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Are Merchants Losing The CNP Fraud Battle - A QPS Whitepaper

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The whitepaper created by Team QPS provides an elaborate insight on rising card not present (CNP) fraud challenges faced by e-commerce/m-commerce merchants. You will get detailed information on how ML and AI are turning out as key elements in detecting fraud and preventing chargeback for boosting revenue and brand reputation for retailers.

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Are Merchants Losing The CNP Fraud Battle - A QPS Whitepaper

  1. 1. QPS WHITEPAPER Are Merchants Losing The CNP Fraud Battle?
  2. 2. 2 TABLE OF CONTENTS Introduction ______________________________________________________________3 What Brings The High Fraud Tide To CNP Shore?_______________________________ 4 CNP Fraud – A Sharp Knife Slicing Away Merchants Profit_________________________ 5 Machine Learning Playing Crucial Role________________________________________ 5 QPS Robust Solutions Combating Chargeback _________________________________ 6 QPS Empowering Merchants________________________________________________ 6 QPS Effectiveness Snapshot – Proven Track Record _____________________________ 8 Open API Integration ______________________________________________________ 9 Conclusion _____________________________________________________________ 10 Resources _____________________________________________________________ 11 Connect with QPS _______________________________________________________ 12
  3. 3. 3 INTRODUCTION The number of global internet users have reached 4 Billion in 2018 and are predicted to cross 6 Billion by 2022, bringing the connected devices on the Internet close to 50 Billion by 2020. Growing internet usage is the breeding ground of cybercrime which is predicted to cost the world $6 Trillion annually by 2021, posing the greatest threat for the global financial services industry. Retailers are estimated to lose $130 Billion to card-not-present (CNP) fraud globally during the next five years. In the U.S. alone, CNP fraud losses are predicted to exceed $7 Billion by 2020. Threats have increased manifold as fraudsters are getting more sophisticated in their attacks by using advanced methods. As rising CNP fraud is throwing a tough challenge, Account Takeover Fraud (ATO) and New Account Fraud (NAF) are also catching up fast and posing an even bigger threat for the online payments ecosystem. ATO fraud has reached a four-year high in 2017 resulting in a $5.1 Billion loss for merchants.
  4. 4. 4 What Brings The High Fraud Tide To CNP Shore? E-commerce is becoming a preferred marketplace as it is predicted to touch $11 Trillion by 2023 and the share of CNP transactions will growing accordingly. The e-commerce expenditure is destined with intensified growth which will attract more fraudsters as they always prefer the vulnerable path, and after the introduction of EMV chip cards, they are focusing more on such payment channels. CNP fraud remains the most prevalent fraud type and making huge losses to merchants, particularly in countries with high EMV migration rates. The challenge faced by retailers with CNP channel is to authenticate the cardholder as it cannot be done using the physical POS procedure hence, an alternative approach to authenticate the cardholder is required. Yahoo and Equifax data breaches during the past years have brought a fraud storm to the CNP world, as fraudsters are illicitly harvesting on the breached data, putting millions record containing personal information at risk. The stolen data is used for credential stuffing with the help of online bots to test the login credentials on numerous websites as well as facilitating account takeover attack. When it comes to payment cards, card-present fraud has decreased over the last couple of years; especially after EMV implementation but card-not-present (CNP) fraud continues to rise. The graph below is highlighting the growth of CNP credit card losses during the last five years.
  5. 5. 5 CNP Fraud – A Sharp Knife Slicing Away Merchants’ Profit Merchants are the immediate victim of the CNP fraud aftermath. They lose the merchandise ordered by the fraudsters, refund money to the customer whose payment information was used by a fraudster, and further pay associated chargeback fees. This can have large ramifications for merchants, including the time and cost to examine the chargeback, dealing with the customer’s frustration due to canceled purchases and ensuring that this customer is not lost. Quatrro Processing Services (QPS) has been serving merchants with an ever-evolving approach for preventing fraud and chargeback.QPS’ innovative approach of fraud prevention driven by Artificial Intelligence (AI) and Machine Learning (ML) helps merchants to identify and prevent the risk of fraud. QPS’ smarter fraud mitigation strategy helps merchants to catch the fraud before the product is shipped and thus saves on fraud and prevents the chargeback. Machine Learning (ML) Playing a Crucial Role Use of ML to detect anomalous behavior is an emerging and effective method, enabling faster detection of suspicious pattern. Designing, implementing and upgrading the fraud detection rules can be facilitated in real-time. AI complements ML to design and implement algorithms which help in understanding customers’ pattern from past cases and automate the threshold limiting for real-time analysis.
  6. 6. 6 AGGREGATOR MODEL - QPS’ aggregator model not only helps merchants in fraud prevention but also helps in effective chargeback control with its highly efficient amalgamation of advanced machine and human intelligence. It is an efficient E2E (end-to-end) proactive chargeback management and CNP fraud prevention solution, which is driven by real-time transaction monitoring. REAL-TIME TRANSACTION MONITORING–Real-time monitoring strategy acts as a super quick model providing a resolution within 300 million seconds by analyzing multiple authentications including advanced Big Data analytics. BATCH MODE PROCESSING - Large data volumes are processed efficiently with QPS batch mode processing which provides in-depth transaction analysis. With this method, comprehensive verification is achieved in resolution time between 30 minutes – 24 hours through human eye intervention. CHARGEBACK PROPENSITY RATE (CPR) – QPS’ proactive chargeback prevention through CPR eliminates the dimension of fraud, threatening businesses. For generating CPR, a rating from HIGH/ MEDIUM/ LOW is assigned to each work order in conjunction with the system and human intelligence. QPS has been helping businesses and retailers in mitigating CNP fraud losses by empowering them with robust fraud detection solutions, layered with comprehensive data analytics services. Below is the ever-evolving CNP fraud & chargeback prevention model by QPS. QPS Empowering Merchants QPS Robust Solutions Combating Chargeback
  7. 7. 7 E2E CNP Fraud & Chargeback Management QPS’ solutions consist of cutting edge technology supported by a complete back-office services function ensuring the reduction in false positives. BIG Data and social media analytics help in evaluating rules/algorithms, assessing fraud patterns and trends, reducing chargeback and friendly fraud. An E2E fraud protection solution has been tailor-made to enhance order acceptance rates combating chargeback before service deliveries & order shipments. CNP Secure- An Al-enabled Solution For e-commerce Fraud Prevention QPS’ smarter fraud detection solution - CNP Secure provides an effective chargeback and fraud protection solution. AI-driven CNP Secure is integrated with vital elements for higher accuracy and real-time prevention as given below:  Advanced Access Control Engine  Core Decision Engines For Managing Rules & Scoring Modules  Advanced ML Algorithms For Fraud Scores And CPR Ratings  Open API For Easy And Fast Integration  Next Level Business Logic Layer Module For Fast Decisions Facilitating Payments Security with Open API Advanced machine learning through open API and human eye intervention enhance the capability of fraud detection, reduce chargeback and boost profits. Analysts derive the fraud score by analyzing a powerful database highlighting customer's behavior on specific merchants and then negating the chargeback propensity termed as the Chargeback Propensity Rate (CPR). QPS’ model of fraud prevention helps you to identify the propensity/risk of a fraudster committing fraud and protect your business by deploying a multilayered fraud prevention strategy.
  8. 8. 8 QPS CNP fraud prevention services travel through the API channel, making it feasible for clients to integrate their transaction data quickly and conveniently. The API system is a technology marvel through which QPS can share the service response within a minute for a real-time transaction and within 48 hours in case of bulk mode. The futuristic design of API integration allows machine learning models to nab fraudsters at every turn and always be one step ahead of them. APIs allow the data to be easily embedded or interwoven throughout, to help ensure a smooth and integrated user experience. “AI and machine learning driven CNP fraud fighting models are yielding 30% increase in fraud detection rate over previous approaches. An amalgamation of AI and API, as a vital extension of FinTech is an ideal approach to provide the level of protection that today’s business demands. QPS with its technology advances and futuristic fraud fighting strategies, provide merchants the confidence and security layer to fight CNP fraud and chargeback. “ - Manu Sharma, AVP Expert Systems, QPS QPS Effectiveness Snapshot – Proven Track Record
  9. 9. 9 With API integration in place, QPS is able to make live data accessible for real-time transaction monitoring and prevent fraud before it happens. QPS API is complemented with unique Blocking and Bypass Engines, which create extensive fraud management efficiency for debit/credit card issuers. It helps in monitoring transactions for the specific merchant and terminal levels or at MCC and country levels. This Increases CNP transaction approval rate while reducing processing and customer service time through operational efficiencies and mitigating the risk of customer attrition. Meticulously Advanced BIG Data Analytics Services It includes comprehensive analytics services for evaluating rules and assessing fraud patterns which will help in improving decision accuracy and ensuring fraud loss reduction, covering the following:  Identifying fraud trends and patterns  Creative, interactive analysis to uncover patterns that are most likely to be indicative of fraud  False-positive review
  10. 10. 10 Conclusion QPS plays the role of an ideal aggregator with highly efficient scoring and identity data solution along with email verification coupled with AI and human intelligence. QPS highly skilled resource pool provides expert analysis to combat CNP fraud by employing a multi- layered approach for identity verification and fraud prevention. We will protect merchants’ brand reputation and their customer's trust with our 24*7*365 fraud mitigation approach. “Embracing AI and robotics are vital for achieving our goal of e-commerce fraud prevention technologies advancement. With fraud strategies evolving, we need to work together to make sure that we protect businesses against rising fraud and chargeback with a smarter approach driven by machine learning and open API.” - Ankit Maharaj Singh, VP, QPS
  11. 11. 11 Resources https://www.thepaypers.com/expert-opinion/card-not-present-fraud-are-you-even-aware-of-your- options-to-combat-cnp-fraud-/773006 https://www.clear.sale/infographics/cnp-fraud-is-skyrocketing https://www.paymentscardsandmobile.com/card-payments-rise-to-24-of-total-e-commerce-spend/ https://cybersecurityventures.com/cybersecurity-almanac-2019/ https://cybersecurityventures.com/cybersecurity-almanac-2019/ https://cybersecurityventures.com/hackerpocalypse-cybercrime-report-2016/ https://www.globalbankingandfinance.com/the-migration-of-card-not-present-fraud-in-europe-and- how-to-fight-it/ https://www.printful.com/blog/the-basics-of-ecommerce-fraud-what-is-it-and-how-to-manage-it/
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