Chargeback Protection Best Practices and Tools

Chargeback types, hidden costs, and prevention best practices

How to Reduce Your Chargebacks

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Definition and Types of Chargebacks

What is a Chargeback?

A chargeback or “dispute” is the reversal of a credit card charge by a customer’s bank or payment processor. When a customer notices an unfamiliar charge on their statement, they can call the bank to contest the charge and the bank issues a refund. The digital business bears the financial impacts of repaying the customer and faces fees from the issuing bank.

A chargeback rate is a calculation of the number of chargebacks against the volume of sales. However, processors don’t reconcile chargebacks against the dates that the transactions actually occurred. For instance, Visa divides last month’s chargebacks by this month’s transactions. So, if a business had big sales—and normal chargebacks—in December, and those December chargebacks are calculated against lower January sales, they could show an unusually high chargeback rate. Even though it doesn’t reflect the “true” rate, higher fines and fees are charged.

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Chargeback Protection for Merchants

Types of Chargebacks

Tackling fraud can be difficult because it’s hard to identify and distinguish between criminal fraud, friendly fraud, and legitimate disputes. The ability to quickly and accurately identify and segment fraud can help mitigate challenges, improve operations, and increase revenue.

Criminal Fraud occurs when stolen credit card numbers are used to fraudulently obtain physical goods, digital goods, or services. This type of fraud is increasing twice as quickly as eCommerce sales and accounts for approximately two out of three chargebacks.

Friendly Fraud occurs when a consumer makes a legitimate purchase with their credit card and then enters a dispute with the issuing bank rather than requesting exchanges or refunds from the merchant. It can be malicious, but more often arises from a misunderstanding.

Legitimate Disputes occurs when problems with merchant setup, transaction data, or order processing results in poor user experience or consumer confusion — and lead to chargebacks.

Chargeback Types

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Negative Impacts and Hidden Costs of Chargebacks

Impact of Chargebacks

Chargebacks not only result in lost revenue and merchandise, they also bring increased fees and fines by processors. Merchants that exceed a defined chargeback threshold for a period of time are placed in an Excessive Chargeback Program, incurring additional monthly fees (sometimes thousands of dollars) until their chargeback rate is under control. Monthly penalties vary by card processor and depend on the number of consecutive months businesses are in the program. The higher the chargeback rate, the higher the fees and penalties. Excessive chargebacks can eventually lead to termination of a merchant account, possibly causing them to go out of business.

14 Direct and Hidden Costs of Chargebacks

Direct Costs
Lost Merchandise
Chargeback Fees
Shipping Costs
Potential Credit Card Penalties
High Transaction Fees
Network Termination
Operational Costs

Hidden Costs
Manual Reviews
Wasted Labor
Lowered Bank Authorization Rates
Opportunity Costs
Customer Acquisition Costs
Brand Loyalty
Customer Friction

Credit Card Chargeback Thresholds and Fraud Monitoring Programs

Card networks use monitoring programs to compel merchants and acquirers to reduce fraud and/or dispute levels. Merchants in an excessive chargeback program generally have three months to address their chargeback rates, or at least present a plan for doing so. Once a plan is created, they may have a compliance window of three to six months. In the worse-case scenario, the card brand could eliminate a merchant’s account and they would no longer be able to accept payments.

Card Programs

Visa Dispute Monitoring Program (VDMP) and Visa Fraud Monitoring Program (VFMP)

Visa’s strict thresholds mean merchants need to keep a close eye on their margin of error when it comes to risk outcomes. By accepting Visa cards at point-of-sale, merchants are responsible for controlling and preventing their own fraud incidents. Objectives of the program are to identify and remediate excessive dispute activity.

Visa Fraud Monitoring Program (VFMP)

Early Warning

Standard Program

Excessive Program

Threshold Criteria

0.65% of sales and $50,000

$75,000 in fraudulent transactions and 0.9% fraud: sales ratio

$250,000 in fraudulent transactions and 1.8% fraud: sales ratio

Visa Dispute Monitoring Program (VDMP)

Early Warning

Standard Program

High-Risk Program

Threshold Criteria

0.65% of sales and $50,000

100+ dispute count and 0.9% dispute: sales ratio

1,000+ dispute count and 1.8% dispute: sales ratio

Mastercard: Excessive Chargeback Merchant (ECM) or High Excessive Chargeback Merchant (HECM) programs

Mastercard can place merchants in one of two programs: Excessive Chargeback Merchant (ECM) and High Excessive Chargeback Merchant (HECM). Through network data, Mastercard automatically tracks chargebacks for all transactions, including eCommerce transactions, and notifies acquirers when an individual merchant ID has breached the compliance threshold. ECM is intended to reduce chargebacks and strengthen the integrity of the Mastercard Network.

Monthly Criteria:

Number of Chargebacks
100 to 200
300 or more

Basis Points
150 to 200
300 or more

Chargeback Prevention Steps

Preventing Chargebacks – The 3 Best Practices

Preventing chargebacks isn’t a once-a-month task or a discrete event that takes place at a single point in time. There are multiple prevention and interception “catch points” where you can take action to reduce chargebacks, product losses, and fees.

1. Stop bad transactions before they’ve been approved.

Automate the risk assessment by using an established fraud protection solution to scale commerce without increasing chargebacks.

• Advanced AI and Machine Learning: Automate decisions using advanced AI, Supervised and Unsupervised Machine Learning (ML) to reduce manual reviews, cut operating costs, and approve more borderline — but valid — orders.

• Customize Policies: Pairing continuous AI-driven technology with customized rules based on individual risk thresholds provides complete control to approve, decline, or review digital interactions and provide the most accurate assessment of risk.

• Multi-Dimensional Velocities: Measure velocities across multiple components in a purchase, including device, IP, payment, address, and phone number to prevent issues such as card testing.

• Link Identity Trust Signals: Analyze and link identifiers such as email address, shipping address, device ID, and Geolocation in order to confirm accurate identities in real-time.

2. Reduce chargebacks.

Avoid chargeback fees by intercepting a transaction before the issuing bank applies it as a chargeback.

• Friendly Fraud Solution. Reduce unnecessary payment disputes by allowing issuing banks to request information in real-time to help cardholders recognize a transaction at the time of inquiry.

• Chargeback Alerts. Avoid chargeback lag and intercept “bad” transactions even after they’ve been approved, to protect against product losses and chargeback fees.

• Business Intelligence Reporting. The ability to gain insights from transaction and chargeback data is essential for improving risk assessment and reducing false positives.

3. Win chargeback representments.

Winning chargeback disputes requires expertise plus robust transaction data.

• Improve Chargeback Disputes. Fraud prevention solutions that integrate or offer chargeback management services reduce the cost of chargeback disputes and improve win rates.

• Partner with Experts. Successfully managing chargebacks requires expertise that few online businesses can afford to maintain. Working with third-party providers that integrate with fraud prevention solutions can help avoid chargebacks and prevent them from occurring in the first place.

Using Fraud Prevention Platforms to Protect Against Chargebacks

Effective fraud prevention is a complex undertaking that requires sophisticated tools and techniques developed by technical experts. Enterprise-class fraud prevention solutions deliver substantial ROI through reduced fraud, increased revenue, and lower fraud mitigation costs.

Identity Trust Data Network. Fraud prevention solutions that manage extremely large data sets in real-time are better at deterring rapidly changing fraud attacks.

Advanced AI and Machine Learning. Fraud prevention platforms driven by artificial intelligence (AI) can meet the challenges of current and emerging eCommerce fraud threats. Using an AI-driven fraud prevention solution that runs supervised and unsupervised ML in parallel allows greater control to adjust the organization’s tolerance levels for fraud, chargebacks, and declines.

Third-party data orchestration. Screening technologies that are tightly integrated — interacting in real-time — are superior to workbench solutions that merely aggregate individual screening functions in a linear fashion.

Checklist for Fraud Protection Solutions

An all-in-one enterprise-grade solution that includes criminal fraud prevention, friendly fraud prevention, account takeover protection, case management, policy creation and management, and advanced data analytics can address all fraud prevention needs and dramatically reduce chargebacks.

Keep the following checklist in mind when selecting an all-in-one fraud protection.

Kount’s Solution for
Merchant Chargeback Protection

More than 9,000 companies rely on Kount’s leading merchant chargeback protection to significantly reduce chargebacks and their related costs.

Kount’s AI-driven fraud prevention solution is simple to implement, easy to use, and delivers the most accurate eCommerce fraud protection. The award-winning solution includes everything needed to evaluate transaction risk:

• An extensive network of trust and fraud related signals

• Advanced AI and machine learning

• The ability to create, edit, and test business policies

• A case management tool for manual reviews

• Reporting and analytics to evaluate everything from macro trends to a single transaction

• An orchestration hub for third party integrations

Up to


Manual Reviews
Up to


False Positives
Up to


Efficiencies Up to


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Datamart Analytics Uncovers Criminal and Friendly Fraud

An advantage of Kount’s solution is the depth of data essential for sorting criminal from friendly fraud. A component of Kount’s Friendly Fraud solution is Datamart – a feature that enables businesses to use advanced data analytics and intelligence to study more complex fraud. Datamart provides robust qualifier data such as email address, product, and data types. This helps to surface patterns not easily recognized, helping businesses to further reduce complications from fraud.

Businesses are empowered to look beyond chargebacks to pinpoint how to improve margins, revenue, and the customer experience. By untangling their business challenges, merchants can address each one to increase sales margins, and improve user experience, customer satisfaction, and retention rates.

Kount’s Identity Trust Global Network

Kount’s Identity Trust Global Network uncovers the true level of trust behind interactions where other solutions often miss fraud, or create false positives and unnecessary friction due to limited datasets and lack of real-time AI.

The largest data network of trust and fraud-related signals drives quick and accurate trust decisions, linking signals from payments data, location ID data, digital identifier data and unique customer data.

From a website visit to login, checkout, or account creation, Kount’s Identity Trust Global Network goes to work analyzing billions of identifiers to establish real-time links between identity elements in order to return identity trust decisions that provide the desired customer experience—ranging from low friction to blocking fraud.

See how Kount Prevents Chargebacks with Real-Time Fraud Prevention.

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