{"url":"https://www.clear.sale/blog/5-ways-to-reduce-online-credit-card-false-decline-rates","title":"5 Ways to Reduce Online Credit Card False Decline Rates","tldr":"Roughly 40% of shoppers have had a valid order falsely declined. Learn 5 ways to reduce credit card false decline rates without weakening fraud protection.","markdown":"TL;DR\n\nFalse declines happen when a legitimate order is blocked or questioned as if it were fraud, and they cost merchants far more than actual fraud does. Online stores can lower their false decline rate without weakening protection by manually reviewing high-risk orders, understanding why declines happen, avoiding rejections based on assumptions, verifying purchases with customers, and combining skilled analysts with machine learning. This multilayered approach pairs human judgment with automated screening to approve more good orders.\n\nFor most of us, when we want to buy a product, we want to buy it NOW. But what happens when you can’t, because your order gets declined?\n\n## It’s unsettling and aggravating. And for a merchant, it’s very bad news.\n\nThe news gets worse: false declines happen more often that most people think. In fact, about [40% of Americans](http://www.creditcards.com/credit-card-news/fraud-alert-blocked-poll.php) have had a purchase transaction falsely blocked or questioned, even though the order was legitimate, the card number was valid, and the transaction should have been processed.\n\n## Why are so many legitimate transactions being flagged or declined?\n\nRecent security breaches and increased sophistication among fraudsters have made credit card companies more assertive in their fraud prevention efforts. As a result, they’re expanding their fraud criteria, hoping to capture more deceitful transactions.\n\nAs consumers and retailers alike increasingly suffer the negative effects of false declines (also known as false positives – as in, falsely delivering a positive fraud score or fraud verdict), the dollar value of lost purchases is also skyrocketing. The impact these false declines can have for e-commerce merchants is concerning.\n\n## The Hidden Cost of False Declines\n\nWhat causes a false decline, anyway? It can be tough to decipher. Credit card companies and payment gateways don’t openly publish their sophisticated algorithms for flagging transactions, so they can prevent fraudsters from circumnavigating the process.\n\nBut we know this: Most fraud protection systems use a complex formula (weighing up to [500 distinct elements](http://www.creditcards.com/credit-card-news/fraud-alert-blocked-poll.php)) to comprehensively assess the risk that a transaction might be fraudulent.\n\nWith this level of complexity, there’s greater room for error.\n\nRecent statistics report that:\n\n- So far in 2016, false declines make up 58 percent of declined transactions.\n\n- False declines could cost retailers up to $8.6 billion by the end of the year.\n\n- Retailers lose more money on false declines ($118 billion) per year than the amount lost to actual credit card fraud ($9 billion).\n\n- 32 percent of customers experiencing a false decline choose not to shop with that merchant again.\n\nClearly, false declines present a massive challenge for merchants, payment processors and banks. How can a business prevent fraudulent transactions without alienating the customers who are caught in the middle?\n\nWe’ve got some suggestions for you.\n\n## 5 Ways to Reduce Credit Card False Decline Rates\n\nHere are five ways to lower your false decline rate while still maintaining appropriate levels of protection for your business.\n\n- Manually review questionable and high-risk orders. A manual review will allow you to identify truly fraudulent orders, giving you insights into how to distinguish fraudulent from legitimate purchase behavior.\n\nThe problem is that nearly [30 percent of all online orders](http://www.experian.com/blogs/insights/2016/05/reduce-false-declines/) will be subject to review. As a result, this option can be time-consuming and a potentially significant operational expense, making it less practical for merchants with high order volumes. If you don’t have the in-house expertise to manage these reviews, it might not even be an option for your business.\n\n- Understand why declines occur. What indicates high-risk transactions? Many systems will automatically decline certain purchases — e.g., first-time visitors making an exceptionally large purchase, purchases outside a customer’s normal pattern, purchases that originate in certain countries, etc. Make sure you’ve appropriately optimized your system settings so you can increase the success rate of future transactions.\n\n- Don’t reject transactions based on assumptions. Rejecting orders based on generalizations (e.g., assuming that all purchases made in a country different than that of the issuing country must be fraudulent) can be a problem. If you’re not making decisions based on detailed data, you could be losing opportunities to make a sale. And the more legitimate sales you accept, the more information you have to continue to fine-tune your processes.\n\n[Understanding the context](//blog.clear.sale/post/3-Reasons-to-Reduce-Your-False-Decline-Rate) in which a purchase was made will always benefit your bottom line, your decline rate and your customer relationships.\n\n- Contact customers to verify a purchase’s authenticity. Before flagging a transaction, contact customers immediately to verify transaction details. Customers will appreciate that you’re looking out for them and providing a secure online ordering process, and you’ll be able to validate more purchases and experience fewer lost sales.\n\n- Employ a multilayered fraud protection A combination of highly skilled analysts and deep-learning algorithms scanning each and every transaction offers a comprehensive strategy to identify and prevent false declines. Although automated tools on their own can be effective, this combined approach adds in information gained directly from communicating with clients in order to enhance the machine-learning database, for superior results.\n\n## Screen Transactions and Verify Purchases to Decrease False Declines\n\nAs real-life human beings, consumers don’t all fit neatly into one-size-fits-all packages. We travel internationally, make large and impromptu purchases, and ship gifts to friends and family in far-flung corners of the world.\n\nThis reality makes it incredibly tough to tell the difference between fraud and legitimate orders, and merchants will always be at risk of falsely turning away actual purchases.\n\nAvoid this risk by leveraging an industry-leading [combination of machine learning and human intelligence](//blog.clear.sale/post/inhouse-outsourced-fraud-prevention-ecommerce-chargeback) to spot fraud and validate legitimate purchases. As a result, you’ll keep (and build) your client base without losing sales to emerging fraud behaviors and friendly fraud schemes.\n\nMaximize security. Minimize credit card false decline rates. Improve customer retention. What’s not to like?\n\nTo learn more about reducing false declines as part of a robust fraud-prevention program, contact us at (855) 379-4611 or [contact@clear.sale](mailto:contact@clear.sale).\n\n## Frequently Asked Questions\n\n### What is a false decline?\n\nA false decline, also called a false positive, happens when a legitimate transaction is blocked or questioned as if it were fraud, even though the order is valid and the card is genuine. The customer is real and the purchase should have been processed, but the fraud system flags it anyway.\n\n### Why are so many legitimate transactions being declined?\n\nSecurity breaches and more sophisticated fraudsters have pushed credit card companies to broaden their fraud criteria to catch more deceptive transactions. Fraud systems can weigh up to 500 distinct elements per transaction, and that level of complexity leaves more room for error, which catches legitimate orders in the net.\n\n### How much do false declines cost merchants compared to actual fraud?\n\nFalse declines cost merchants far more than fraud itself. The article reports retailers lose more revenue to false declines than to genuine credit card fraud, and a meaningful share of customers who experience a false decline will not return to that merchant, compounding the loss.\n\n### How can a merchant reduce false declines without weakening fraud protection?\n\nThe article recommends five steps: manually review questionable and high-risk orders, understand why declines occur and tune your settings, avoid rejecting orders based on assumptions, contact customers to verify a purchase, and use multilayered protection that combines analysts with deep-learning algorithms.\n\n### Why is rejecting transactions based on assumptions a problem?\n\nRejecting orders on generalizations, such as assuming every cross-border purchase is fraudulent, costs merchants legitimate sales. Decisions made without detailed data lose revenue, and every good sale you accept gives you more information to fine-tune your fraud process.\n\n### Why is manual review alone not always practical?\n\nManual review helps identify truly fraudulent orders, but nearly 30 percent of online orders can be subject to review, making it time-consuming and costly. For merchants with high order volumes or without in-house expertise, full manual review may not be feasible, which is why a combined human-and-machine approach works better."}