The cost of a dispute does not go down when your team gets better at handling it. That sentence contains the CFO and CEO problem with dispute management.
Operational improvement, including better training, clearer processes, and more experienced dispute or chargeback analysts, reduces the cost per case at the margin. But it does not change the underlying structure. Every new cardholder adds to the dispute caseload. Every increase in card volume adds to the team's workload. The cost of dispute management grows with the portfolio, and there is no version of manual operations that changes that relationship.
Zero-touch dispute resolution has emerged as a commonly used term for the structural alternative. Here is what the automated pipeline looks like.
What zero-touch dispute resolution actually means
A zero-touch dispute does not require a dispute analyst to initiate, classify, investigate, or submit it.
When a cardholder raises a claim, the system identifies the transaction type. It checks the relevant pre-dispute intelligence layer: the network-level signal that indicates whether a merchant has flagged the transaction for resolution before a formal chargeback is raised. It scores the case against first party fraud or serial disputer indicators using the full cardholder transaction history, distinguishing a genuine fraud incident from a cardholder who authorised a purchase and then disputed it. It resolves, deflects, or captures the claim and submits the appropriate scheme response on the correct deadline.
No case was touched. The dispute analysts’ queue is shorter. The write-off rate is lower. The cardholder receives a resolution or feedback. That is the dispute management ROI case in its simplest form: the better cardholder experience, at a fraction of the operating cost.
This is already happening at scale. Modernising operations with automated dispute workflows is delivering massive structural relief, reducing claim volumes by 30-40% and cutting friendly fraud losses by 40-50%, according to EY's data on financial dispute automation. By replacing fragmented, multi-step tracking with intelligent intake, institutions are stripping out manual friction and compressing resolution timelines from weeks down to a single day.
This exact operational shift is visible in practice: PostFinance, one of Switzerland's largest card issuers, reduced its transaction recording time from 30 minutes down to just 5 minutes while boosting processing capacity nearly fivefold. Meanwhile Cembra, a leading Swiss consumer credit issuer, now routes 75% of inbound chargeback requests through a self-service virtual agent to eliminate back-office friction, and two in three of those are resolved or deflected with zero manual intervention.
Why first-party fraud makes the manual model increasingly expensive
First-party fraud has surged to account for 36% of all global fraud events according to the LexisNexis Global State of Fraud and Identity Report, and the operational impact is compounding rapidly, with 64% of merchants reporting increasing rates of first-party misuse in the past year, as noted in the Merchant Risk Council's 2026 Global eCommerce Payments and Fraud Report.
A cardholder who disputes a transaction they authorised looks, in a manual workflow, like any other complainant. The claim is genuine in the sense that the cardholder believes their grievance is valid. But the outcome (writing off a transaction that should not be written off) is an issue that compounds across a portfolio.
Manual dispute operations have limited means to score this risk reliably before the analyst’s decision. Chargeback automation platforms that apply intelligent classification to the full transaction history catch it more accurately and consistently. Dispute management platforms specifically designed for first-party fraud optimisation resolve or deflect cardholder confusion at the point of intake before formal chargeback cycles begin, protecting margins.
The volume is also growing. Annual global chargeback volumes are forecasted to scale to 324 million transactions by 2028, marking a 24% vertical climb in a three-year window, according to data from Mastercard’s Global Chargebacks Outlook. At that scale, an operation that cannot distinguish first-party misuse from genuine fraud at intake carries an expanding write-off exposure embedded in its operating cost.
The financial case at current manual rates
Processing a disputed transaction manually costs financial institutions an average of $9 to $10 in processing overhead per case. For a mid-to-large issuer managing 100,000 disputes per month, this hidden operational drain quietly scales to over $11 million annually in direct handling costs alone, long before fraud write-offs or regulatory SLA penalties are factored into the equation.
Transitioning to an automated workflow delivers a 40-50% reduction in friendly fraud losses. The savings accrue because decisions are executed with greater speed, accuracy, and consistency at intake, rather than dragging staff through weeks of manual data compilation.
The regulatory cost of missing SLAs
There is also a compliance cost to manual operations that does not appear in the dispute budget line.
PSD2 requires EU issuers to provisionally credit cardholders for unauthorised transactions within one business day of receiving a claim. The UK's Payment Systems Regulator mandates APP fraud resolution within five business days. These are not aspirational targets. They are existing legal obligations.
Manual dispute operations routinely miss these windows when volumes spike. A fraud event, a seasonal peak, or a product launch stretches a team that was sized for steady-state workloads. The resulting compliance breach carries regulatory consequences that have nothing to do with team quality and everything to do with the structure of the operation.
Automated dispute workflows do not miss SLA deadlines because of volume spikes. That is the structural consequence of leveraging dispute platforms designed for deadline-sensitive workflows.
What the dispute management workflow actually requires
Three capabilities are consistently present in platforms achieving the published automation benchmarks.
- Pre-dispute network intelligence: direct integration with the Ethoca and Verifi networks that carry real-time signals from merchants about transactions under query. These signals allow resolution before the formal chargeback cycle begins, reducing both scheme fees and processing time.
- First-party fraud or serial disputer scoring: intelligent classification models that assess the full cardholder transaction history to identify misuse patterns. Platforms with this capability resolve or deflect claims at the point of intake, before a formal case is opened.
- Rule-based automation: the ability to submit straightforward cases (e.g., Card-Not-Present) to Visa or Mastercard without a dispute analyst in the approval chain. For eligible cases, this delivers fully automated resolution and resolves the SLA compliance problem at the structural level.
The CFO question
At what card volume does your current dispute model require an additional hire that a different model would make unnecessary?
Our agentic dispute management solution, Amiko, is built to break the linear relationship between portfolio growth and dispute operations headcount. Its platform combines pre-dispute merchant intelligence, friendly-fraud and serial disputer scoring, and many rule-based automation capabilities, all enabling best-in-category zero-touch dispute resolution performance. Amiko is built for EU and US regulated issuers: GDPR-compliant, PCI DSS certified, and ISO 27001 accredited. See how this works against your current dispute volumes.