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Do you remember a time when you were amped up to buy that new pair of shoes, or any special item online – only to have your credit card or other payment information (which you know is real), declined? All of that time spent browsing, selecting, getting off of your couch to find your credit card, entering payment information wasted?
You are not alone!
According to the U.S. Department of Commerce, e-commerce sales growth has nearly doubled since 2019, with no signs of slowing down. There are many reasons for this, the most obvious being the fact that most retail locations were forced to shut down during COVID. Older generations who may have been hesitant to shop online, suddenly were left with no other option once the full wave of lockdowns hit worldwide. Lockdown conditions triggered major growth for merchants, driving new revenue and lifetime customer value.
This is not, however, all good news for e-commerce operators.
With an increase in online payments volume, comes an increase in payment fraud. Many merchants have hurried to solve this problem, only to discover an even bigger challenge, namely the increase in falsely declined transactions which leave many shoppers frustrated enough to abandon their shopping journey altogether.
What are false declines, and why do they occur?
False declines, otherwise known as false positives, are valid credit card purchases that are incorrectly declined at the time of sale by the credit card issuer. To an online shopper, who might be trying to complete their purchase before the end of their bus commute, it can appear as though the merchant or website is at fault. For the in-person retail shopper who might be in a rush to get their child to soccer practice, it can be easy to blame the point of sale device (self-check out, terminal) or even the store clerk.
Disappointed shoppers, disappointed merchants
To the consumer, false declines can be simultaneously insulting and an extreme nuisance. In fact, more than 80% of cardholders who experienced a false decline said it wasn’t just inconvenient – it was outright embarrassing, especially when it occurred in-store, surrounded by friends, family or strangers. According to another study by Sapio Research, 33% of falsely-declined new shoppers abandon the transaction and retailer entirely and never try again.
Accenture reports that Gen Z and Millennials, more than older generations, expect a frictionless shopping experience and instant gratification. As the estimated combined spending power of Gen Z and Millennials is nearly $3 trillion, it is in merchants’ best interest to provide the most seamless and personalized shopping experience possible.
For merchants, false declines come with a compounding effect. Credit card false declines not only result in lost revenue, they also result in lost customer loyalty and brand reputation, especially for first time buyers. Each falsely declined purchase represents a sale that may never be made, and a potential customer dispute – which is a whole other challenge for merchants’ operations and customer service teams.
How do false declines impact revenue?
According to the Global Fraud Survey published by the Merchant Risk Council, the average merchant declines 2.6% of all orders due to suspected fraud. The higher the price, the more likely a transaction is to be declined. If one does the math, these numbers translate to plenty of lost revenue for merchants.
In 2019, Aite Group concluded that merchants lose up to 75 times more revenue to false declines than they do to legitimate fraud. Considering that this study was published before the pandemic, it is fair to assume that the amount of lost revenue is even higher today. In fact, Aite Group has estimated as much as $430 billion will be lost globally to false declines for merchants in 2021, up from the estimated $331 billion recorded in 2018.
How can INETCO help?
The first step to reducing false declines of transactions is learning how to leverage your valuable payment network data. The ability to maximize the value of each digital payment is tied to your data foundation. Your performance monitoring, fraud detection and analysis capabilities will only be as good and fast as the payment transaction data you have access to. “It’s about having the right access to the right data at the right time. Utilizing stagnant data, in a time where real-time and digital payments are gaining rapid momentum, is no longer sufficient, and can significantly reduce your systems’ accuracy.” – Ugan Naidoo, CTO of INETCO.
This is why there has never been a better time for payment fraud teams to layer multi-channel fraud detection and prevention strategies with INETCO Insight. With INETCO Insight, you can attain the highest security standards, and avoid detection lag times. Here are some examples of what you can do by leveraging your data to its potential:
- Monitor every link along every card-present and card-not-present transaction – from both a performance and fraud perspective – in real-time.
- Decrease the operating costs and resource hours associated with harnessing payments data across disparate data stores, multiple schemas, and different channels.
- Increase fraud coverage to all self-service and digital channels, and reduce the number of legitimate customers accidentally blocked from accounts as a result of cyber attacks.
- Identify transaction anomalies and compromised network components that would fly under the radar of individual security monitoring systems.
- Detect, investigate and block multi-vector fraud attacks, advanced persistent cyber threats, account takeovers and suspicious transactions as they are unfolding – before the reputational and financial damage is done.
One of the biggest problems for retailers and bankers is obtaining and managing the data required for an effective fraud program from multiple data sources, systems, and solutions. Data from multiple systems along the payment channel comes in multiple formats that are merged and transformed before being used by fraud detection systems. The result is a loss of fidelity and timeliness: data provided by multiple systems may be out of date, incomplete, misleading or incomprehensible. What customers need is access to all their data in real-time, in a centralized platform, in an actionable format.
INETCO Insight solves this by providing a single solution that can capture, decode, aggregate, and analyze every field of every payment network transaction in milliseconds. Better data means better analysis of potential fraud and reduced false positives, as well as the ability to detect network performance issues that can result in false declines.
Ensure High Visibility
As with any decision, the ability to view the whole picture is crucial when it comes to making the best assessment. Detecting and preventing payment fraud in real-time requires an in-depth assessment at every step along the customer payment journey. This end-to-end journey typically starts with a login, a card tap, a wallet swipe or a card insertion.
The ability to continuously see across every initiated transaction – from the customer endpoint, to the host or third party service authorization, and back for completion – is what Gartner recommends as part of the CARTA (Continuous Adaptive Risk and Trust Assessment) approach. This is a methodology that promotes the elimination of siloes by orchestrating fraud management decisions from a single platform – which in turn, can reduce the number of falsely declined transactions.
INETCO Insight removes the data acquisition and security monitoring challenges that impact the speed of fraud detection and the accuracy of transaction scoring and blocking – across all payment channels within your business. With message-level visibility into every transaction link and all transition points along an end-to-end payment journey, it becomes easier for CISOs, cybersecurity and payment fraud detection and prevention teams to maintain the highest security standards, protect expanding attack surfaces, and add an enhanced layer of network-level defense and pattern recognition to their payment fraud and security strategies.
Adaptive Machine Learning and Risk Scoring
Machine learning models are arguably one of the most powerful tools which can be used to analyze and determine the legitimacy of financial transactions. However, legacy payment fraud tools and most fraud investigation software often use limited data points on new customers and cannot accurately distinguish between legitimate consumers and fraudsters. Without further investigation, it can be extremely difficult to understand the full story on specific transactions.
With INETCO Insight, individual customer activity is continuously assessed and compared against adaptive machine learning models and behavioral analysis of every card and customer. The platform is built to ingest transaction data in real-time, rebuild individual customer models on the fly, and assign risk advice for every transaction in milliseconds. The result is a more precise fraud risk score – with corresponding lower false decline rates – for all types of card-present, card-not-present transactions, ACH and open banking transactions, including:
- ATM withdrawals
- Cross-channel transactions
- Mobile wallets and e-payments
- Online purchases
- In-store card payments, including contactless
So you can go ahead and buy those shoes!