Tag: credit card transactions

Even as 75% of large and mid-sized U.S. e-commerce marketplace merchants predict continued double-digit online sales growth rates through the end of 2022,1 their success is hampered by unnecessary friction driven by concerns of card-not-present fraud and additional fraud risks in an online world. Compared to the 96% approval rate for point-of-sale purchases, card-not-present transactions yield a surprisingly low 81% approval rate. According to a survey conducted by Aite Novarica,1 the difference stems from reviewing up to 16% of attempted transactions for possible fraud. Even more surprising is that many of the respondents report that more than two-thirds of these reviews are later found to be unwarranted. Current transaction processing and risk capabilities are impeding growth and creating friction that damages e-commerce marketplace brands. What do we mean when we talk about online card-not-present transaction friction? Much of the success or failure of e-commerce depends on how easy merchants make it for consumers to complete a transaction. Effective identity resolution, fraud mitigation and risk solutions can lead to increased sales, while unrefined solutions and unnecessary friction will run merchants the risk of denying a legitimate customer purchase at checkout because they have been incorrectly labeled a fraudster–a ‘false positive’ or ‘false decline.’ These solutions leave room for improvement based on several key factors–the limited amount of data that passes through the authorization stream from the merchant to the issuer is a key contributor. According to Aite-Novarica Group’s The E-Commerce Fraud Enigma: The Quest to Maximize Revenue While Minimizing Fraud Report, “This reinforces the importance for merchants to augment the decisioning on their side with a wide variety of data sources that can help inform them regarding the risk profile of both the customer and the transaction.” Challenges with current transaction processing and verification tools Today, merchants leverage email address data, device information and other technologies to augment their address verification capabilities. The challenge is that these tools each judge the risk of a specific component of the transaction or the individual. Where integration is lacking, false positives are amplified and that is exactly what the data1 says is happening. Different tools working in isolation all catch the same fraud but flag different false positives—dragging down overall performance. The result is that 75% of e-commerce merchants place maximizing sales, minimizing friction and reducing false declines at the top of their to-do list. 88% say they are ready for a change to achieve these goals.1 Fast Facts 16% of all attempted online transactions experience friction for suspected fraud. 70% of this number is unnecessary, and upon manual review, are ultimately approved.1 78% of e-commerce merchants report friction driven by suspected fraud is increasing. 78% of merchants report increasing declines due to suspected fraud over the last two years. 46% indicate an increase of more than 5%.1 81% of consumers say that a positive online experience makes them think more highly of a brand.2 The longer it takes for banks and issuers to process new account, the higher the rate of abandonment, which reaches 40% when the process takes longer than 10 minutes.3 The friction that consumers encounter throughout their buying journey and the expenses associated with merchant and issuer manual reviews can be costly. It is estimated that 70% of unwarranted friction is costing businesses ~$11B in false decline losses and sales annually.1 That number is expected to increase. And, beyond profit losses incurred from the order that was declined, merchants risk damaging brand reputation because of poor customer/buying experiences, and in some cases, the loss of the customer relationship as well. Reducing friction and providing a positive shopping experience is increasingly important to business success Businesses looking to address this and limit false declines should not allow this to come at the expense completing transactions for legitimate customers. Experian can help. By leveraging our multidimensional data, technical expertise and advanced analytics capabilities, we can help businesses authenticate valid customers without unnecessary friction, thus increasing revenue by increased approval rates, without increasing fraud or operating expenses. Get started with Experian Link™ - our frictionless credit card owner verification solution. Learn more. Experian Link   1"E-Commerece Fraud Enigma: The Quest to Maximize Revenue While Minimizing Fraud Report" Aite-Novarica Group, July 2022 2"Global Insights Report: The Evolving Expectations and Experience of the New Digital Customer" Experian, April 2022 3"Capturing the Digital Identity Evolution Through a Layered Approach" Liminal, June 2021

The credit card marketplace is a crowded and complex landscape. Recent research by Experian shows the average U.S. consumer has 3.1 credit cards and 2.5 retail cards, with an average balance of $6,354 and $1,841, respectively. So how can you build upon your existing customer relationships and offer the right products to the right people at the right time? By understanding consumer behavior. Pretty simple concept. But targeting viable consumers and making enticing offers takes some detective work. Gone are the days of demographic-based approach to audience segmentation for credit marketing campaigns. Consumers are now engaged on their smartphones, laptops, tablets, fitness bands, across countless apps, browsers, emails and more. Simply knowing a person’s gender and age doesn’t provide any information about how he spends the day, his consumer behaviors, personal interests, unique wants or needs. Developing rich consumer personas based on transaction credit data can be a powerful tool to understanding consumers so lenders can design more relevant and personalized credit offers, experiences and products to a very targeted audience. Experian DataLabs can help by analyzing transaction data to understand the consumers in your portfolio. For example, looking at your portfolio of 40-year-olds in the U.S. provides basic demographic information. A closer look at transaction data could reveal unique details within the age group to help you group and target, such as: Frequent travelers: These road warriors log serious miles. If they’re not traveling for work, they’re cashing in miles for vacation. This unique group leads your portfolio in airfare, cruise line, car rental, hotel and travel agency spend. With so much time spent away from home, this group is rarely found in grocery stores. Local business owners: Advertising, computer equipment, and software are typical expenses of this segmented group. There may be an opportunity to capture spend outside their business activity or to ensure they have the right card to fit their business needs. Constant commuters: These consumers use their card for local travel and transportation. And they are less likely to use their card for expenses related to other types of travel or maintaining a vehicle. After a long day, they like to grab a drink while waiting for the train. Online Shoppers: Consumers in this group use their card with various online merchants, including Amazon, Etsy, iTunes, and PayPal. Online shoppers are also above average spenders in elementary education, child care services, and family clothing. Social hipsters: They can be found meeting with friends for coffee and drinks, and are more likely to rely on local transportation and tend to eat out instead of cooking in. Effective audience segmentation ensures that your marketing dollars are invested in real people who are most likely to respond on certain media, have already expressed an interest in your product, and are geographically accessible to a specific retail location. Every campaign should be as dynamic and unique as its consumers. The powerful combination of consumer and transaction data allows you to customize audience segments to maximize customer engagement and drive campaign success.

If someone asked you for stats on your retail card portfolio, would you respond with the number of accounts? Average spend per month? Or maybe you know the average revolving balance and profitability. Notice something about that list? Too many lenders think of their portfolio and customers as numbers when in reality these are individuals expressing themselves through their transactions. In an age where consumers increasingly expect customized experiences, marketing to account #5496115149251 is likely to fall on deaf ears. Credit card transaction data including bankcard, retail, and debit cards holds a wealth of information about your consumers' tastes and preferences. Think about all the purchases you made using a credit card this past month. Did you shop at high-end retail stores or discount stores? Expensive restaurants or fast food? Did you buy new clothes for your kids? Maybe you went to the movies, or met friends at a bar. How you use your card paints a picture of who you are. The trick is turning all those numbers into insights. You may have been swept up in all the excitement around Apple’s announcement of the iPhone X in August. However, you may have overlooked the incorporation of Neural Embedding, or machine learning, as one of the most powerful features of the new phone. Experian DataLabs has developed an innovative approach to analyzing transaction data using similar techniques. Unstructured machine learning is applied and patterns begin to emerge around customer spending. The patterns are highly intuitive and give personality to what was previously an indecipherable stream of data. For example, one group may be more likely to spend on children’s clothing, child care services, and theme parks while another spends on expensive restaurants, airlines, and golf courses. If these two consumers happened to spend approximately the same each month on your card, you’d probably treat them as category. But understanding one is a young family and their other is jet setter allows you to tailor messaging, offers, and terms to their needs and use of your products. Further, you can ensure they have the best product based on their lifestyle to minimize silent attrition as their needs evolve. But it’s not just about marketing. When your latest attrition dashboard is updated, what period are you measuring? Do you analyze account closures from the previous month? Maybe a few months back? Understanding churn is important, but it’s inherently reactive and backward looking. You wouldn’t drive a car looking in the rearview mirror, would you? Experian enables clients to actively monitor the portfolio for attrition risk by analyzing usage patterns and predicting future spend. Transactions are then monitored up to daily and, when spend doesn’t occur as expected, an alert is sent so you can proactively attempt to save the account before it closes. These algorithms are finely tuned to reduce false positives that can come from seasonality or predictable gaps in spend such as only using a card at certain times during the week. Most importantly, it gives you an opportunity to manage each account and address changing customer needs instead of waiting for customers to call to cancel. So how well do you know your customers? If you’re still looking at them as numbers, it may be time to explore new capabilities that allow you to act small, no matter how large your portfolio. Transaction Data Insights brings cutting-edge machine learning capabilities to lenders of all sizes. By digging into behavioral segments and having tools to monitor and send alerts when a consumer is showing signs of attrition risk, card portfolios can suddenly treat customers like people, providing the customized experience they increasingly expect.