Trends Like Open Banking And BNPL Will Sustain E-Commerce’s Hot Streak, a Report Says

John Stewart
January 17, 2022
https://www.digitaltransactions.net/trends-like-open-banking-and-bnpl-will-sustain-e-commerces-hot-streak-a-report-says/

Open banking, single-click checkout wallets, and the hot buy now, pay later trend will all help drive e-commerce volume worldwide in the coming five years, predicts Juniper Research in a report released Monday. This momentum is likely to push online sales long after the short-term impetus from the pandemic subsides, Juniper says.

E-commerce volume totaled $4.9 trillion globally in 2021, a figure the United Kingdom-based research firm forecasts will reach $7.5 trillion in 2026, when China will control a 37% share. Wider availability of multiple e-commerce channels, including mobile devices, will propel the overall growth worldwide, Juniper says. But along with the boom in e-commerce will come a corresponding growth in fraud via identity theft, account takeovers, and fraudulent chargebacks, the report warns. China, for example, will account for more than 40% of fraud losses worldwide in 2025, at more than $12 billion, Juniper forecasts.

Open banking is a trend by which fintechs can verify balances in consumers’ accounts and transfer funds to pay for online purchases. As standards bodies work to promulgate standards for this business, e-commerce payment providers “should … partner with specialists in … specific emerging payment areas to keep pace with changing merchant expectations around acceptance types,” the research firm says in its release, referring to digital wallets and crypto as well as open banking.


Open banking has taken on a higher profile in the global payments market with efforts by both of the global card networks to acquire firms that specialize in this area. Visa Inc. has acquired Tink AB, while Mastercard Inc. bought Aiia and Finicity Corp.

Physical goods will continue to dominate e-commerce spending, the report says, accounting for 82% of payment value by 2026. To tap into the trend, Juniper advises, payments providers should support buy now, pay later plans, which allow consumers to split purchases into four equal installments paid over a six-week period at no interest. BNPL is becoming more controversial, however, as the Consumer Financial Protection Bureau has launched an investigation of the option and as reports emerge that consumers with multiple accounts are more likely to miss a payment.

While still a big trend, e-commerce sales in the U.S. market cooled significantly last year as the pandemic effect lost some of its force. Third-quarter sales in 2021 reached $214.6 billion, up 6.6% year-over-year, according to the Census Bureau, which tracks retail sales. That follows an 8.9% rise in the second quarter and three straight quarters with increases of 32% or more. Fourth-quarter 2021 results are not yet available.

Posted in Credit card Processing, Credit Card Reader Terminal, Credit Card Security, Digital Wallet Privacy, e-commerce & m-commerce, Financial Services, Mail Order Telephone Order, Merchant Account Services News Articles, Merchant Services Account, Mobile Payments, Mobile Point of Sale, Point of Sale, Small Business Improvement, Smartphone, Uncategorized, Visa MasterCard American Express Tagged with: banking and e-commerce, e-commerce, e-commerce businesses, e-commerce merchants, e-commerce processor, e-commerce transactions, ecommerce, ecommerce merchant, ecommerce merchants, ecommerce sites, mobile commerce payment, mobile payment, Mobile Payments, mobile processing transactions, mobile transactions, mobile wallet, mobile wallet transactions, mobile wallets, mobile-commerce payments, online transactions, point-of-sale transactions, transaction processing, transactions, wallet

What Will the Future Hold for Chargebacks in Digital Payments?

The chargeback process was introduced more than four decades ago as a consumer-protection mechanism. It was meant to inspire consumer confidence in payment cards, which were still a novel concept at the time. Fast-forward to today, though, and these forced payment reversals have evolved into a significant problem for online merchants.

Chargeback abuse—commonly known as friendly fraud—is a major source of loss. In fact, chargeback issuances resulting from friendly fraud were expected to reach $50 billion annually in 2020, according to Mercator Advisory Group.

Even then, this figure is a low estimate. It doesn’t account for current trends in a post-Covid environment, where we’ve seen a dramatic increase in friendly fraud. These attacks were already up by the end of March, and there’s no sign that they’re going to slow down.

Covid-19 might look like the source of the problem on a superficial level. If we dig deeper, though, we see four underlying factors behind the preexisting upward trend in chargeback filings:

• More fraudsters view the CNP environment as the “channel of least resistance;”
• Inconsistency in technologies and regulations across different markets;
• The rise of mobile banking;
• The response by card networks like Visa and Mastercard.

These four factors carry diverse ramifications for the market. For instance, roughly $118 billion in e-commerce transactions are declined each year, according to Javelin Strategy & Research. Most of these rejected purchases are false positives, meaning the merchant unnecessarily rejected the purchase in hopes of avoiding a chargeback.

Clearly, there’s a growing disconnect between merchants, financial institutions, and card networks regarding how best to address this situation. We can see this reflected in the fact that the rate of chargeback issuances in North America is expected to significantly outpace those in the European market. This is attributed to factors like strong customer authentication protocols required by the Revised Payment Services Directive (PSD2), and more widespread use of 3-D Secure technology.

The pressure is on for industry players to find more comprehensive solutions for chargebacks. These solutions must be data-driven and adaptable, though. Otherwise, the growing disconnect between cardholders, merchants, financial institutions, and card networks will exacerbate existing problems in the market, leading to further losses.

The good news is that, in the meantime, there are strategies merchants can employ to address these concerns. For instance, even though friendly fraud operates by concealing itself behind false chargeback reason codes, it’s still helpful to have a clear understanding of what each reason code means in context.

Merchants can’t avoid friendly fraud in the same way they can detect criminal attacks or eliminate merchant errors. However, they can minimize friendly fraud risk by adopting key best practices, including:

• Notifying customers to remind them about recurring payments;
• Keeping organized and well-documented transaction records;
• Using delivery confirmation when shipping physical goods;
• Providing easy access to round-the-clock, live customer service;
• Providing a quick response to any refund or cancellation requests.

Also, if a merchant identifies a chargeback as friendly fraud, it’s important to engage that dispute through the representment process. This is a complex, time-consuming process, which is why many merchants opt to outsource their chargeback management. It’s still possible to conduct the process with in-house management. However, it will require strong evidence to support the merchant’s case, such as:

• A legible sales receipt
• A tracking number
• Any emails or transcripts of communications you’ve had with the customer
• Delivery confirmation information
• A record of in-store pickup
• Photographic evidence (when available)

This evidence needs to be contextualized with a chargeback rebuttal letter, explaining why the original transaction was valid. Also, merchants are on a tight schedule. In most cases, they have only a few days to provide a response to their acquirer.

Chargeback management can be a difficult and confusing process. But, with the problem of chargeback abuse only set to grow over time, it’s something merchants can’t afford to take for granted.

—Monica Eaton Cardone is the chief operating office and cofounder of Chargebacks911, Clearwater, Fla.

COMMENTARY: What Will the Future Hold for Chargebacks in Digital Payments?

Monica Eaton-Cardone September 11, 2020 Competitive Strategies, E-Commerce, Fraud & Security, Issuing/Originating, Mobile Commerce, Point-of-sale, Transaction Processing

Posted in Best Practices for Merchants, Credit card Processing, Credit Card Security, e-commerce & m-commerce, Electronic Payments, Internet Payment Gateway, Uncategorized, Visa MasterCard American Express Tagged with: chargeback, chargebacks, ecommerce, ecommerce merchant, ecommerce merchants, ecommerce sites, electronic payment, electronic transactions, fraud protection, mobile payment security, strategies, transaction security

4 Ways That Ecommerce Merchants Misuse Data

The use of customer data can help you make smarter decisions that can improve your store, enhance the shopper experience, and increase conversions. When used incorrectly, however, data can waste resources and alienate your visitors.

Ways that ecommerce merchants commonly misuse data.

Collecting Unnecessary Data

Big Data analytics and reporting tools can put a lot of information in your hands, but that doesn’t mean you should collect and track every single metric. Don’t waste space and bandwidth collecting information that is not essential in your business. Unnecessary data can create noise that slows down the analytics process. Gathering and analyzing information you don’t need can distract you from the metrics that matter. Collecting too much data can create security headaches. The best defense against breaches is to not have data to steal. If you don’t need it, don’t collect it.

Determine your store’s key performance indicators before collecting any information. A good way of doing this is to examine each metric and ask yourself whether it’s just  nice to know or is something that you can actually act on. While it may be nice to know that a particular customer has a high Klout Score, that metric probably won’t do anything for your bottom line. It’s better to not bother with it. Key metrics vary from one business to the next. For most ecommerce sites, the important metrics usually include conversion rate, traffic sources, and on-site browsing activities.

Creeping-out Shoppers

Most retailers do this inadvertently when they’re trying to customize the shopper experience. A certain amount of personalization can provide value and convenience to users, but you also have to draw the line between cool personalization and creepy. Sending emails with tailored product recommendations is a good way to increase conversions. But you have to be careful with how you execute it, so that you don’t appear too intrusive. The same goes for remarketing banner ads.

Ignoring Qualitative Information

Numbers can produce many insights, but focusing solely on that data can create an incomplete view of your company. Best data strategies make use of both quantitative and qualitative information. Go beyond the numbers to get the pulse of your customers by collecting feedback through social interactions, customer service logs, surveys with open-ended questions and more. Qualitative information can complement and validate the hard numbers.

Using Data to Justify a Decision or Hypothesis

When it comes to data collection, many merchants fall into the confirmation bias trap, wherein they interpret the information to confirm their existing beliefs or to justify their decisions. Using data this way causes you to ignore information or results that aren’t in line with your beliefs and could result in you missing opportunities. Say a company has so much faith in its new marketing strategy that when website traffic improves, the staff deems the campaign a success without looking at the conversion or retention rates. If the staff had ignored initial biases and looked at the big picture instead, they could have identified flaws and found ways to correct them. The key to addressing this is to have an open mind when interpreting information. This can be difficult, especially when you’re too close to your business. Consider a third-party specialist who can remain objective, to help make the right decisions.

 

Posted in Best Practices for Merchants, e-commerce & m-commerce Tagged with: breaches, business, conversion rate, customer, customer data, customer service, data, ecommerce, ecommerce merchants, Merchant's, rate, retention rates, Security, sources, tools, traffic

Credit Card Processing Fees

There are no enforced standards in the card processing industry regarding rates, fees, and contractual terms. It is possible for two providers to offer seemingly the same rates and fees that result in different processing costs.

Excessive Monthly, Annual, or Quarterly Fees

There are numerous monthly, annual, or quarterly fees merchants may see on their statements each month. Many merchants pay far more than they should for these fees. The fees may have names like statement fee, service fee, membership fee, regulatory fee, PCI fee, and host of other names. The fair amount each merchant should pay for these fees varies by sales volume and merchant type. Also, the amount a merchant pays for any given fee isn’t as important as the overall processing cost. These are general guidelines; some merchants should pay far less. If you are currently paying more, it may be a good time to review your overall processing cost including your pricing plan, rates, and fees.

Excessive Payment Gateway Fees

A payment gateway route transactions from the merchant’s website to the provider. Some retail point-of-sales devices require a gateway to route the transactions. Merchants generally pay a per-month and a per-transaction fee for use of the gateway. As a rule, the direct cost to process through the gateway is a few cents per transaction.

PCI Non-compliance or Non-validation Fee

Many providers now charge a monthly non-compliance or non-validation fee if the merchant is not PCI compliant. This fee may be in addition to a monthly, quarterly, or annual PCI fee. Supposedly, providers charge the non-compliant or non-validation fee as an incentive for merchants to become compliant. Nonetheless, some providers use this fee more for revenue generation, than as an incentive. Some providers do not charge this fee at all.

Merchants should not change providers because of this fee. Instead, the merchants should become PCI compliant to eliminate the fee and reduce the probability of being breached, which could easily result in huge monetary penalties – tens of thousands of dollars. To become compliant, merchants should complete the PCI Self-Assessment Questionnaire and adhere to the PCI requirements, which may require quarterly scans. In short, if a merchant is being charged a non-compliance or non-validation fee, it is as much the merchant’s fault as anyone else.

Visa FANF Fee

In 2012, Visa started charging providers a Fixed Acquirer Network Fee (FANF). The actual fee charged by Visa is dependent on the merchant type. The fee for customer-present retail merchants is based on the number of locations. The cost for ecommerce and fast food merchants is based on the volume of business. Customer-present retail merchants that have non-swiped transactions can also pay an additional customer-not-present FANF fee.

Most aggregators – i.e., merchant account providers that group multiple merchants into a single merchant account, such as Square, PayPal – integrate the FANF cost into their rates and fees versus itemizing them out separately. Most traditional providers properly pass through the actual Visa FANF fee to their merchants. However, there are a few that treat this fee as another hidden revenue stream. I’ve seen providers charge a flat monthly fee for customer-present merchants and I’ve seen the FANF fee inflated by as much as 50 percent for ecommerce merchants. Keep in mind when reviewing that the fee is generally based on the volume of the prior month. In order words, the fee you see on your statement for April activity is likely based on the March volume, as providers need to know the monthly Visa volume before they can assess the fee.

Unusual Discover Card Fees

For Discover transactions, some providers charge a higher percentage, or higher per-item fee, or monthly access fee.

 

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Impact on 2013 Holiday Sales’s Big Data

Impact on 2013 Holiday Sales’s Big Data

 Holiday season has ended and the analysis has begun to understand what worked and what did not for ecommerce merchants. Cyber Monday became the biggest online shopping day in history with a 20.6 percent increase in sales over 2012, according to the IBM 2013 Holiday Benchmark Report. Retailers are increasingly tapping into the avalanche of data from their own sites and from third-party sites to drive sales and better serve their customers. This article will address five key ways Big Data impacted the 2013 holiday shopping season.

 Contextual Promotions

The use of Big Data has enabled contextual promotions – mostly real-time push notifications based on consumers’ social media activity, tracking their locations, or capturing their interactions on the web and mobile devices. This holiday season contextual promotions were heavily used. IBM’s Cyber Monday Report states, “On average, retailers sent 77 percent more push notifications during the five day holiday shopping period when compared to daily averages over the past two months.” Retailers invested in social media sites like Facebook, Pinterest, and Instagram (among others) during the November and December holiday season. This led to higher referral sales from these sources.

Several physical retailers, including Best Buy and Kohl’s, also deployed location-based promotions to push notifications while the consumer is in or near the store. Some retailers tracked consumers’ locations without their knowledge, raising privacy concerns. Other retailers required an opt in by consumers to receive these promotions.

Additionally, some retailers used mobile apps to send contextual promotions based on tracking shoppers’ activities on the app and their physical locations with using it. Macy’s and J.C. Penney, for example, partnered with Shopkick (a shopping app provider) during this holiday season to reward brick-and-mortar shoppers with discounts or song downloads for trying on clothes, scanning barcodes, or making purchases.

Gift Selection

Holidays are all about gift giving. Some retailers used their Big Data recommendation algorithms to make it simpler to select gifts. These retailers built predictive models that process data from multiple sources like social media, wish lists, gift registries, and past purchases to predict the right gift for an individual.

Improved Customer Service

The holiday season results in more traffic for ecommerce merchants, which naturally leads to an increase in the volume of customer service issues. To keep customers happy during this time and manage customer service costs, some retailers implemented Big Data solutions to monitor customer activity and proactively respond to negative social media posts or issues. After all, one negative tweet can significantly impact business during this time of the year.

Real-time data feeds inform retailers in advance if customers will experience issues like a slow site, out of stock products, or delayed delivery. Retailers can either proactively correct the issue or notify the customers afterwards. Fab.com, for example, automatically credits a customer the difference if a price of an item drops immediately after purchase. T-Mobile USA has integrated Big Data across multiple IT systems to combine customer transaction and interactions data to better predict customer defections. By monitoring social media interactions with transaction data and billing systems, T-Mobile USA has reportedly reduced customer defections in half in a single quarter. Dell uses Big Data solutions to analyze real-time feeds from weather reports, delivery trucks, and orders to proactively resolve delivery problems before customers are aware of them.

Integrated Analytics

Most large retailers serve customers across multiple channels and devices. This makes it critical for those retailers to have a single view of all customer and product activity using data from all sources. Some retailers are already using such solutions and several more deployed such solutions before the holiday season. This one capability is crucial to track other Big Data uses, such as contextual promotions, gift selection, personalized customer experience, and improved customer service.

 

Personalized Customer Experience

Retailers have used Big Data to personalize their site content for several years. This was a competitive differentiator during this holiday season, however, as indicated by pre-holiday survey by Baynote, a personalized customer experience solution provider. The survey noted that eighty-one percent of retailers planned to upgrade ecommerce platforms to focus on customer experience, and to increase engagement, revenue, and ultimately lifetime value from improved relationships with shoppers. Retailers can categorize each shopper into a segment of one with its own customized landing pages, product catalog, campaigns, and even content. The result is an enhanced customer experience and an improved conversion rate.

Amazon.com continued to maintain its dominance in this space by using its extremely rich data set to personalize the shopping experience for its millions of shoppers. Another benefit from personalizing the customer experience is increased impulse buys, which become more important during the holidays as shoppers are in the right frame of mind to spend money.

Posted in e-commerce & m-commerce, Electronic Payments, Internet Payment Gateway, Merchant Account Services News Articles, Small Business Improvement Tagged with: analysis, analyze real-time feeds, barcode, benchmark, big data, brick and mortar, credits a customer the difference, customer service issues, customer transaction and interactions data, ecommerce merchants, large retailers, location based promotions, making purchases, online shopping, physical retailers, real-time data feeds, retailers, rich data set, shopping season, social media activity, transaction data and billing systems