The payments ecosystem is rapidly transforming as artificial intelligence transcends from piloting to operational infrastructure. Today, issuers, card networks and processors utilize AI for fraud detection, dispute management and real-time risk assessment. Beyond 2025, merchants will require effective use of AI in transactions, customer service and back-office processes in order to keep up with competitors.
Common Challenges When Deploying AI
AI isn’t a silver bullet. Bad data still results in mediocre models, which can either lead to more declines or bias in manual oversight. RTPs shorten the time to make a decision—models must score the transaction and potential payee in nanoseconds. Compliance units require an audit trail of models and third-party applications—from the source of training to the audits and back-up options. Finally, more ecommerce traffic comes from automated shopping agents and scripted behavior. Merchants must welcome agents that can assist but also filter out the negative forms of automation that drive up costs or expose organizations to fraud risk.
The Role of Your Merchant Account and Gateway
With AI, what you have for a current merchant account and gateway is all. Gateways access the data from device/network/behavior that the modeling provides so it can implement added risk rules, targeted 3-D Secure, or even step up checks based upon a need only when risk is warranted[1]. This means processors ultimately help submit chargebacks and documentation, so work with those who make their approval rates and fraud rates public, support proper ISO 20022 fields, honest passthrough of fraud signals, and provide a solid dispute API[2]. This will integrate your AI within the data from actionable results you know to be true.
Prepping for AI Shopping Agents
Major assistants are now placing orders on behalf of consumers. Configure them as a new customer segment in identity markers, traffic controls, and reporting. Ask your gateway or WAF how agent identity will be conveyed, establish allowlists for trusted agents and log conversions differently so marketing can attribute value. Fine tune bot protections so that exploitive automation is filtered, but not the helpful hands with high intent orders.
PCI DSS v4.0: What's New 2025
Previously future dated requirements are now enforceable and impact audits and scoping. Pay particular attention to stronger multi factor authentication, targeted risk assessments for custom flows like pay by link and phone orders, stronger key management and consumer facing security statements. Ensure service providers have attestations in compliance with v4.0 and your documentation shows alignment. Now is the time to close gaps before the peak season catches you off guard with scoping realities.
ISO 20022: An Opportunity to Use New Fields for Improved Outcomes
Fielded data means better scoring, faster reconciliations and stronger dispute documents. Map ordering, invoicing and shipping fields to newly created ones, normalize names and addresses, store policy agreeance alongside transactions. Ensure these fields can be surfaced in reporting so that finance, support and risk can track a payment from the moment it was input through to supporting evidence without manual effort[3].
Instant Payments: Updated Risk Window and Operations Policy
Funds disbursed via offerings like FedNow or RTP are immediate and harder to retract[4]. Create a separate policy that screens beneficiaries prior to funding, adds out of band validation for first time or large amounts disbursed, flags changes to beneficiary information as something to investigate. Train support with definitive talking points, establish refund policy up front and track exceptions daily so they do not become compounding losses.
Six Core Strategies For Using AI In Payment Processing
Strategy 1: Capture Better Signals At Checkout
The better the quality of inputs, the better the model. Add device/browser fingerprints, velocity checks, IP reputations and behavioral signals like typing speed or copy/paste on fields. Standardize addresses/names. Keep consent and policy acknowledgement associated with the transaction, i.e., refund windows, delivery timeframes. These are all factors that increase approval accuracy and bolster subsequent dispute rationale, which cuts time to resolution and shields chargeback thresholds.
Strategy 2: Use Targeted Step Up Instead of Blanket Friction
AI should determine whether friction is needed, not a static rule. If there's excess risk, send the consumer down a 3-D Secure path or additional verification effort. If the risk is low, let the transaction go through without interruption. This raises approval rates while still curbing fraud and friendly chargebacks. Should reference segments, monitor conversion, approvals and liability shifts so step up rules remain in alignment with business objectives.
Strategy 3: Modernize Chargeback Workflows With AI
Disputes are still all about data and timeliness. Leverage AI to compile packets for order history, device match, delivery evidence, correspondence and policy consent. Trigger appropriate parties to receive alerts and drafts of responses that analysts can approve. Monitor success rates per issuer, product and reason code to drive policy changes; over time this data will drive the best step up conditions, shipping methods and descriptors.
Strategy 4: Separate Instant Payments From Card Rules
Real time rails like FedNow and RTP settle quickly with low reversal support. Separate policies should exist on pre-credit screens and beneficiary risk scores for payment conditions as well as out of band verification for high-value payments or first time recipients. Customer service needs to be trained on these claims as well including clear scripting, identity authentication and reconciliation templates. Treat this flow as its own product—reporting and risk thresholds should not be held to the same standards as card rules.
Strategy 5: Close The Loop With Finance And Support
Report fraud decisions/disputes back to customer service and finance teams. Support needs background on escalations including risk scores, device matches and history; finance needs a clean handoff for transaction, invoice and ledger mapping. When AI-backed systems can communicate with back-office systems, you reduce manual adjustments and time to resolution. This facilitates month-end reconciliation and leadership trust in reporting.
Strategy 6: Govern Your Models Like Any Other Critical System
Create a brief model register that includes purpose, owners, inputs, performance, monitoring requirements and fallback. Ask your vendors for the same. Document all changes and have a convenient playbook for incident response. This supports emerging regulatory requirements and keeps teams aligned when something drifts. Good governance avoids undesirable performance shifts that drive approvals down or fraud losses up in times of high volume activity.
What To Expect Next
In a year’s time, even more AI shopping bots will order for users, payout and transfer flows will get even more rich data from ISO 20022 and fraud and authentication solutions will become more aligned than ever. Compliance teams will regard AI as they would any other high risk system, with testing and monitoring requirements to be documented. Merchants that garner improved signals, smartly direct friction, and unify dispute documentation will receive higher approvals and experience fewer chargebacks through 2026.
Implementation Plan For Q4 2025
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Security and compliance
Close remaining PCI v4.0 gaps, refresh multi factor authentication and encryption policies, and re-scope any custom flows such as pay by link or phone orders[5]. -
Fraud stack
Turn on device and behavior intelligence, set velocity limits, and configure step up only for risky segments. Track approval rate and false declines weekly. -
Agent readiness
Coordinate with marketing and security to admit trusted agents and log their performance. Update bot rules to avoid blocking legitimate assistants. -
Data and disputes
Standardize evidence capture and map ISO 20022 fields into reporting. Monitor chargeback win rate by issuer and reason code. -
Instant rail readiness
Build a separate policy for FedNow and RTP. Add beneficiary verification for new or edited recipients and review outliers daily.
FAQ
Q: What is AI and why is it relevant in payment processing in 2025?
A: AI refers to machine learning systems that score risk, authenticate customers, compile dispute evidence and fine-tune approvals in real-time. It’s relevant in 2025 because networks and processors have integrated this into platforms and subsequently merchants experience immediate changes in approvals, fraud losses and chargeback wins. As a result of better device signals, behavior analytics, and quality of structured data (thanks to ISO 20022), AI will function to reduce false declines, catch synthetic identities in their infancy, and allow finance teams to better align reconciliation[6]. This means merchants get more revenue from the same traffic with less time spent operating.
Q: Will AI increase approvals while not letting in more fraud?
A: Yes, if implemented cautiously. This means coupling richer features at checkout with targeted step up and ongoing monitoring. If risk is low, let the transaction go through—no friction. If risk is high, apply 3-D Secure or a second factor only where it’s useful to the consumer. This way conversion is preserved and liability can be shifted where fraud is perceived. Stakeholders should monitor approval rate, fraud rate and false declines by segmentation and continually refine thresholds as patterns emerge. Over time, AI learns from approved vs blocked traffic which improves fraud outcomes and chargeback ratios.
Q: How do we measure AI payments ROI?
A: Start with a baseline—approval rate, fraud losses, false declines, chargeback rate, time to first response in disputes and analyst hours per case. Post device/behavior signals or step up, monitor shifts in each metric and convert to dollars. For example, the difference a single point makes in approval rate during busy times is impressive enough. Quicker responses in disputes and higher win percentages decrease chargeoffs and fees. Factor in operational efficiencies from reduced manual review time and more streamlined reconciliation. Add all revenue opportunities and cost savings together for program ROI compared to cost of tools and labor.
Q: Do small merchants need to worry about real time rails and ISO 20022?
A: Yes, especially if you send or receive payouts, conduct high value transfers or foresee having instant refunds in your customer service repertoire. Your provider will handle technical connections but since settlement happens faster, reporting is upgraded and dispute evidence is more accurate, you will benefit from your data being properly mapped. ISO 20022 brings fields that help align orders, invoices and delivery proof to the original transaction from a single payment. Even a small team could benefit by aligning order-level information and asking their gateway to expose those fields within reports/APIs.
Q: Where do we start if we have little resources?
A: Start with basic data capture and targeted friction. Power up device fingerprinting, IP reputation, and basic behavior analytics. Normalize checks out addresses and names. Enable 3-D Secure on higher-risk segments only—first time buyers; high-ticket items. Then standardize your dispute evidence checklist wherever it makes sense—policy consent, delivery confirmation, prior history; whatever it takes to leave no stone unturned. These actions generate measurable benefits without excessive engineering endeavors from development which position the enterprise for modeling benefit down the road. Monitor monthly results with a view to threshold adjustment so the program continues to get better.
Sources
- PCI Security Standards Council. “PCI DSS Resources and v4.0 Guidance.” Accessed August 2025.
- Federal Reserve. “Payments Systems and Compliance Standards.” Accessed August 2025.
- SWIFT. “ISO 20022 Migration and Standards.” Accessed August 2025.
- Federal Reserve. “FedNow Service, Program Overview.” Accessed August 2025.
- Visa. “Payment Security and Dispute Guidance.” Accessed August 2025.
- Mastercard. “Fraud and Security Solutions for Businesses.” Accessed August 2025.
