptions?
This framing made sense because payment methods were economically equivalent. A check, an ACH transfer, and a wire all generated the same return: none. The choice was administrative, so we built administrative systems to handle it.
Then something shifted in the infrastructure.
Payment methods began to emerge that generate measurable financial return. Virtual card programs offering rebates. Dynamic discounting arrangements. Commercial card networks with reward structures. These methods existed alongside traditional payment rails, creating choice where none had existed before.
The adoption pattern reveals something interesting. Industry research shows that even as these methods matured and became widely available, utilization remained consistently low. Data from enterprise payment operations suggests that roughly 10-15% of eligible payment volume flows through yield-generating methods. The rest continues through traditional rails that generate no return.
This pattern raises a straightforward question. If methods exist that generate return, and if suppliers are capable of accepting them, why does most payment volume flow through methods that generate nothing?
The answer explains why Payment Economics is emerging as a formal discipline now, and why it could not have emerged earlier.
The Structure That Limited Adoption
Early implementations of yield-generating payment methods contained an economic asymmetry. They created measurable value for buyers while imposing operational costs on suppliers.
Consider virtual cards in their initial form. When a supplier received a virtual card payment, they experienced frictions that did not exist with traditional methods. Settlement took 5-7 days compared to 2-3 days for standard ACH. Reconciliation required manual processes, as card payments came through different channels than remittance information. The supplier's accounts receivable team absorbed complexity that their check or ACH processes did not create.
Meanwhile, the buyer captured the financial return. The rebate flowed to the company making the payment, while the company receiving the payment bore the operational burden.
From a supplier's perspective, accepting a virtual card meant accepting a payment method that served their customer's financial interest while increasing their own costs. The economics were extractive rather than reciprocal.
Suppliers responded rationally. Research confirms that suppliers declined these methods when given the choice, citing concerns about integration complexity and interchange fees.
This created what we now understand as a structural ceiling on adoption. Whether a buyer negotiated a 1% rebate or a 2% rebate made little difference if suppliers declined the method entirely. The constraint was not the rate of return. It was supplier acceptance of the method itself.
Finance teams attempted various approaches to increase adoption. They negotiated better rebate rates. They launched supplier enrollment programs. They ran education campaigns explaining the benefits of electronic payment.
Acceptance rates remained between 10-15%.
The problem was not communication or education. The underlying economics asked suppliers to absorb costs so that buyers could capture benefits. You cannot solve a structural problem with a process solution.
This remained the fundamental constraint until two things changed: systems evolved to make supplier behavior visible, and infrastructure shifted to create supplier-side value.
Why Supplier Acceptance Remained Invisible
Understanding why this constraint persisted requires examining how teams architected payment systems.
Teams designed legacy AP systems to manage workflow, not economic outcomes. These systems track which invoices they processed, which payments they executed, and what exceptions occurred. This is their design purpose and they perform it well.
But they do not track which payment method the company offered to each supplier, whether suppliers accepted or declined specific methods, why suppliers made those decisions, or how acceptance behavior changes over time. This is not a reporting gap. These systems never captured the underlying transaction data because teams built them when payment methods were economically neutral.
Treasury systems faced a parallel limitation. They tracked aggregate outcomes (total rebates earned, total card spend) but not payment-level economics. A Treasury dashboard might show "$875,000 in annual rebates," but it cannot answer "what percentage of suppliers accept cards when offered?"
This created an ownership gap. AP managed workflow. Treasury managed cash. Procurement managed supplier relationships. No function owned the question "what financial return are we generating from method selection?"
When no function owns a metric, optimization becomes structurally impossible. Not because people are neglecting it, but because the question has no natural home.
The discipline became possible when payment platforms emerged that teams architected specifically to capture payment-level economics. These platforms track which methods companies offered, which suppliers accepted, why suppliers declined, and how behavior changed over time.
Before this infrastructure existed, Payment Economics was conceptually sound but practically impossible. The discipline is emerging now because the measurement layer finally exists.
The Infrastructure Shift
Over the past two years, payment infrastructure underwent changes that altered the economics of method selection.
Modern payment rails began settling transactions faster. Industry analysis shows that speed has become the primary consideration in B2B payment method choice, with real-time payment capabilities fundamentally changing supplier expectations. Where earlier implementations took 5-7 days to settle funds to suppliers, newer infrastructure reduced this to 1-3 days. For suppliers accustomed to 30-45 day check processing cycles, this represented a meaningful improvement in cash conversion. The payment method that had once delayed their cash now accelerated it.
API connectivity between payment networks and supplier systems automated reconciliation processes that had previously required manual intervention. Remittance detail could flow directly to accounts receivable systems, eliminating the matching work that created operational burden. Supplier-side friction became supplier-side efficiency.
Platform architecture made value distribution structurally possible in ways that legacy payment systems could not support. A buyer could allocate a portion of captured yield back to suppliers, either through accelerated settlement, relationship credits, or direct value sharing. The economics shifted from purely extractive to potentially reciprocal.
Systems emerged that made individual contributor impact visible within finance organizations. When an AP team member's decision to route a payment through a yield-generating method becomes measurable, and when that contribution connects to recognition and career development, behavior changes. Work that organizations had treated as administrative overhead became work tied to financial performance.
Environmental contribution became embeddable within transaction infrastructure. Some platforms (including AP Copilot) now allocate a percentage of payment value to verified climate initiatives, creating board-reportable sustainability metrics from operational decisions. Where this capability exists, typically 1% of payment value flows to verified carbon removal or renewable energy projects. A payment decision becomes both a financial decision and an environmental one.
These developments happened in parallel across different parts of the payments infrastructure. Together, they created conditions where yield-generating methods could serve multiple stakeholders simultaneously.
When all stakeholders benefit, acceptance shifts from concession to preference. The supplier receives payment faster with less operational burden. The buyer captures financial return. The AP team member receives professional recognition. Measurable environmental impact accrues. The decision to accept becomes rational, not accommodating.
This structural shift explains why supplier acceptance can now reach 50-60% when infrastructure previously constrained it to 10-15%. The ceiling lifted because the underlying economics changed. Acceptance became economically rational for suppliers rather than economically costly.
Payment Economics works as a discipline when infrastructure exists to create positive-sum outcomes. Prior to these changes, optimizing payment method selection meant optimizing an extractive process. After these changes, it means optimizing a collaborative one.
The difference is fundamental.
Understanding What Drives Return
Once you recognize that payment method selection generates financial consequences, the question becomes how to measure and understand those consequences systematically.
Two factors determine total financial return. The first is the rate of return earned when yield-generating methods are used. The second is the proportion of total payment volume that actually flows through those methods.
We can express this relationship as:
Payment Yield = CR × SA
CR (Capital Return) represents the blended financial return rate across yield-generating payment methods. This includes rebates from commercial and virtual card programs, value captured through dynamic discounting, benefits from early payment programs, and return from payment float optimization.
SA (Supplier Acceptance) represents the percentage of total payment volume that flows through yield-generating methods rather than through traditional methods that generate no return.
The relationship between these variables reveals where financial return actually originates.
Consider two companies, each processing $500 million in annual supplier payments.
The first company has negotiated excellent rebate rates. Their CR is 1.5%, among the best in their industry. However, only 10% of their payment volume flows through methods that generate this return.
Payment Yield: 1.5% × 10% = 0.15%
Annual return: $750,000
The second company has average rebate rates. Their CR is 1.2%. However, 60% of their payment volume flows through yield-generating methods.
Payment Yield: 1.2% × 60% = 0.72%
Annual return: $3,600,000
The second company generates nearly five times more total financial return despite having inferior rebate rates.
This comparison demonstrates the central insight of Payment Economics: Supplier Acceptance optimization produces larger absolute returns than rebate rate optimization.
The reason becomes clear when you examine the possible range of each variable. CR has natural constraints. Even with exceptional negotiating leverage, commercial rebate rates rarely exceed 2%. The range of achievable improvement runs from perhaps 0.5% to 2%, a spread of 1.5 percentage points.
SA operates across a much wider range. Current enterprise average sits around 10-15%. Infrastructure improvements have demonstrated SA reaching 60-70%. The range of possible improvement spans 50+ percentage points.
When two variables multiply, improving the variable with the wider range produces larger absolute impact. The mathematics direct attention to where optimization creates value.
Most finance organizations today can tell you their CR. They know their rebate rates. They track total cash back earned.
Very few can tell you their SA. They cannot answer what percentage of payment volume flows through yield-generating methods. They do not know which suppliers accept which methods or why.
This asymmetry explains why Payment Yield remains low. Companies optimize the variable they can measure while the variable that drives absolute return remains invisible.
Payment Economics as a discipline focuses on making SA measurable and optimizable.
Observing The Principle In Practice
A mid-market manufacturer processing $85 million in annual supplier payments considered their payment operations fully optimized. Their AP team processed invoices efficiently. Their Treasury function had negotiated competitive rebate rates. When they calculated annual rebates captured, the total was $107,000.
No one questioned whether more was possible because no one had formulated the question itself.
Then someone in finance asked a different question: What percentage of our total payment volume actually flows through the methods generating that return?
Extracting this answer required manual effort, as their AP system tracked invoice processing but not method-level economics. When they finally assembled the data, the answer was 9%.
If 9% of volume generated $107,000 in return, what was happening with the remaining 91%?
The remaining volume flowed through checks and standard ACH. These methods generated zero return. The legacy AP system routed suppliers to these payments through default rules that had gone unexamined for years.
Their Payment Yield was 0.13%. They were capturing $107,000 annually, but simple arithmetic suggested $522,000 remained uncaptured.
The constraint was Supplier Acceptance.
They implemented a payment platform designed to make SA visible and optimizable. Over six months, SA improved from 9% to 53%. With CR held constant at 1.5%, Payment Yield rose from 0.13% to 0.74%. Annual return increased from $107,000 to $629,000.
The $522,000 improvement came from three sources.
First, routing optimization. The platform revealed that a portion of suppliers could already accept yield-generating payment methods, but legacy routing rules directed their payments to checks or ACH instead. These suppliers required no conversation, no enrollment, no education. They needed corrected routing logic.
Second, targeted supplier engagement. A larger portion of suppliers could accept yield-generating methods but did not currently do so. The platform provided visibility into who these suppliers were and why they had declined previously. This allowed targeted conversations where AP team members could explain specific value: faster payment receipt, simplified reconciliation, optional value sharing arrangements.
Third, employee alignment. When Payment Yield became a visible metric and individual contribution to its improvement became measurable, behavior changed within the AP function. The company implemented a recognition program that tracked each team member's contribution to SA improvement. AP staff could see how their routing decisions and supplier conversations affected overall Payment Yield. Administrative work became work tied to financial performance. Team members engaged proactively in supplier acceptance optimization rather than treating it as background activity. The platform made individual impact visible. The recognition program connected that impact to career development and performance reviews.
The improvement required no changes to rebate rates, no renegotiation of supplier contracts, and no addition of headcount. It came from recognizing that payment method selection is an economic decision and deploying infrastructure that made that decision systematic rather than default-driven.
This case represents early evidence that the discipline works. Payment Economics as a formal framework is young. The proof library is growing but still small. This single case study does not constitute comprehensive validation across industries, company sizes, and supplier compositions. What it does validate is the principle: when SA becomes visible, when infrastructure enables positive-sum economics, and when accountability exists for the metric, financial return follows. The framework predicts what should happen. This case demonstrates it happening. Additional case studies across different contexts will determine how consistently the principle holds and where natural constraints limit its application.
The ceiling at this company appears to be approximately 65% SA. The remaining suppliers face structural barriers: regulatory constraints, technical limitations, or strong requirements for specific settlement characteristics that yield-generating methods cannot yet accommodate. But the movement from 9% to 53% demonstrates that the historical ceiling of 10-15% was artificial.
What Constrains SA Optimization
Not every supplier can or will accept yield-generating payment methods. Understanding these constraints helps set realistic expectations for what SA improvement is achievable.
Structural barriers limit some suppliers regardless of infrastructure improvements. Government agencies often require ACH or wire transfers due to regulatory mandates. Healthcare providers operating under specific compliance frameworks may face restrictions. Utilities and regulated industries sometimes have limitations on acceptable payment methods.
Supplier leverage plays a role. Large, sophisticated suppliers with significant pricing power may insist on their preferred payment methods as a condition of doing business. A Fortune 500 vendor supplying critical components has different negotiating dynamics than a mid-market service provider.
Research shows that interchange economics affect supplier willingness to accept card payments. When a supplier accepts a card, they typically pay 2-3% in interchange fees to the card network. The value proposition must account for this cost. Faster settlement, automated reconciliation, and potential value sharing must deliver enough operational benefit to offset the interchange expense. For suppliers with tight margins or high-volume, low-margin transactions, this math may not work regardless of infrastructure improvements.
Industry-specific dynamics create variation in achievable SA. Distribution companies with diverse supplier bases may see SA reach 60-70%. Manufacturing companies with concentrated spend among a few large vendors may plateau at 40-50%. Professional services firms with mostly individual contractors may achieve 70%+. The ceiling depends on supplier composition, not just infrastructure quality.
The $85M manufacturer case study demonstrates what becomes possible when infrastructure removes historical constraints. The 9% to 53% improvement occurred over six months, which represents strong execution. Most companies should expect 12-18 months to achieve similar results, depending on supplier complexity, internal change management capability, and starting baseline. The movement itself validates the principle. The timeline and ceiling will vary by context.
The Aggregate Opportunity
Analysts project that U.S. businesses process approximately $35 trillion in B2B payments annually, with non-cash B2B transactions showing an 11.4% CAGR through 2028. Data from enterprise payment operations suggests the current average Payment Yield across this volume sits around 0.175%.
At 0.175% Payment Yield, the aggregate return captured annually is approximately $61 billion.
The infrastructure changes described earlier create different economics. Industry research demonstrates that virtual cards will be the fastest-growing B2B payment channel over the next five years, with a 370% increase in transaction value. Modern payment platforms demonstrate SA reaching 60-70% when suppliers receive faster settlement, reconciliation automates, value sharing becomes possible, and employee incentives align. Competitive rebate rates cluster around 1.5% CR when companies leverage card networks effectively and reach scale.
If the average enterprise moved to 65% SA and 1.5% CR, three things would follow. Payment Yield would reach approximately 1%. Aggregate return would reach approximately $350 billion. The gap would represent $289 billion in currently uncaptured annual value.
Not all payment volume is addressable. Government contracts, healthcare providers, utilities, and large enterprise suppliers with negotiated payment terms may face regulatory constraints or have sufficient leverage to require specific payment methods. The addressable opportunity varies by industry, supplier mix, and company size. But even accounting for these constraints, the majority of mid-market and enterprise payment volume remains unoptimized for SA.
At the individual company level, the opportunity scales linearly with payment volume:
Annual Payment Volume → Current PY (0.175%) → Achievable PY (1%) → Annual Gap
$100M → $175K → $1M → $825K
$500M → $875K → $5M → $4.1M
$1B → $1.75M → $10M → $8.25M
This is not speculative modeling. It is arithmetic applied to observed payment volumes, demonstrated SA achievement, and standard rebate rates.
The gap exists because infrastructure made SA optimization structurally impossible until recently. Companies optimized what they could measure (CR through rebate negotiations) while SA remained invisible.
The emergence of measurement infrastructure changed what is structurally possible.
Where to Begin
Payment Economics does not require organizational restructuring or multi-year implementation programs to start. It requires three immediate actions.
1. Calculate Your Current Payment Yield
Most companies can assemble a directional baseline using existing data.
Pull total payment volume for the past 12 months from your AP system. Pull total financial return captured from payments (card rebates, discounting captured, measurable float benefits) from Treasury.
Calculate: Payment Yield = (Total Financial Return) ÷ (Total Payment Volume)
Example: $875,000 in rebates ÷ $500 million in payments = 0.175% Payment Yield
Next, decompose into CR and SA:
CR = (Total Financial Return) ÷ (Payment Volume Through Yield Methods)
SA = (Payment Volume Through Yield Methods) ÷ (Total Payment Volume)
Verify: CR × SA should equal your Payment Yield
This decomposition reveals which lever determines your current performance. If SA is low (under 20%) while CR is competitive (1.2% or higher), you have identified the constraint.
2. Make Supplier Acceptance Visible
Even without specialized infrastructure, you can gain directional insight.
Pull a list of your top 100 suppliers by payment volume. For each supplier, manually identify payment method currently used, acceptance status for yield methods, and settlement timeframe.
This exercise takes 2-3 hours and reveals critical patterns:
What percentage of your top suppliers currently accept yield-generating methods?
How much of your payment volume goes to suppliers who accept versus suppliers who decline?
Which suppliers might accept yield methods if offered faster settlement or better reconciliation?
The goal is visibility into whether SA is constrained by supplier inability (they cannot accept yield methods), supplier preference (they can but choose not to), or internal routing (they can and would, but we route them elsewhere).
3. Assign Ownership and Create Accountability
Ask: who in our organization owns Payment Yield as a metric?
If the answer is unclear, create accountability. Assign someone (whether in Treasury, AP, or a dedicated role) to own this metric. They should track Payment Yield monthly, report trends to finance leadership, understand what drives changes in CR and SA, and identify opportunities for improvement.
Add Payment Yield to your monthly finance review alongside DSO, DPO, and working capital metrics. Even if the number starts low, making it visible creates momentum.
What gets measured gets managed. What gets managed improves.
These three actions take less than a week to complete. They require no new systems, no budget approval, no organizational change. They establish your baseline, reveal your constraints, and create accountability for improvement.
Timeline expectations: Meaningful SA improvement typically occurs over 12-18 months as supplier relationships evolve, routing logic improves, and organizational behavior changes. The $85M manufacturer achieved 44 percentage points of SA improvement in six months, which represents exceptionally strong execution. Your timeline will depend on supplier complexity, organizational change management capability, and how much low-hanging fruit exists in routing optimization. Starting measurement now establishes the baseline that makes improvement visible.
The Invitation
Payment Economics is emerging as a discipline because three conditions aligned simultaneously.
Infrastructure evolved to create positive-sum outcomes. Industry research confirms that supplier enablement programs can streamline onboarding and create smoother paths to improved payments for both buyers and suppliers. Suppliers now benefit from faster settlement and easier reconciliation. Employees can be recognized for optimizing method selection. ESG value can be embedded in transaction flows.
Measurement became possible. Platforms emerged that capture payment-level economics, supplier acceptance behavior, and method-specific return. These platforms made the invisible trackable.
The opportunity became material. With $35 trillion in U.S. B2B payments and a $289 billion gap between current and achievable Payment Yield, the financial impact is too significant to remain unmeasured.
The framework is sound: Payment Yield = CR × SA
The insight is validated: Supplier Acceptance optimization drives more absolute return than rebate rate optimization.
The proof exists: Companies moving from 9% SA to 50%+ SA are capturing multimillion-dollar improvements with no changes to rebate programs.
What remains is formalization.
Every established discipline in finance began this way. Portfolio theory started with a few practitioners who recognized that asset allocation determined return. Behavioral economics emerged when researchers documented that decision patterns created measurable inefficiencies. Working capital management formalized when companies realized cash timing was optimizable.
Payment Economics is following the same trajectory.
The companies engaging with this framework now are not adopting an established practice. They are helping create one. They will define what benchmarks matter and how they are measured. They will determine where Payment Yield ownership sits organizationally. They will establish what infrastructure becomes standard and how best practices evolve.
Over the next 12 months, the proof base will expand. More companies will measure Payment Yield. More case studies will document SA improvement across different industries and contexts. The framework will be tested against diverse supplier compositions, payment volumes, and organizational structures. What works consistently will become standard practice. What proves context-dependent will inform implementation guidance.
This is the nature of disciplines in formation. The early practitioners write the standards. The companies that formalize Payment Economics first will shape how the discipline develops while others are still evaluating whether it matters.
If you calculate your Payment Yield this week, you are early. If you make SA visible and assign ownership, you are positioning yourself to shape how this discipline evolves. If you implement infrastructure that captures payment-level economics and creates incentive alignment, you are actively formalizing the practice.
Finance organizations are formalizing the discipline right now, through this journal and through the teams implementing these frameworks. Your choice is whether to observe that process or participate in it.
Platforms Applying Payment Economics
AP Copilot: Virtual card platform maximizing supplier acceptance and cashback.
Learn more: apcopilot.com
About The Payment Economics Journal
The Payment Economics Journal is published by Clear Paths Growth to formalize the discipline of treating payments as economic assets rather than administrative overhead.
The frameworks and metrics presented in this journal emerged from observing leading practitioners who were generating measurable financial performance from payment operations before the discipline existed to explain it.
Media inquiries: advisory@clearpathsgrowth.com
Suggested Citation
Jasinski, D. (2025). The Formalization of Payment Economics. The Payment Economics Journal, Issue 3. Clear Paths Growth.
Authorship & Intellectual Property
Payment Yield and the Payment Yield Model were originally defined by Daniel Jasinski and published by Clear Paths Growth in The Payment Economics Journal (November 2025).
All models, frameworks, and definitions presented herein are the intellectual property of Clear Paths Growth LLC. Brief quotations are permitted with proper attribution. Commercial reuse or derivative implementation requires written permission.
© 2025 Clear Paths Growth LLC. All rights reserved.
References
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Citizens Bank. (n.d.). Virtual Cards: Simplifying Supplier Payments. Retrieved from https://www.citizensbank.com/corporate-finance/insights/virtual-cards-simplifying-payments.aspx
Juniper Research. (n.d.). B2B Payments to Hit $224 Trillion by 2030 Globally, Driven by Emerging Market Expansion. Retrieved from https://www.juniperresearch.com/press/b2b-payments-to-hit-224-trillion-by-2030-globally-driven-by-emerging-market-expansion
PYMNTS. (2024, June 13). Can Virtual Cards Overcome Their 'Achilles Heel' of Supplier Acceptance? Retrieved from https://www.pymnts.com/news/b2b-payments/2024/can-virtual-cards-overcome-their-achilles-heel-of-supplier-acceptance
PYMNTS. (2025, January 9). Understanding the Supplier's Role in Driving Virtual Card Acceptance. Retrieved from https://www.pymnts.com/news/b2b-payments/2025/understanding-the-suppliers-role-in-driving-virtual-card-acceptance
PYMNTS. (2025, June 2). Getting on Board: How Supplier Enablement Is Unlocking the Benefits of Virtual Cards. Retrieved from https://www.pymnts.com/tracker_posts/getting-on-board-how-supplier-enablement-is-unlocking-the-benefits-of-virtual-cards
Worldline. (2025, September). 10 Key Payment Trends Shaping 2025. Retrieved from https://worldline.com/en-us/home/main-navigation/resources/blogs/10-key-payment-trends-shaping-the-market-in-2025-and-why-they-matter-for-software-providers