The Year in Chargebacks
Midigator’s The Year in Chargebacks report takes an in-depth look at payment disputes. The data provides unprecedented insight into why chargebacks happen, how to prevent and fight chargebacks more effectively, and what’s in store for the future.
At Midigator, we believe data analysis is one of the most impactful elements of a successful chargeback management strategy. Data-driven decisions produce far better results than guesses and assumptions. The Year in Chargebacks report is designed to help you recognize the value of data analysis and the role it can play in chargeback management.
Ultimately, we want to help you create intelligent, effective strategies that will lead to a significant improvement to your bottom line.
We hope this resource is valuable to you!
The data in this study was collected from a subset of merchants who used Midigator to manage chargebacks for 12 consecutive months. These merchants were chosen because they represented a broad spectrum of billing models, industries, transaction volumes, and dispute management styles.
Despite efforts to collect data from a diverse group of merchants, preference was shown to businesses that sold products or services with a recurring (subscription) billing model. These merchants were specially chosen because they provided a higher volume of data for analysis.
Half of the 2017 study participants were also chosen for the 2018 analysis. The combination of some repeat participants and some new was intentional. The goal was to maintain a consistent study size that included both year-over-trends and fresh insight.
Merchants in this study ranged from small, start-up businesses to large, enterprise brands. In 2018, individual chargeback counts ranged from 78 disputes a year to 63,229. Sales ranged from $514,000 to $82,908,500 annually.
The 2018 data was generated from 14.2 million transactions.
Midigator’s The Year in Chargebacks report is the first of its kind because it is data-driven analysis. All other industry reports that contain chargeback information are based on merchant surveys.
Data provides a more accurate explanation because it is factual, whereas surveys reflect opinions and assumptions. Therefore, The Year in Chargebacks report provides a truer representation of the industry.
What are the most important conclusions that can be drawn from The Year in Chargebacks? Here is a high-level overview of the most significant insights in the 2019 report and suggestions on how to respond.
Why does The Year in Chargebacks report show a decrease in year-over-year trends when other studies indicate chargeback risks are intensifying?
The difference is an ongoing effort to prevent disputes.
Chargebacks are an increasing threat, as the 3.36% average chargeback-to-transaction ratio indicates. If merchants didn’t make any effort at all to reduce risk, the data in The Year in Chargebacks would be much different.
However, the merchants in this study recognize the dangers that chargebacks pose to their business and have been making an effort to reduce them.
Therefore, the drop in the chargeback-to-transaction ratio emphasizes the effectiveness and importance of an ongoing, proactive chargeback prevention strategy.
Merchants are encouraged to create a comprehensive chargeback prevention strategy1 to reduce unnecessary revenue loss, costs, and penalties. This should include a combination of pre-sale (address verification service, card security codes, etc.) post-sale (prevention alerts, VMPI, etc.), and post-chargeback (analytics) initiatives.
Of the four types of chargebacks (fraud, cardholder disputes, authorization issues, and processing errors), fraud was by far the most commonly used reason for disputing transactions; 70.85% of all chargebacks were filed with a fraud-related reason code. This was a 20.4% increase from 2017.
However, reason codes don’t always tell the full story—the reality is usually much different. Of those disputes classified as fraud, 77.25% were proven to be friendly fraud.
Friendly fraud can and should be fought2. To win, a merchant needs to prove the transaction wasn’t fraudulent. The most compelling evidence against fraud is address verification service (AVS), card security codes (CVC2, CVV2, etc.), and 3D secure (Mastercard SecureCode, Verified by Visa, etc.).
Collecting this data during the checkout process empowers merchants to successfully expose friendly fraud and recover lost revenue.
Processing error disputes should be the result of merchant oversight (agreeing to one amount but processing the transaction for a different amount, charging the card more than once, processing the transaction late, etc.).
However, data shows that merchants were only at fault for one out of every four disputes. The rest were the result of consumers making false claims.
In the fraud category, at least 0.46% of chargebacks were invalid. In these situations, issuers processed the disputes after the submission deadline.
Merchants are probably accepting liability for more disputes than they need to.
Fight rules should not be rigidly based on things like reason code, as that information alone isn’t an accurate indication of whether or not the case can be won. Instead, the availability of compelling evidence should be a determining factor. If merchants can prove the chargeback is invalid, they can win.
A significant portion of chargebacks are filed within a week of the original transaction with more disputes happening on day eight than any other point on the timeline. More than half of all disputes (54.53%) were initiated within a month of the original transaction.
If merchants can anticipate when chargebacks will happen, they can act preemptively to improve customer satisfaction and work to prevent the disputes from happening. This could include follow-up emails to confirm delivery, inquiries about expectations, rewards programs, and more.
Nearly all of cardholder confusion was resolved once merchants provided more information about the transactions. These “cardholder does not recognize” disputes were fought and won.
Both Mastercard and Visa are retiring the “cardholder does not recognize” reason code. However, these chargebacks won’t disappear simply because the reason code is gone. Instead, disputes will likely shift to other classifications.
Unfortunately, when the confusion is masked with not-as-specific explanations, it will be much harder for merchants to recognize it and provide the needed clarification.
Therefore, it is advisable for merchants to provide the clarification up front. They should add as much information as possible to their billing descriptor3 (URL, phone number, etc.), include a Contact Us page on their website, offer 24/7 customer service, answer inquiries quickly, and embrace anything else that will help customers recognize the business and remember the purchase.
Percent of Transactions that Turn Into Chargebacks
Is there an accurate metric to gauge the impact of chargebacks? What is the best way to monitor trends?
The most relevant and accurate insight comes from multi-dimensional analysis. It reduces the risk of assumptions drawn on incomplete data that can often happen without context. Therefore, the most precise metric for general, industry-wide analysis is likely the chargeback-to-transaction ratio—the percent of transactions that turn into chargebacks.
The average chargeback-to-transaction ratio for the merchants in this study dropped by 13.3% between 2017 and 2018.
The most significant drop in the chargeback-to-transaction ratio typically happens within the first four months of launching a prevention strategy. The decrease then becomes more gradual over time.
Forty-one percent of participating merchants had used Midigator’s services for 6-12 months prior to the study’s inception in 2017 and continued throughout the duration of 2018. Therefore, when merchants start or update their prevention strategy, they could see an even bigger drop than the 13.3% decrease shown in this study.
The chargeback-to-transaction ratio shows that payment disputes are still a major concern for merchants—especially for card-not-present transactions. A 3.36% ratio is well above the card networks’ 1% threshold6.
However, the year-over-year decrease is encouraging. Merchants in this study were actively managing disputes and attempting to keep risk in check. Therefore, the drop in the chargeback-to-transaction ratio suggests that ongoing management strategies help prevent chargebacks and reduce risk exposure with greater effectiveness.
This chargeback-to-transaction ratio is reflective of general cardholder behaviors and commerce trends; chargebacks are an ever-present concern for merchants.
However, the high chargeback-to-transaction ratio itself might not be reflective of all industries. What is a universal application is the year-over-year trend: chargebacks can be controlled with the right tools and strategies.
Most Common Reasons for Disputes & Friendly Fraud
Why are transactions disputed? What reasons do cardholders and their banks offer?
Four different categories are used to classify chargebacks. These categories vary slightly based on the network but can generally be thought of as fraud, cardholder disputes, authorization issues, and processing errors. The cardholder’s bank reviews each case and picks the category (or reason7) that seems to be the best fit for the dispute.
Fraud-related disputes accounted for the vast majority of chargebacks in both 2017 and 2018, increasing at a rate of 24.5% for Visa and 11.52% for Mastercard. All processing errors and authorization issues combined accounted for less than 1% of chargebacks.
However, reason codes don’t always tell the full story—reality is usually much different. The cardholder’s bank assigns a reason code to each chargeback before sending it to the merchant. Often times, the reason code assignment is based on limited knowledge and insight.
In most cases, the bank chooses a course of action based on information the cardholder provides. If the cardholder is using the chargeback process incorrectly—a practice known as friendly fraud8—the information provided to the bank could be inaccurate or incomplete.
Even though 70.85% of disputes were categorized as unauthorized transactions, 77.25% of those disputes were proven9 to be friendly fraud.
The extent of friendly fraud highlights the importance of responding to chargebacks and recovering revenue that was unfairly sacrificed.
Percent of Revenue Lost to Chargebacks
The absolute “cost” of each chargeback varies and is impacted by several different expenses: lost processing fees, chargeback fines, labor costs for management, and much more. However, since the largest and most easily-defined loss is the transaction amount, monitoring the percent of revenue lost to chargebacks is likely the most accurate gauge of financial impact.
The total amount of revenue lost to chargebacks decreased by 44.7% between 2017 and 2018. This reduction is relative to the decrease in the average chargeback-to-transaction ratio.
Again, investing in proven-effective chargeback prevention strategies yields a positive ROI by reducing the amount of revenue lost to chargebacks.
Why does The Year in Chargebacks report show a decrease in year-over-year trends when other reports show chargeback risks to be intensifying? The difference is an active and ongoing effort to manage risk.
Chargebacks are an increasing threat. Things like friendly fraud and shifting industry regulations inflict more and more damage on a merchant’s bottom line each year. If merchants didn’t do anything to curb the ever-present threat, these charts would look much different. However, the merchants in this study recognize the danger that chargebacks pose to their business and take proactive action to reduce risk as much as possible.
However, there is no way to guard against all risk. Therefore, merchants are advised to have a plan in place to fight illegitimate chargebacks10 when they do happen, recover lost revenue, and protect their bottom line.
Win Rates and ROI of Fighting
Win rates, or the percent of chargebacks fought and won, fluctuated drastically on a merchant-by-merchant basis. In 2018, win rates ranged from 12.26% to 85.54%.
Several things can impact a merchant’s win rate, but the availability of relevant compelling evidence11 is often the most significant. If the merchant doesn’t have required evidence, the chargeback can’t be won.
For example, 71% of merchants in this study did not use AVS, 3D secure, and/or card security codes in 2018 because they didn’t want to create friction during the checkout process. They forfeited chargeback response rights for the sake of fewer false positives and lower cart abandonment, which was reflected in a lower-than-average win rate.
When analyzing win rates, there were two interesting discoveries to take particular note of.
First, win rates by category. The processing error category had the highest win rate (78.6%) of the four categories. Disputes in this category should be the result of merchant error: agreeing to one amount but processing the transaction for a different amount, charging the card more than once, processing the transaction late, etc.
However, the reality is that merchants are actually only at fault for one out of every four disputes. Three out of four disputes are the result of consumers making false claims or invalid disputes being processed by the issuer.
The second noteworthy insight is win rates for cases where the cardholder doesn’t recognize the transaction. Both Visa and Mastercard had “cardholder does not recognize” reason codes. Visa retired this reason code in April 201812 and Mastercard has plans to do the same in Q3 or Q4 of 201913. Since the codes were still in use for at least part of 2018, there is data available to analyze.
The win rate for “cardholder does not recognize” disputes was 96.2%. In other words, 96.2% of cardholder confusion was resolved once the merchant provided more information about the transaction. While it’s good that merchants were able to recover the majority of lost revenue, the reality is that these disputes never should have happened in the first place.
The fact that the card networks are retiring these dispute reason codes indicates they recognize the high likelihood of unnecessary (and for the merchant, unfair!) chargebacks. However, doing away with the reason codes won’t, unfortunately, do away with the chargebacks themselves. Issuers aren’t going to simply ignore cardholders when there is confusion about a purchase. They’ll likely just shift those “cardholder doesn’t recognize” disputes to a different reason code.
These two discoveries lead to one valuable conclusion: merchants should not base their fight rules exclusively on factors like reason code. Reason codes alone are not an accurate indicator of whether or not the case can be won.
For example, “cardholder doesn’t recognize” disputes might shift to fraud-related reason codes. Or, they might not. Determined friendly fraudsters could try an entirely different tactic.
As five merchant case studies show, a well-rounded chargeback management strategy based on data-driven decisions and intelligent fight rules has the best results.
|ROI for Fighting Chargebacks|
Length of Time Between the Transaction and Dispute
The chargeback lag time, or amount of time that passes between the transaction date and the chargeback date, provides valuable insight.
Each chargeback has a time limit—a deadline for when the cardholder’s bank must submit the dispute. The amount of time available14 and the specified start date vary based on the reason code used to dispute the transaction. However, most chargebacks must be filed within 75, 90, or 120 days of the original transaction.
Few disputes use the maximum amount of time allotted. Most processing errors and authorization disputes have either a 75 or 90-day limit, yet only 6.3% were initiated more than 60 days after the transaction. Most chargebacks in the fraud and cardholder dispute categories can be filed 120 days or more after the transaction, yet only 18.4% were initiated after day 60.
The fact that some fraud disputes were initiated on the same day the transaction was processed shouldn’t be surprising. Responsible cardholders who are attentive to their accounts and suffer legitimate fraud are likely to take action right away. Similarly, some cardholder disputes might be detected early on. For example, a recurring transaction that was supposed to be canceled could be caught immediately.
While these short lag times are interesting, the long lag times are even more insightful.
Some consumer disputes can be initiated more than 120 days after the transaction. Extensions are often allowed and take into consideration things like delayed delivery. Fraud disputes, on the other hand, have a hard 120-day time limit—there are no exceptions to this rule.
However, the data shows that 0.46% of fraud-related disputes happened after the deadline had passed. These chargebacks are not compliant with card network regulations, and the issuers should not have processed them. Merchants are advised to be on the lookout for these expired cases since invalid disputes can be fought and won.
Lag time spiked one week after the original transaction was processed, with more disputes happening on day eight than any other point on the timeline. More than half of all disputes (54.53%) were initiated within a month of the original transaction.
Understanding chargeback lag time can help improve prevention efforts. For example, if the majority of chargebacks happen on day eight, merchants might want to reach out to their customers to gauge satisfaction and address any issues on day seven
In addition to calculating lag time based on reason code, it is also insightful to analyze the lag time by transaction amount.
Arguments have been made in the past that buyer’s remorse is a common reason for friendly fraud. Another claim is that high-value merchandise is a popular target for fraudsters because of the resale potential. However, the available data seems to challenge those ideas, as buyers remorse and legitimate fraud would both likely have a short lag time.
It took an average of 59.3 days for cardholders to dispute purchases above $5,000. The extreme delay in initiating a dispute on high-dollar purchases indicates other motives, like a forgotten or unrecognized purchase, are more likely.
Transactions in the $200-249.99 range had the shortest average lag time (30 days) while the $40-49.99 range had the longest (62.8 days).
Peak Time of the Year for Disputing Transactions
When are transactions disputed? Which months have the highest chargeback rates?
To understand the implications of this data, it should be analyzed in the context of chargeback lag time.
Just over half (54.6%) of chargebacks are filed within 30 days of the transaction. Another 27.1% are filed 31-60 days after the transaction. And 11.6% are filed 61-90 days after the transaction. In total, 93.3% of disputes are initiated within three months of the original purchase.
This data is reflective of general commerce activity. Merchants with transaction trends that differ significantly from traditional consumer behavior should analyze their own individual chargeback data, as it will likely vary from the norm.
Therefore, it is safe to assume the significant spike that happens each year in January is the result of an influx in holiday-related purchases in the previous months—Thanksgiving, Black Friday, and Cyber Monday. New Years purchases could cause a slight increase in chargebacks in March.
The May and August spikes could similarly be related to purchases associated with spring and summer holidays—Mother’s Day, Memorial Day, and Easter. Spring and summer vacations and the activities that go with them—travel, dining out, new clothes, weight loss, outdoor sports, etc.—could also be contributing factors to the August influx.
This data can be used to help merchants better allocate chargeback management resources. For example, prevention15 should be the primary focus from October to December and March to July. Resources should be funneled into chargeback responses16 January, May, July, and August.
Countries with the Highest Chargeback Rates
When expanding into new markets, merchants should evaluate the revenue potential of each individual country versus the anticipated risk. For merchants who sell globally (in more than one country), the following cardholder locations had the highest and lowest chargeback-to-transaction ratios.
There was a fairly significant amount of turnover between 2017 and 2018 for the top 10 high-risk countries. Peru and Guatemala where the only two countries to have a high chargeback-to-transaction ratio both years. This suggests merchants quickly exit regions if the risk outweighs the reward.
These high-risk countries have limited earning potential, as evident by the low percentage of payment card adoption. In countries with available data, card ownership averaged 43%–which contrasts significantly with the 83% average adoption rate17 of the low-risk countries.
Merchants might be tempted to withstand higher chargeback risk and invest more into prevention if there is significant earning potential. However, high chargeback risk coupled with a small audience of potential shoppers isn’t appealing.
|Antigua and Barbuda||36.36%|
On the other hand, trends for the low-risk countries were relatively static between 2017 and 2018. More than half of the low-risk countries remained the same year-over-year: Denmark, New Zealand, Puerto Rico, Canada, Sweden, and Norway.
Countries with a low chargeback-to-transaction ratio also had a high payment card adoption rate, averaging 83%. This suggests that a greater awareness of payment card benefits is accompanied by a better understanding of associated risks and responsibilities.
However, trends seem to be shifting, and risk will likely start to increase in the low-risk regions.
When limiting the data to countries that processed 1,000 or more transactions in at least one of the analyzed years, new trends emerged.
While these countries still had much lower ratios than other parts of the world, a year-over-year analysis shows a higher portion of transactions are turning into chargebacks.
The United Kingdom had the highest chargeback-to-transaction ratio for both 2017 and 2018; however, the 2018 ratio was 122.43% higher than in 2017. This could be due to several different influences.
Data breaches, for example, might be a major cause. Financial services firms in the UK reported 480% more data breaches in 2018 than 201718. Additionally, the data breach at British Airways was said19 to be the world’s most devastating hack of 2018. Personal information for local consumers was stolen and probably used for unauthorized transactions, leading to greater chargeback activity.
Why does the chargeback-to-transaction ratio increase when analyzing country-specific data but decrease when examining other variables?
The data in this section was collected from global merchants (merchants who sell in more than one country). The results indicate that risk management is easier and more effective for domestic sales than international. Merchants have a better understanding of local cardholder and issuer expectations. Venturing into new markets introduces unfamiliar risks.
The overall chargeback-to-transaction ratio decreased because the majority of data (84.25%) was associated with low-risk, domestic sales.
However, the most likely contributor to the UK’s chargeback-to-transaction ratio is a growing awareness of friendly fraud. Friendly fraud first emerged in the US because eCommerce sales took off at a faster pace than any other market. However, as the popularity of online shopping grows on a global scale, friendly fraud is likewise reaching new regions.
This observation is supported by the fact that risk in all countries, except Switzerland, increased between 2017 and 2018. The greatest influxes happened in Sweden (768% increase), France (632.12% increase), and New Zealand (299.07%).
Issuing Banks with the Highest Chargeback Ratios
The first six digits of a cardholder’s account number are the bank identification number (or BIN). The BIN identifies the bank that issued the card to the cardholder. Analyzing chargebacks by BIN can help reveal differences in issuer preferences and expectations.
When limiting the 2018 data to BINs that processed 1,000 transactions or more, the financial institutions with the highest chargeback-to-transaction ratios weren’t too surprising. They were mostly large, well-known banks in the U.S. These banks serve a very diverse set of customers with widely-varying shopping habits, expectations, and ethics. Chargebacks would be common at these banks.
Most financial institutions have several, if not dozens, of BINs. BINs are used to classify different account characteristics, like debit or credit, Visa or Mastercard, business or personal, etc. BINs are also added as the bank grows and the demand for cards increases.
The 30 BINs with the highest chargeback-to-transaction ratios were associated with just 12 financial institutions. Five financial institutions were unique, but seven had more than one BIN listed.
|Financial Institutions with One High-Risk BIN||Country|
|Robins Financial Credit Union||USA|
|Shinhan Card Co||South Korea|
|Financial Institutions with Multiple High-Risk BINs||Country|
|M & T Bank||USA|
However, when analyzing the data without the transaction count filter and increasing the size of the data set, the results are very different. All of the 60 BINs with the highest chargeback-to-transaction ratio (except one–U.S. Bank) processed less than 500 transactions. And all but three of the banks were outside the U.S.
The 60 BINs with the highest chargeback-to-transaction ratios were associated with just 32 financial institutions. Seventeen financial institutions were unique, but fifteen had more than one BIN listed.
|Financial Institutions with One High-Risk BIN||Country|
|Banco Nacional De Mexico||Mexico|
|Bank Of Communications||Honduras|
|Gwinnett Community Bank||USA|
|La Banque Postale||France|
|Maui County Credit Union||USA|
|Financial Institutions with Multiple High-Risk BINs||Country|
|Bank of Scotland||UK|
|Card Services for Credit Unions||USA|
|Commonwealth Bank of Australia||Australia|
|National Building Society||UK|
|Royal Bank of Scotland||UK|
|St. George Bank||UK|
Eleven of the 31 high-risk banks in 2018 also had high chargeback-to-transaction ratios in 2017: Bank Hapoalim, Bank of Scotland, Barclays, BBVA Bancomer, Capital One, Halifax, Lloyds Bank, Nationwide Building Society, NatWest, Royal Bank of Scotland, and U.S. Bank.
What conclusions can be drawn from this information?
First, the extremely high chargeback-to-transaction ratio at several UK and Australian banks raised a red flag. Why were banks disputing well over half—and up to 99.45%—of their transactions?
Some of the merchants in this study sold merchandise with a recurring billing model. Upon closer inspection, it was discovered that the majority of subscription transactions processed with these high-risk BINs were disputed. Obviously, cultural differences came into play, and that particular billing structure wasn’t as well received in those countries as it is in other parts of the world.
Second, the one-off nature of certain BINs was surprising. If large financial institutions have dozens of different BINs, why would just one or two have a high chargeback-to-transaction ratio? For example, why did one U.S. Bank BIN rank so much higher than the others?
Some BINs are managed on a regional basis. If one BIN is significantly higher than the others, it might be because cardholders in that part of the country are more demanding and willing to engage in friendly fraud.
Financial institutions might also use BINs to segregate cardholders by demographics—for example, high-risk customers with low credit scores. Since they sustain greater financial liability for these cardholders, banks might be tempted to auto-dispute suspicious transactions as a way to proactively shorten their losses. Recent updates to card network regulations should reduce the frequency of these auto-disputes in the future.
Another contributing factor could be the type of card issued with a given BIN. For example, the chargeback-to-transaction ratio could be higher for debit cards than credit cards. Or, transactions processed with a personal card could be disputed at a higher rate than transactions processed with a business card.
Percent of Chargebacks Prevented
The most effective chargeback prevention strategies are the result of a multi-layer approach—multiple tools and actions applied at various points of the customer experience. While a multi-layer strategy is most effective, it is often difficult to determine the outcome of each individual prevention effort.
Moreover, some strategies have accurate metrics to gauge chargeback prevention but don’t factor in the risk of false positives.
However, chargeback prevention alerts20 is one tool that won’t increase customer friction or turn away good sales while also providing accurate data to monitor effectiveness.
Of those merchants who used chargeback prevention alerts in 2018, 60% resolved 30% or more of disputes before they progressed to costly and damaging chargebacks.
The merchants in this study showed an increasing interest in chargeback prevention alerts with 3.9% more merchants using alerts in 2018 than 2017.
Combined with other issuer-merchant collaboration networks and detailed analytics, prevention alerts can help finish off the much-needed post-sale layer of a chargeback management strategy.
The Impact of VCR
Visa Claims Resolution, which went into effect in April 2018, was an attempt to update and improve the legacy chargeback workflow. This edition of The Year in Chargebacks has the unique opportunity to analyze the initiative’s impact since data was obtained both before and after the rollout.
The first noteworthy element of VCR was the increase in Visa fraud disputes, which was somewhat expected. As part of Visa Claims Resolution, reason code 75 (cardholder does not recognize) was retired21. As anticipate22, those disputes were likely recategorized with a fraud-related reason code.
The Year in Chargebacks report provides an unprecedented look at the payments industry and offers a valuable benchmark to evaluate individual chargeback management efforts. This annual publication will serve as an ongoing resource for insightful analysis on emerging trends.
- For the sake of this report, friendly fraud is defined as the number of successful dispute responses versus the number of losses.